Testing, Tools, and Frameworks

Companies are using DevOps to respond quickly to changing market dynamics and customer requirements. In any case, the biggest bottleneck in implementing a successful DevOps framework is testing. Many QA organizations leverage DevOps frameworks but still prefer to test their software manually. Unfortunately, this means less visibility and project backlogs, eventually leading to project delays and cost overruns. Smaller budgets and the desire for faster delivery have fueled the need for better approaches to development and testing. With the right testing principles, DevOps can help shorten the software development lifecycle (SDLC), but not without costly mistakes. Many organizations are adapting their traditional sequential approach to software development to be better equipped to test earlier and at all stages. Everyday Test Automation Challenges Development Time – Many companies think about developing their test automation frameworks in-house, but this is usually not a good idea because it is time-consuming and would cost you significant capital to develop it from scratch. Learning Curve – Companies that use code-based open-source tools like Selenium rely on tech-savvy people to manage their test automation framework. This is a big problem because non-technical business users may find it difficult and time-consuming to learn the tools. In addition, technical users and teams have more important tasks to perform than testing. Maintenance Costs – Most test automation tools use static scripts, which means they cannot quickly adapt to changes that occur due to UI changes in the form of new screens, buttons, user flows, or user input. What Is the Shift-Left Strategy? It is part of an organizational pattern known as DevSecOps (a collaboration between development, security, and operations) that ensures application security at the earliest stages of the development lifecycle. The term “shift left” refers to moving a process left on the traditional linear depiction of the software development lifecycle (SDLC). In DevOps, security and testing are two of the most commonly discussed topics for shifting left. Shift Left Testing Testing applications was traditionally done at the end of development before they were sent to security teams. Applications that did not meet quality standards, did not function properly, or otherwise did not meet requirements, would be sent back into development for additional changes. It resulted in significant bottlenecks during the SDLC and was incompatible with DevOps methodologies, which emphasize development velocity. As a result of shift left testing, defects can be identified and fixed much earlier in the software development process. This streamlines the development cycle, dramatically improves quality, and enables faster progression for security analysis and deployment to later stages. Shift-Left Security Security testing has become a standard practice in recent years following application testing in the development cycle. At this point, various types of analysis and security testing would be conducted by security teams. Security testing results will determine whether the application can be deployed into production or if it must be rejected and returned to developers for remediation. Due to this, long delays in development occurred, or the risk of releasing software without necessary security measures increased. Shifting security left means incorporating security measures throughout the development lifecycle rather than at the end. By shifting security left, the software is designed with security best practices integrated. Potential security issues and vulnerabilities are identified and fixed as early as possible in the development process, making addressing security issues easier, faster, and more affordable. It is no secret that IT has shifted left over the last two decades. It is possible to operate development infrastructure on a self-service basis today because it is fully automated: With AWS, GCP, or Azure, developers can easily provision resources without involving IT or operations. CI/CD processes automatically create, stage, and deploy test, staging, and production environments in the cloud or on-premises and tear them down when they are no longer required. CloudFormation and Terraform are widely used to deploy environments declaratively using Infrastructure-as-Code (IaC). With Kubernetes, organizations can provision containerized workloads dynamically using adaptive, automated processes. As a result of this shift, development productivity and velocity have increased tremendously, raising serious security concerns. The fast-paced environment leaves hardly any time for post-development security reviews or analysis of cloud infrastructure configurations. As a result, it is often too late to fix problems that are discovered before the next development sprint. What Is the Shift-Left Testing Principle? When developers test early in the development cycle, they can catch problems early and address them before they reach the production environment. By discovering issues earlier, developers don’t waste time applying workarounds to flawed implementations, and operations teams don’t have to maintain faulty applications. To improve the quality of an application, developers can identify the root cause of issues and modify the architecture or underlying components. The shift left approach to testing pushes testing to the left, or the earlier stages of the pipeline. By doing this, teams can find and fix bugs as soon as possible during the development process. In addition to increasing collaboration between testers and developers, shift left testing makes identifying key aspects that need testing early in development a whole lot easier. A major benefit of shifting testing is that testers are involved in the whole cycle, including the planning phase. Testing becomes part of the developer’s day-to-day activities as they become competent in automated testing technologies. Software is designed from the ground up with quality in mind when testing is part of the organization’s DNA. Benefits of Implementing Shift-Left Strategy A key benefit of “shift-left” testing is that it reduces overall development time. However, two key DevOps practices must be implemented to shift left: continuous testing and continuous deployment. Increased Speed of Delivery It’s not rocket science that the sooner you start, the sooner you finish. Therefore, identifying critical bugs early in the Software Development Cycle allows you to fix them sooner and more efficiently. The result is a significant decrease in the amount of time between releases and a faster delivery time. Improved Test Coverage Starting with the test execution right at the start of the development process, all software features, functionalities, and performance can be quickly evaluated. Test coverage percentages increase naturally when shift left testing is performed. The overall quality of the software is significantly enhanced by increased test coverage. Efficient Workflow Ultimately, shifting left is worth the effort and time it takes to implement. This allows the QA team to go deeper into the product and implement innovative testing solutions. Furthermore, it allows the testing team to become more comfortable with the tools and techniques involved. In addition, shift left testing simplifies several aspects of software development. Lower Development and Testing Cost Debugging is one of the most difficult aspects of software development. Usually, the cost of fixing a bug increases significantly as the software progresses in SDLC. Therefore, the earlier you find your bugs, the easier they are to fix. Let us take the example of a payment app that discovers a security vulnerability only after the release of its latest app version. Sure, it would have cost some more if the team had found the vulnerability earlier in development. But now, the company will have to spend significantly more time, effort, and money to fix the problem. In addition, the complexity of implementing changes in a production environment makes it difficult to do anything after the fact, not to mention the associated total cost of late maintenance.Gartner estimates the cost of network outages at $5,600 per minute – a total of over $300,000 per hour. Improves Product Quality The shift left testing approach positively impacts overall code quality with rigorous and frequent code quality checks. In addition, it facilitates timely correspondence between stakeholders, developers, and testers and ensures timely feedback, which helps improve code quality. This means that your customers receive a stable and high-quality end product. Also, you can listen to Siddharth Kaushal, who shared an idea of using shift-left testing and how automation tools can aid the idea of shift-left testing to make the process easily consumable by agile teams. Conclusion Once you mix Shift Left with leading DevOps practices – Continuous Testing and Continuous Development – you lay the foundation for Shift Left to win. Moreover, Shift Left is essential in a DevOps environment because. Teams discover and report bugs quickly. Features are released quickly. The quality of the software is outstanding.

In 2018, the release team was significantly smaller than it is now, releases were not yet happening regularly, and all of the company’s QA engineers played a part in the pre-launch inspection. That was very time-consuming, though, and it slowed down the overall development process significantly. It was decided that the testing of each app released would be conducted solely by the release team. Back then, the release cycles lasted two weeks. The team had 3 QA engineers, who weekly for 2–3 full-time days, checked the release build of one of the alternating platforms. In addition to checking the release, the guys were busy streamlining the release process, writing documentation, onboarding newcomers, and updating test cases in the TMS. There were a number of drawbacks to this approach: Defects could only be discovered during the 2–3 days of the check, so more time was required to fix them, and the Time-to-Market (TTM) increased. If anyone in the team was unable to take part in the testing of the release, the workload on the other team members was significantly greater, and so too was the time required for the check. Long-release checks are tedious, and the likelihood of a defect being missed increases. There is a low level of coverage across devices, meaning that specific defects were more likely to be missed. During the check, you had to get to grips with all the new features and the ways of configuring the test environment to suit them. The test cases and other documentation, therefore, have to be perfectly written before the point when the feature gets into the release. Otherwise, the inspection process would be slowed down: a lot of time would be wasted clarifying all the nuances. Changing the Release Inspection Process At the end of 2021, the decision was taken to scale up the release check to the QA engineers from all teams. And it was decided that, from 2022 onwards, we would move to weekly checks of both mobile platforms at the same time and stop doing the TMS TestRail in favor of Qase since the former was very slow and kept going down. Since the automatic branch cuts and the forming of the release build for the mobile app used to take place on a Friday evening, Monday was chosen as the most suitable day for checking the release. The tech leads in each team knew that, for four hours on a Monday, the QA engineers would be working solely on the release check. For those four hours, the tech leads had to remove, or at least minimize, any team activities in which the QA engineer was supposed to be involved. In turn, by the time the check started, the release team would prepare a relevant test environment, form the test runs and distribute them to all the cases. The aforementioned problems were thereby solved: All the bug reports are compiled in the first four hours of a Monday, and accordingly, the fixes are put into the release build at a much earlier stage. If a couple of QA engineers are unable to take part in the release check, this has practically no impact on how quickly the release check can be conducted. The release check does not take more than four hours — and it’s much easier to maintain one’s concentration and alertness for that kind of time interval. The level of coverage across devices goes up several times over. Certain very specific new features are initially checked by their “owners” and then gradually rolled out across the entire team. The release team also writes UI self-tests in conjunction with the QA Automation team, which develops various testing instruments. To achieve this, the following tools are used: Appium Kotlin, JUnit 5 Selenoid Allure The Upshot At this point in time, UI tests have covered about 30 percent of the total test cases in the acceptance set. They are launched immediately after the cut on the release branch, and the result of them, in the shape of an Allure report, is sent to Slack by a bot. As this automated process unfolds, the test cases are taken out of the release run’s pool. During the release check, the QA engineer on duty goes through the fallen tests manually and, where necessary, compiles a bug report: In order to keep the tests green and discover bugs ahead of time, they are launched on a dev-build every night. After that, the duty QA enters the new test update tasks or bug reports on a special dashboard. A range of tests can also be launched by anyone who wishes to do so with the help of GitHub Actions. As a result of the changes set out above, the duration of build release checks has fallen from around 72 hours to four hours without sacrificing anything in terms of the quality of the product. One of the problems that the release team encountered was that of time zones. Our staff is located in a wide range of different cities and countries, making it far from easy to conduct a simultaneous release check. However, given that most of the engineers are located in three time zones, it was decided that the time of the check should be made as close as possible, taking everyone’s work schedule into account. In Almaty, for instance, the release check starts first thing in the morning. Another problem is related to the fact that, in order to get a large number of engineers involved in the same process, a particular effort is required on the organizational front: Drawing up lists of the people who are going to take part in the release, taking vacations and days off into account. Redistributing cases in the release process if anyone has had any problems getting through them. Checking and preparing the test environment in good time, and doing the same thing with the methods of delivering the app build, so that there is no downtime. Checking to make sure that the developers promptly set to work on any defects discovered in the release build. Answering any questions that arise on the part of those involved in the process and dealing with any unexpected situations. To solve this problem, a flow of weekly duties was introduced by one of the QA engineers in the release team, who assumes responsibility for all the duties referred to above and independently accompanies the release from beginning to end. In the first instance, it was hard to work out how long the release check was going to take. To calibrate its duration, the progress on the cases it is going through is recorded at hourly intervals. It turned out that an interval of four hours was ideally suited to the task and enabled everyone to go through the release at a comfortable pace. Thereafter, the release team left in the flow a requirement to note the release’s progress. The table below shows the percentage of cases from the release run that have been completed at a particular stage of the release check. It can be seen that the total time spent on the check gradually falls: Now, the time required to check a release version of the app is gradually falling. With the transition to this flow, the TTM of product features was significantly reduced, and at the same time, the quality of the check was enhanced. The release process, meanwhile, became more predictable and transparent for all the other teams.

Today’s modern businesses require faster software feature releases to produce high-quality products and to get to market quickly without sacrificing software quality. To ensure successful deployments, the accelerated release of new features or bug fixes in existing features requires rigorous end-to-end software testing. While manual testing can be used for small applications or software, large and complex applications require dedicated resources and technologies like python testing frameworks, automation testing tools, and so on to ensure optimal test coverage in less time and faster quality releases. PyTest is a testing framework that allows individuals to write test code in Python. It enables you to create simple and scalable test cases for databases, APIs, and user interfaces. PyTest is primarily used for writing API tests. It aids in the development of tests ranging from simple unit tests to complex functional tests. According to a report published by future market insights group, the global automation testing market is expected to grow at a CAGR of 14.3%, registering a market value of US$ 93.6 billion by the end of 2032. Why Choose Pytest? Selection of the right testing framework can be difficult and relies on parameters like feasibility, complexity, scalability, and features provided by a framework. PyTest is the go-to test framework for a test automation engineer with a good understanding of Python fundamentals. With the PyTest framework, you can create high-coverage unit tests, complex functional tests, and acceptance tests. Apart from being an extremely versatile framework for test automation, PyTest also has a plethora of test execution features, such as parameterizing, markers, tags, parallel execution, and dependency. There is no boilerplate while using Pytest as a test framework. Pytest can run tests written in unittest, doctest, and nose. Pytest supports plugins for behavior-driven testing. There are more than 150 plugins available to support different types of test automation. The diagram below shows a typical structure of a Pytest framework. Pytest root framework. As shown above, in the structure, the business logic of the framework core components is completely independent of Pytest components. Pytest makes use of the core framework, just like instantiating the objects and calling their functions in the test script. Test script file name should either start with `test_` or end with `_test`. The test function name should also be in the same format. Reporting in Pytest can be taken care of by Pytest-HTML reporting. Important Pytest Features 1. Pytest Fixtures The most prominently used feature of Pytest is Fixtures. Fixtures, as the name suggests, are decorator functions that are used in pytest to generate a specific condition that needs to be arranged for the test to be run successfully. The condition can be any precondition, like creating objects of the classes required, bringing an application to a specific state, bringing up the mockers in case of unit tests, initializing the dependencies, etc. Fixtures also take care of the teardown or reverting of the conditions that were generated after the test execution is completed. In general, fixtures take care of the setup and teardown conditions for a test. Fixture Scope The setup and teardown do not have to be just for the test function. The scope of the setup may differ from a test function to as large as the whole test session. This means the setup-teardown is executed only once per defined scope. To achieve the same, we can define the scope along with the fixture decorator i.e., session, module, class, and function. Fixture Usage Pytest provides the flexibility to use a fixture implicitly or call it explicitly, with autouse parameter. To call the fixture function by default, the autouse parameter value needs to be set to True, else to False. 2. Conftest.py All the fixtures that are to be used in the test framework are usually defined in conftest.py. It is the entry point for any Pytest execution. Fixtures need not be autouse=True. All defined fixtures can be accessed by all the test files. conftest.py needs to be placed in the root directory of the Pytest framework. 3. Pytest Hooks Pytest provides numerous hooks that will be called in to perform a specific setup. Hooks are generator functions that yield exactly once. Users can also write wrappers in conftest for the Pytest hooks. 4. Markers Pytest provides markers to group a set of tests based on feature, scope, test category, etc. The test execution can be auto-filtered based on the markers. i.e., acceptance, regression suit, login tests, etc. Markers also act as an enabler for parameterizing a test. The test will be executed for all the parameters that are passed as the argument. Note, Pytest considers a test for one parameter as a completely independent test. Many things can be achieved with markers, like marking a test to skip, skipping on certain conditions, depending on a specific test, etc. 5. Assertion Pytest does not require the test scripts to have their assertions. It works flawlessly with Python inbuilt assertions. 6. Pytest.ini All default configuration data can be put in pytest.ini, and the same can be read by the conftest without any specific implementation. PyTest supports a huge number of plugins with which almost any level of a complex system can be automated. A major benefit of Pytest is that any kind of implementation of the structure is done using raw Python code without any boilerplate code. It means implementing anything in Pytest is as flexible and clean as implementing anything in Python itself. Amidst shorter development cycles, test automation provides several benefits that are critical for producing high-quality applications. It reduces the possibility of unavoidable human errors taking place during manual testing methods. Automated testing improves software quality and reduces the likelihood of defects jeopardizing delivery timelines.

Testing is an extremely important part of any software development process. It is an umbrella term used to refer to various stages involved in ensuring that a product performs adequately. One such stage of testing is integration testing. I and T is a term often used by software developers. It is an abbreviated form of the term integration and testing, also sometimes simply called string testing, thread testing, or integration testing. Software is made up of various modules; in this process of testing, a developer combines all the various modules of software and then tests them together. It is a vital part of any software development process because it helps understand not only how the different modules of software interact with each other but how smoothly they are able to work as a singular unit. What Is Integration Testing; Its Purpose and Its Objectives? If we had to understand what integration testing is clearly, an example of a pen would be perfect. A pen comprises three parts; its cap, its body, and its ink. All these parts are produced and manufactured separately. The quality check is also done individually for each part. However, a pen is not launched until all the parts are put together and tested as a single unit. How well a pen writes depends on how it performs when all the parts are put together and then tested as a whole. This is the process of integration testing in a nutshell. Process of Integration Testing Integration testing is a little more complicated than simply putting together a pen and running it over the paper. In this process, a developer merges the various modules that comprise software together. In doing so, they make sure to keep the fundamental blueprint of the software in mind. The testing phase, which is the phase performed before integration testing, ensures that all the modules are merged correctly to deliver software that functions. A developer then connects with the client or the firm that the software is being sold to or developed for and then tries and understand their requirements, expectations, and what exact functions they need the software to perform. Keeping these expectations as parameters in mind, developers then run the software to ensure that its modules can interact with each other to perform specific functions. Why Is Integration Testing Performed? No part of a product is sent for assembly until it is fully functional. So, it is only natural to assume that if you put together a bunch of functional parts of a product, or in this case, a program, the result should also be a fully functional product. However, that is not the case. Many times, different modules of software work pristinely by themselves but have trouble interacting with other modules. It is also not uncommon for various modules to not be able to perform a specific function when combined. All these reasons make the process of integration testing an extremely important one for developers and software alike. Objectives of Integration Testing Bringing together different modules to create a fully functional application Ensuring real-time application by incorporating the changing requirements of a client into the application itself. Catching and resolving the errors that might have been missed during the unit testing stage. Dealing with problems such as incorrect data formatting, API response generation, external hardware being erroneous, and third-party services presenting an incorrect or incomplete interface for the application., Ensuring that individually working components of a module work adequately when integrated. Testing how the application or software developed performs the functions it is required to. How Popular Is Integration Testing Among Developers? As mentioned above, testing software or an application can get quite boring super quick; it is not challenging for a developer at all, does not require much creative liberty, and can definitely get extremely monotonous and time-consuming. However, it is still one of those phases that a developer cannot even fathom skimping out on. This is because testing ensures that any application developed by a software engineer is not only functional and satisfactory but that it provides exceptional results and meets the expectations of the developer who designed it and the client it was designed for. Other than this, any application that has undergone testing witnesses an increase in its value of up to five times its base value. This is because any product or application that has been tested multiple times has the confidence of its developers, and the clients are assured that it is bound to have minimal to no errors during its practical application The trial-and-error method is one of the most popular methods that has been in existence since ancient times. While it is certainly time-consuming and tedious, people still do so because they know that testing out a new idea, procedure, or product would provide them with better, more sustainable results in the long run. Once the creators of a product, and in this case, developers of the software, have put their product through multiple stages of testing, they can catch and resolve the practical errors of their program. Being thorough with all stages of application testing, especially Integration testing, is any developer’s thumb rule, and correctly so.

Do you know Cucumber is a great tool used to run acceptance tests using the plain-text functional descriptions with Gherkin? Behavior Driven Development strategy or BDD, as it is popularly known, is implemented using the Cucumber tool. The best part about using the Cucumber BDD framework are: Tests are first documented before being implemented. Tests are easy to understand for a user who doesn't even know the functionality. It efficiently combines the automated tests having living documentation and specifications that can be executed. Can't wait to get started with Cucumber? To help you out, we will be diving into some of the best Cucumber practices that will enable you to write better scenarios using the Gherkin language. You will also get a clearer picture of the Behavior Driven Development concepts with these practices. Basics of Cucumber BDD Framework Before we jump dive into Cucumber best practices, there are a few things you need to understand about the Cucumber BDD framework. First, to work with Cucumber for Selenium automation testing, you would need three types of files as described below: Feature File: It serves as an entry point to the Cucumber tests. It is the file where your test scenarios are written in the Gherkin language. A Feature file may contain single or multiple test scenarios. The Feature file is used as a live document and ends with a .feature extension. Step Definition: It contains the piece of code, in your chosen programming language, with some annotations attached to it. On seeing a Gherkin Step, Cucumber executes the code which is contained within the Step. The annotation has a pattern that links the Step Definition to the matching steps defined in the Feature File. Others: We may need other files to execute tests at different levels. For example, we are testing the Web UI; then, we will be using a tool like Selenium, which might use a framework of its own like the Page Object Model. Since, in this post, our primary focus is Cucumber best practices, let us leave the other files' details for some other time. In the next section of this blog, we will understand feature files in detail and how we can use them efficiently. These are some of the essential practices you should implement for successfully using Cucumber and Selenium. As already stated, we will use Gherkin to write the scenarios in the Cucumber BDD framework. Let us now understand in detail some Cucumber best practices. 1. Creating a Feature File We will start by creating a file in our project structure that will consist of the steps to mimic a certain functionality. Since, in this post, we will understand Cucumber's best practices, we will only focus on how we can write our features file to model our test scenarios. We will see the practical implementation later. As an example, let us take the Login functionality using Gherkin. Use Case: Model the behavior of logging into an application with valid credentials: Create a file with .feature extension inside the project folder. For example, let us name it "Login.feature". Inside the file, we will give a title depicting the functionality. So in our example, it can be something like "Feature: Login Action." We will now start writing our scenarios in the feature file. The general syntax for writing a scenario in a feature file is: As [a user] I want to [perform some action] for [ achieving a result] So using the above two points, let us start with writing a Feature: Feature: Login Action Scenario: As an existing user, I want to log in successfully. With this, you need to make a note of the important points listed below: First, it is advised that you make your feature file independent from other functionalities. This means trying to make each feature specific to a single functionality. You can make your feature file understandable by using the same language as the requirement is specified, i.e., always try to describe the actions as they would have been done by the client. Next, in the feature file, you will be writing the Scenarios. Scenarios are simply the behavior of a functionality. While testing, we might have to write multiple scenarios to cover the test scope. To write a scenario, we use Keywords defined by Gherkin. The primary keywords used in Gherkin sentences are: 1. Given: Defines the pre-condition of the test. 2. When: Defines the user action that will be performed. 3. Then: Defines the post-condition or the outcome of the test. 4. But: Used to add negative conditions to the test. 5. And: Used to add a condition(s) to the test. Note that you only need to state what you want to do in the feature file and not how you want to do it. The how part will be taken care of in the Step Definition file, which we will see later in this article. See below an example of a poorly written scenario: Scenario: As an existing user, I want to login successfully Given the user is on the Home page When the user navigates to the Login page And the user can see the login form And the user enters username and password And the user is able to click on the Submit button Then the user is logged in successfully And the successful login message is displayed There is no point in writing such lengthy scenarios with unwanted details as it makes it difficult to read and maintain. A better way to write the same scenario with fewer lines is as follows: Scenario: As an existing user, I want to login successfully. Given the user is on the Home page When the user navigates to the Login page And the user enters username and password Then the successful login message is displayed Did you see how with fewer sentences, we can depict the same scenario by including only the necessary details and ignoring beating around the bush? :slightly_smiling_face: Below are a few points that you need to keep in mind while writing scenarios in Gherkin: Always remember that the order of your statements must follow Given-When-Then. Since 'Given' implies a pre-condition, 'When' refers to an action, and 'Then' refers to a post-condition for the action, it will be unclear to write 'Then' before 'When.' Always remember that Given-Then-When should occur only once per scenario. You can extend any sentence by using 'And.' This is because every scenario depicts an individual functionality. If we will include multiple Then-When, there would be no point in being a single functionality. Make sure that your sentences are consistent when talking about perspective. This means if the scenario description is described in first person, then the sentences should also be in first person to maintain homogeneity. Try to write the minimum steps in a scenario. It helps in making the scenario understandable and clear. Try writing brief sentences which are explanatory. Try to make your scenarios independent. If the scenarios are interlinked, it may generate errors, for instance, in the case of parallel test execution. 2. Separating Feature Files When testing with live applications, you might have to create multiple feature files. It becomes crucial to bifurcate the feature into different files. You can organize files so that all the features related to a specific functionality are grouped in a package or a directory. This is another one of the essential Cucumber best practices we recommend for seamless BDD implementation. For example, consider an e-commerce application; you can organize the file such that, at the first level, you can have a package, say Orders, and in that, you can have multiple features like Pending Orders, Completed Orders, Wishlist, etc. Doing so will make your project organized, and it will be easy for you to locate the tests as per the functionality. 3. Using The Correct Perspective At times it becomes very confusing as to what perspective should you write your scenarios in; the first person or third person. The official Cucumber BDD framework documentation uses both points of view. Below are the arguments for both the point of view: First Person BDD was created by Dan North, who, in his article "Introducing BDD," recommends the use of the first person. Using the first person is rational since it depicts keeping yourself in place of the person actually performing the action. Third Person The people who prefer the third-person point of view state that using the first-person can confuse the reader. It does not clarify who is performing the action, i.e., an individual user, an admin, or some user with a particular set of roles. It is argued that third-person usage shows the information formally and minimizes the risk of making any false assumptions about who is actually involved in performing/testing a scenario. So, all in all, there is no mandate on using any one point of view; the one practice that you have to remember is to maintain consistency. The description should resonate with the test steps and be from a single perspective. 4. Additional Keywords Used in Gherkin Apart from the commonly used keywords discussed above, there are a few more that are used in Gherkin. If you want to implement the Cucumber best practices, this is an important one to start practicing. Background Background simplifies adding the same steps to multiple scenarios in a given feature. This means if some common steps have to be executed for all the scenarios in a feature, you can write them under the Background keyword. For example, to order a product from an e-commerce website, you will have to do the following steps: Open the website. Click on the Login link. Enter the username and password. Click on the Submit button. Once you have completed the above steps, you can search for the product, add that product to your cart, and proceed with the checkout and payment. Since the above steps would be common for many functionalities in a feature, we can include them in the Background. Feature: Add To Cart Background: Given the user is on the Home page And the user navigates to the Login page And the user enters username and password Then the successful login message is displayed Always try to keep the background as short as possible since it will be difficult to understand the following scenario if it is kept lengthy. The key with the Cucumber Feature file is the shorter, the better. Scenario Outline A Scenario outline is similar to the test data corresponding to a test scenario. It is no compulsion to write a scenario with a scenario outline, but you can write it if needed. Scenario outline: Order with different quantities Given: User searches for HP Pen Drive When: Add the first result on the page with quantity <qty> Then: Cart should display <qty> pen drive Examples: |qty| |1| |5| |24| Doc Strings If the information in a scenario does not fit in a single line, you can use DocString. It follows a step and is enclosed within three double quotes. Though often overlooked, it is one of the most crucial Cucumber best practices to follow. Scenario: Login with a valid-user Given the user is on the Home page And the user navigates to the Login page And the user enters username and password Then the successful login message is displayed with text: “You have successfully logged into your account! There are multiple discount offers waiting for you!!” Data Table The Data Table is quite similar to Scenario Outline. The main difference between the two is that the Scenario outline injects the data at the scenario level, while the data table is used to inject data at the step level. Data tables serve to input data in a single step. It is not necessary to define the head of a data table, but it is advised to maintain a reference to data for easy understanding. Scenario: Login with a valid-user Given the user is on the Home page And the user navigates to the Login page And the user enters <username> and <password> | username | password | | test1 | password1 | As shown in the example above, you can use a data table in single steps with different data that you may need to inject. Languages Cucumber is not limited to writing the scenarios in English. Similar to the conventions followed in English, you can write the scenarios in multiple human languages. The official Cucumber documentation has all the information about using the Language feature and the dialect code of various languages. For example, to use French as the language to write your scenarios, you can use the # language as a header in the functionality like below: # language : fr (Note: fr is the dialect code for French) Tags There may be cases when you need not execute all the scenarios of the test. In such cases, you can group specific scenarios and execute them independently by using Tags. Tags are simply the annotations used to group scenarios and features. They are marked with @ followed by some notable text. Examples: @SmokeTest @RegressionTest Scenario: …. @End2End Feature: …. Note that the tags are inherited in the feature file by all the components, viz the scenario outline, scenario, etc. Similarly, if there is a tag on the Scenario Outline, the data examples will also inherit the tag. The above examples can be configured for execution as shown below: tags={“@End2End”} First, all the scenarios of the feature under @End2End tag would be executed.tags={“@SmokeTest”} All the scenarios under @SmokeTest would be executed.tags={“@SmokeTest , @RegressionTest”} This type of definition denotes OR condition hence, all the scenarios that are under @SmokeTest tag or @RegressionTest the tag would be executed.tags={“@SmokeTest” , “@RegressionTest”} In such a definition, all the scenarios under the @SmokeTest AND @RegressionTest will be executed.tags={~“@End2End”} All the scenarios under @End2End the tag will be ignored.tags={“@SmokeTest , ~@RegressionTest”} All the scenarios under @SmokeTest the tag will be executed, but the scenarios under the @RegressionTest tag would be ignored. Similar to the examples above, you can make combinations of tags as per your requirement and execute the scenarios/features selectively. 5. Step Definition(Step Implementation) So far, we have only understood what our scenarios would do as part of Cucumber best practices. But the next and vital step to automate using Cucumber Selenium is adding a Step Definition that would do the how part, i.e., how would the scenario execute? When Cucumber runs a step in the Scenario, it refers to a matching Step Definition for execution.Implementation of steps can be done in Ruby, C++, Javascript, or any other language, but we will use Java as our example. If you are using an IDE that already has Gherkin and Cucumber installed, you will see suggestions to create a new .java file or select one which has the steps implemented already. On selecting any of the options, a method will be created in the class. For instance, we are resting the step definition for the below step: Given the user is on Home Page. A method would be generated automatically, with annotation having the header text the same as that of the step description: @Given(“^the user is on Home Page$”) public void homePage() throws Throwable{ //Java code to check the above description …. ….. } To create step implementation of scenarios that get data from Scenario Outline or Data Tables, the data is included in the annotations as regular expressions, along with passing as a parameter to the method. @When(“^Add the first result on the page with quantity \”([0-9]+)”\$”) public void addQuantity(int qty) throws Throwable{ //Java code to pass qty in the qty field … ... } And that is how you can implement the steps that you write in the Feature file using Gherkin. Always remember the below points while implementing step definitions- Try to create reusable step definitions. Reusable step definitions will make your tests maintainable, and in case of any change in the future, you will have to make minimum changes to your framework. You can use Parameterization in scenario outlines to reuse step definitions. Wrapping Up You are now familiar with some of the most important Cucumber best practices to follow with your BDD strategy or while implementing Cucumber and Selenium. To summarize this blog post, we would recommend you to: Try to write scenarios in the feature file in a way the user would describe them. This would help you create crisp and concise steps. Avoid coupled steps, i.e., always prefer creating one action per step. This would save you from unnecessary errors. Reuse step definitions as much as possible to improve code maintainability. Try to leverage the use of Background to minimize unnecessary addition of the same steps in different scenarios. Happy testing!

Penetration testing is an essential strategy used by managed service providers (MSPs) to provide their clients with greater cybersecurity. Businesses use this technique to learn how their information security staff and procedures would behave under attack. The primary purpose of penetration tests is to mimic an attack on a network to identify security gaps in an organization's defenses and test the readiness of its security team. According to some predictions, a cyberattack is projected to occur in the United States every 14 seconds, with total losses estimated to exceed $21.5 billion. Penetration testing services can help a business prepare for hacker assaults, malware, and other threats by continuously and routinely testing for weaknesses, vulnerabilities, and inappropriate user behavior on apps, services, and networks. This article delves deep into penetration testing, its types, importance, advantages, techniques, and some of the standard tools included in a genuine penetration test. What Is Penetration Testing? Penetration testing, also known as pen testing, is a security activity in which ethical hackers attempt to compromise an organization's systems in supervised red team/blue team drills. It is a method for "stress testing" the security of your IT system. It utilizes penetration techniques to examine the network's safety and security in a regulated manner. The objectives of a penetration test may include evaluating the procedures, preparedness, and teamwork of security personnel, cooperation between in-house and outsourced security providers, security vulnerabilities and gaps, security tools and defenses, and incident response procedures. Two Sides Comprise a Penetration Test: It is a real test that enables a company to identify its security vulnerabilities and repair them. It guarantees that security teams and tools are up-to-date and "battle-tested"; this is crucial given the rarity of large-scale security incidents and the constant evolution of attacker tools, methods, and procedures (TTPs). A penetration test can help a business find its vulnerabilities and assess its security processes without waiting for a genuine attack. However, penetration testing is not restricted to just networks; it may also be run on individual web applications and smaller equipment. The three most frequent kinds of penetration tests are as follows: Internal penetration testing — the attack originates within the network. External penetration test — the assault commences from outside the boundary. Physical penetration test — the tester achieves physical access to the organization by employing social engineering and other means. Why Penetration Testing? There are several reasons why penetration tests (or "pen tests") should be performed routinely. Firstly, penetration testing can aid in ensuring the following: security of user data, identifying security flaws, locating system flaws, and evaluating the overall effectiveness of existing defenses. In addition, penetration testing can help a company remain current with each new software release. As risks evolve, financial and PI data must be secured iteratively; as new devices are introduced to a system, moving data between different endpoints requires ongoing monitoring and compliance review. Importance of Penetration Testing Similarly, penetration testing provides several significant advantages. It enables managed service providers to demonstrate competence and proactively handle vulnerabilities. It helps enterprises save money by preventing network downtime. Finally, penetration testing methods can aid MSP customers in meeting regulatory standards and avoiding fines. It is essential for preserving an MSP's image, reputation, and customer loyalty. Penetration testing is unstructured and inventive. For instance, while one test may employ brute force, another may use spear phishing to target corporate officials. This ingenuity is crucial, as competent attackers will employ the same abilities and inventions to identify the organization's security vulnerabilities. An additional advantage of penetration testers is that external contractors conduct them, and it is possible to select how much information about internal systems to provide. A penetration test can imitate either an external attacker unaware of the internal network or a privileged insider. The best way to evaluate a company's defenses is using a "blind" penetration test, in which the security and operations teams are unaware of its existence. However, even if internal teams are aware of the test, it can still serve as a security drill to evaluate how tools, people, and security processes interact in a real-world scenario. What Are Penetration Testing Types? According to industry experts, the three most used classifications for penetration testing are black box testing, white box testing, and grey box testing. The categories correspond to various forms of cyberattacks and cyber threats. The focus of black box testing is a brute-force approach. This scenario simulates the actions of a hacker unaware of the complexity and structure of an organization's IT system. Therefore, the hacker will undertake an all-out attack to identify and exploit a vulnerability. The penetration test provides the tester with no information about a web application's source code or software architecture. Instead, the tester employs a "trial and error" methodology to determine where IT infrastructure vulnerabilities exist. This penetration testing method resembles a real-world scenario; however, completion can be lengthy. White box penetration testing is the antithesis of this first method. In white box testing, the tester has complete IT infrastructure knowledge and access to the web application's source code and software architecture. This allows them to hone in on specific system components and conduct component-specific testing and analysis. This procedure is quicker than black box testing. On the other hand, white box penetration testing employs more advanced penetration testing tools, such as software code analyzers and debugging applications. When the tester has a limited understanding of the internal IT infrastructure, grey box testing combines manual and automated testing techniques. For instance, the tester may obtain the software code but not the system architecture specifications. Gray box penetration testing is a combination of white box and black box testing that enables the user to employ automated tools for the full-scale attack while focusing their manual work on discovering "security flaws." These broad categories of penetration testing methods can be further broken into granular divisions. Other forms of penetration tests include the following: Social Engineering Test In this test, an individual is coerced into divulging sensitive information, such as passwords and business-critical data. Targeted helpdesks, workers, and processes focus on these assessments, which are conducted primarily via phone or the internet. Human mistake is the most common cause of security flaws. Therefore, all staff employees should adhere to security policies and regulations to prevent social engineering intrusions. Examples of these norms include the prohibition against disclosing sensitive information through email or telephone. In addition, it is possible to conduct security audits to discover and repair process issues. Web Application Testing One can determine if the program is vulnerable to security flaws using software methods. It verifies the security vulnerabilities of web applications and software installed in the target environment. Physical Penetration Test Strong physical security methods are used to secure sensitive data. This is typically utilized in government and military facilities. All network devices and access points are examined for potential security vulnerabilities. This test is not particularly useful for software testing. Network Services Test This is one of the most typical penetration tests. The network's entry points are determined based on the systems accessed to determine the types of vulnerabilities present. This can be accomplished either locally or remotely. Client-Side Test Typically, a client-side penetration test can discover specific assaults. Cross-site scripting (XSS) assaults, form hijacking, HTML injections, clickjacking attacks, and malware infestations are a few examples. It seeks out and exploits vulnerabilities in client-side software applications. Remote Dial-Up War Dial It searches for modems in the environment and attempts to log in to the computers linked via these modems by guessing or brute-forcing the password. Wireless Security Test It identifies open, unauthorized, and less secure hotspots or Wi-Fi networks and connects them. All penetration testing methods should evaluate internal and external IT infrastructure components. Penetration Testing Services There are both manual and automated penetration testing services. Manual Penetration Testing Manual pen testing is exhaustive and methodical. Typically, it is performed by a contractor or security consulting firm whose testing scope is agreed upon with the client. Within this scope, an ethical hacker searches for vulnerabilities, attempts to compromise the organization's systems and compiles a comprehensive report describing their findings and recommending corrective action. Pros of Manual Penetration Testing: Capability to simulate sophisticated attack campaigns involving numerous threat vectors. Identifies weaknesses in business logic, as opposed to generic vulnerabilities that are simple to detect with automated methods. Still using automated technologies, human penetration testers can mix automatic scans with manual investigation and analysis. False positives are not a worry, as the penetration tester verifies all findings before generating the report. Capability to uncover zero-day vulnerabilities. Cons of Manual Penetration Testing: High cost and considerable effort are required for each penetration test. Typically, testing is only possible periodically or annually, leaving the firm vulnerable to zero-day attacks or vulnerabilities caused by changes to production systems. Depends heavily on the abilities of the tester. Unskilled testers or those lacking knowledge of the organization's industry or technology stack are susceptible to overlooking critical vulnerabilities and insights. From the organization's standpoint, the setup is complex, requiring contracts, a precise scope specification, and collaboration with internal stakeholders. Penetration Testing as a Service (PTaaS) The new paradigm of penetration testing as a service (PTaaS) provides enterprises with an automated platform for performing penetration testing on their systems. PTaaS systems utilize technologies such as automatic vulnerability scanning, dynamic application security testing (DAST), and fuzzing to identify security vulnerabilities and attempt to attack them automatically. Pros of Penetration Testing as a Service (PTaaS): The self-service paradigm allows the client to select which systems and at what intervals each test will be performed via a web interface. Allows firms with a minimal or nonexistent security team to conduct penetration testing. Most services provide a subscription or pay-per-use pricing at reduced prices and flexible payment options. PTaaS solutions can provide automated reporting tailored to the enterprise's needs, including compliance requirements. Cons of Penetration Testing as a Service (PTaaS): Increases the organization's responsibilities, as they must define the testing schedule and independently review results. Some cloud providers need permission to perform automated penetration testing on their infrastructure and limit testing to a predetermined time frame. Encryption of under-test systems can make PTaaS services more difficult to use. Most services are unable to uncover business logic flaws. More false positives than manual testing. Bright is a PTaaS service that automates numerous manual penetration testing procedures. Bright offers a PTaaS platform that eliminates many drawbacks of manual PTaaS services. It employs artificial intelligence (AI), fuzzing techniques, and extensive threat intelligence to identify a lengthy list of known vulnerabilities in addition to zero-day attacks and business logic flaws. In addition, Bright leverages browser automation to deliver zero false positives; it scans many layers of your environment, including online applications and APIs, and generates findings comparable to those caused by manual penetration testers. Penetration Testing Process There are six acknowledged penetration testing procedures. They include planning, reconnaissance and information collecting, scanning and discovery, attack and gaining access, maintaining access and penetration, and risk analysis and report generation. These steps may vary slightly from MSP to MSP based on the desired frequency and type of penetration testing. 1. Preparing for Pen Testing Determining the test's scope and objectives is the initial step in penetration testing. Next, MSPs must collaborate with their customers to determine the necessary logistics, expectations, objectives, and systems. Finally, during the planning phase, it will be determined whether a black-box, white-box, or grey-box penetration testing method will be utilized. 2. Reconnaissance and Source Information During this phase, the "hacker" or penetration tester attempts to learn as much as possible about the target. They will collect information regarding end uses, systems, and applications, among other things. The information will be utilized to conduct a precise penetration test, utilizing a comprehensive and exhaustive rundown of systems to determine precisely what must be handled and assessed. During this phase, search engine queries, domain name searches, internet footprinting, social engineering, and even the examination of tax records may be employed to gather personal information. 3. Researching and Discovering The purpose of the scanning and discovery phase is to determine how the target system will react to various intrusion attempts. The penetration tester often employs automated penetration testing tools to identify initial vulnerabilities. The penetration tester uses both static and dynamic analysis methods. Static analysis examines an application's code to forecast how it will respond to an intrusion. The dynamic analysis examines the code of an application while it executes, offering a picture of its performance in real time. In addition to network hosts, a pen tester will investigate network systems, servers, devices, and hosts. 4. Attack and Obtain Admission After thoroughly grasping the scope and components to be evaluated, the penetration tester will launch an attack in a simulated and controlled environment. The tester may take control of a device to extract data, perform a web application assault such as cross-site scripting or SQL injection, or conduct a physical attack, as described earlier. This phase determines how deeply a tester may penetrate an IT environment without being detected. To protect PI and other sensitive data, the project's scope should dictate the extent of the test's limitations. 5. Preserving Access and Penetrability Once a penetration tester has successfully penetrated their target, they should aim to increase their access and remain for as long as possible. Again, the objective is to mimic a real-world terrible actor as closely as feasible. In this step, the penetration tester will attempt to expand their permissions, locate user data, and remain inconspicuous as they run their programs deeper into the IT architecture. For instance, a penetration tester may attempt to gain administrator privileges. Again, the objective is to remain unnoticed as long as possible and access the most sensitive data (according to the project scope and goals). 6. Risk Evaluation and Report The last element of a penetration test consists of an evaluation and report. A final report will be generated once the penetration tester has been "found" or the project schedule has been met. The report should include a summary of the testing, details of each step the pen tester took to infiltrate systems and processes, descriptions of the vulnerabilities, and recommendations for security improvements. A competent penetration tester will also be able to assess the worth of the compromised systems, i.e., how much their intrusion will cost financially. A penetration tester employs penetration testing tools to accomplish this. Carrying Out Pen Testing Tools for penetration testing can offer the input required to complete the full assessment of cybersecurity. Using data encryption mechanisms and testing logins and passwords, pen testing tools detect security vulnerabilities. They resemble some tools a professional hacker might use to attempt system penetration. In addition, automated tools can benefit black box and grey box penetration tests. Port scanners, vulnerability scanners, and application scanners are the many categories of penetration testing tools. Remote port scanners collect information and personal data about a target. Scanners look for known vulnerabilities in both network hosts and networks. Finally, application scanners examine web apps for vulnerabilities. While penetration testing is possible, it is not the most efficient method because it is time-consuming, complicated, and requires in-depth security expertise. However, if you wish to utilize a penetration tool, there are several essential aspects to consider while choosing software or a program. When choosing a penetration tool, ensure that it is simple to implement and customize for your specific requirements. The penetration tool should readily scan your system and be able to validate any earlier warning signs. In addition, the tool should be able to identify and rank vulnerabilities according to their severity, allowing you to prioritize what has to be addressed promptly. Finally, a component of automation should verify vulnerabilities on your behalf and generate detailed logs. Penetration Testing Tools Common application vulnerabilities can be identified with the aid of automated technologies. The purpose of pentesting tools is to look for malicious code that could lead to a security breach. By analyzing data encryption techniques and determining hard-coded information such as usernames and passwords, pentesting programs can detect security flaws within a system. Criteria for Choosing the Most Efficient Penetration Tool: It must be simple to deploy, configure, and employ. It should be simple to scan the system. It should categorize vulnerabilities under their severity and the urgency of their repair. It must be capable of automating the vulnerability testing process. It should re-verify the exploits discovered in the past. It should produce comprehensive vulnerability reports and logs. Here is a list of recommended penetration testing tools: Acunetix Acunetix WVS provides security professionals and software engineers with an impressive array of functionality in a simple, straightforward, and highly robust solution. Intruder Intruder is a powerful vulnerability scanner that identifies cybersecurity vulnerabilities in your digital estate, discusses the associated risks, and aids in their remedy before a breach. It is the ideal instrument for automating penetration testing operations. Features: Over 9,000 automated inspections are performed on your complete IT infrastructure. Infrastructure and web-layer validations, including SQL injection and cross-site scripting. Scan your system automatically when new threats are detected. Multiple connectors are available, including AWS, Azure, Google Cloud, API, Jira, and Teams. Intruder provides a free 30-day trial for their Pro package. Astra Pentest Astra Pentest is an enterprise-wide, industry-compatible security testing tool. They have a sophisticated vulnerability scanner and a staff of skilled and highly motivated pen-testers who ensure that every vulnerability is identified and the most effective solution is provided. Features: Visualized dashboard Continuous scanning with CI/CD integration identifies weaknesses in business logic, price manipulation, and privileged escalation. You may scan behind the logged-in page with Astra's login recorder addon. Examine advanced web applications (PWA) vs. single-page applications. Real-time compliance reporting. Zero false positives Penetration Testing Best Practices The following best practices will help you increase the efficiency of penetration testing activities. Planning and Reconnaissance are Crucial Vulnerability scans and a thorough search for security holes should be the first steps in a penetration test. Then, a penetration tester should conduct reconnaissance against the target company, gathering data from accessible resources, and preparing the most efficient attacks, just like a real attacker would. It is wise to take meticulous notes, including any vulnerabilities that were found but not used in the test. Developers may be able to replicate and solve errors in the future as a result. Create Attacker Avatars An ethical hacker should behave and think like an attacker. They should think about cyber attackers' motives, objectives, and capabilities. Understanding hacker behavior requires an understanding of motivation. For instance, a hacker looking to steal sensitive information or a hacktivist looking to cause harm will behave differently than one looking to commit financial fraud. The organization should establish the personas of its most likely attackers, rank them, and focus on the best persona before conducting penetration tests. Suspend Development in the Penetration Testing Environment A known, stable system state is necessary for effective penetration testing. The penetration test will be rendered useless by adding a new patch or software package, modifying a hardware element, or altering the configuration. This is because the update may fix any vulnerabilities that were found. Penetration testing is done because it is not always possible to foresee whether an update will positively or negatively impact security. When systems must be changed during a test because there is no other option, the attacker should be informed, and this information should be included in the penetration test report. Conclusion In conclusion, Penetration Testing is conducted while the application operates as intended. Depending on the application's requirements, a different type of testing procedure is then implemented in the application. An approved hacker identifies the application's weak points in advance, preventing any unethical hacker from gaining access.

Software testing is the process of evaluating a software product to detect errors and failures and ensure its suitability for use. It can be performed manually (where testers use their skill, experience, intuition, and knowledge) or automatically (where the tester’s actions are guided by a test script). The fundamental objective of the test process is to ensure that all specified requirements of a software system have been met by the development process and that no undetected errors remain in the system. However, the overall aim of testing is to provide customer or end-user value by detecting defects as early as possible. Testing occurs in different phases throughout the Software Development Life Cycle (SDLC). Testing may also occur after the completion of each phase or after certain checkpoints within each development phase. The different phases through which a piece of software passes before it is released for use are called the Software Testing Life Cycle (STLC). In this article on STLC, we will discuss the fundamentals of software testing, the phases of the software testing life cycle, methodologies, and their best practices. Let’s dive in! What Is the Software Testing Life Cycle? The STLC is an iterative, cyclical process that has the goal of preventing errors in the software. It includes test analysis, planning, designing, setup, execution, and test closure activities. Due to the complexity of the software, it is impossible to guarantee that a product will be free of errors if only one test is performed. Therefore, multiple tests are performed on every phase of the Software Testing Life Cycle. There are different types of tests that can be implemented alongside each other or separately at any time during the life cycle. Examples include usability testing, regression testing, exploratory testing, and sanity testing – for all of these different types, there are many subcategories. Each category has its own special purpose and will vary depending on the circumstances. The STLC has the following phases, which we will discuss in detail in the later sections: Requirement Analysis Test Planning Test Case Designing and Development Test Environment Setup Test Execution Test Cycle Closure Characteristics of the Software Testing Life Cycle STLC is a step-by-step method for ensuring high-quality software. Improves the consistency and efficiency of the agile testing process. As soon as needs are determined or the Software Requirements Specification (SRS) document is ready, the STLC process should begin. Defines goals and expectations clearly for each project aspect. The tester can analyze and establish the scope of testing and write effective test cases while the software or product is still in the early stages of the STLC. It aids in the reduction of the test cycle time and the provision of higher product quality. Ensures the features are tested and passed before adding the additional features. The Difference Between SDLC and STLC Software Development Life Cycle, or SDLC, is one of the most important phases in the development of any software. During this phase, various steps are taken to develop a product and make it market-ready. Software testing is one of the most critical parts of the SDLC process. It has an entire life cycle known as Software Testing Life Cycle or STLC. So, what’s the difference between SDLC and STLC? SDLC STLC Focuses on developing a product. Focuses on product testing. It helps in developing good quality software. It helps in making the software defects-free. Understanding user needs and creating a product that is beneficial to them. Understanding the products development requirements and ensuring it performs as intended. In SDLC, the business analyst gathers the requirements and creates a Development Plan. In STLC, the QA team analyzes requirements like functional and non-functional documents and creates a System Test Plan. In SDLC, the development team creates high and low-level design plans. In STLC, the test analyst creates the Integration test plan. SDLC is responsible for collecting requirements and creating features. STLC is responsible for creating tests adapted to the collected requirements and verifying that features meet those requirements. Before testing, the SDLC phases are completed. After the SDLC phases are completed, the STLC phases begin. The end goal is to deliver a high-quality product that users can utilize. The ultimate goal is to uncover bugs in the product and submit them to the development team so they can be fixed. Software Testing Life Cycle Phases It’s important to understand the phases of the Software Testing Life Cycle to make better decisions about how to test your software. One critical aspect of the testing lifecycle is determining which phase of testing to perform on your software. The first step in this process is to determine whether you need to perform testing on your product or not. If your product is an app that collects data, it will have less need for testing than if it were a banking website that processes financial transactions. Some products may undergo all phases of testing, while others may be tested only partially. For example, a website that exists purely as a marketing tool might not need to go through any tests other than usability tests. Testing can happen at any time, and each phase should be performed at least once before moving on to the next. Every phase is independent of the rest, so you can perform only one if necessary. A typical Software Testing Life Cycle consists of the following phases; let’s have a detailed understanding of each phase. Requirement Analysis Requirement analysis is the initial phase in the Software Testing Life Cycle. This phase examines functional and non-functional requirements from the testing perspective to identify the testable needs. Customers, solution architects, technical leads, business analysts, and other stakeholders communicate with the quality assurance team and comprehend the clients’ requirements to tailor the tests to the customer’s specifications. Entry Criteria Specification document and application architecture are two documents that must be available. The acceptance criteria and the availability of the above documents must be clearly established. Activities in the Requirement Analysis Phase Identifying and prioritizing the requirements. Brainstorming sessions for the feasibility and requirement analysis. Creating a list of the questions that the client, solution architect, technical lead, business analyst, etc., need to answer. Test Planning With the information gathered in the requirement analysis in the previous phase, the QA team moves a step ahead in the direction of planning the testing process. The most crucial phase of the Software Testing Life Cycle is test planning or test strategy. All of the testing strategies that will be utilized to test the program are defined during this phase. The test lead determines the cost estimates and efforts for the entire project at this phase. Here, a variety of test activities are planned and strategized together with the analysis of resources, which increases the effectiveness of the planning phase and aids in achieving the testing target. Software testing can’t be valued without effective tools, especially when you are performing automation testing. Choosing the right tool for software testing is planned in this phase. There are various tools out in the market for performing software testing. Choosing cloud-based automation testing tools like LambdaTest is the right choice when you want to test at scale. Entry Criteria Documents containing requirements. There should be a report on automation criteria provided. Activities in the Test Planning Phase The objectives and scope are described. Selecting the testing types to be carried out and the unique approach for each. Roles and Responsibilities are determined and assigned. Locating the testing resources and equipment needed for the test. Choosing the right testing tools. Calculating the time and effort needed to complete the testing activities. Risk analysis is being done. Test Case Designing and Development The requirements have been examined, and the QA team has created a test plan in response. It’s time to be creative and shape this test strategy by turning it into test cases. To check and validate each test plan, test cases are devised and developed based on a test strategy and specific specifications. Designing test cases in the STLC is a very important process as it will help determine the defects in the product. It can also be called defect identification or defect analysis. In order to design the test cases, first, we need to have a requirement document that will define the scope of functional and non-functional testing. This requirement document can be prepared by business analysts, and it should also include all possible user scenarios of the software product. Once we have the requirement document, we will go for test case designing. Designing test cases involves two steps: 1. Identification of test cases 2. Analysis of test cases The first step is to identify all the possible test cases which can cover all the user scenarios, and then finally, after analyzing them, we need to remove the test cases which are not fit for execution or the test cases which have low priority or the test cases which may not be able to find out any defect. The QA team begins writing effective test cases when the test design step is completed. Entry Criteria The specifications documents. The feasibility report on automation. Activities in the Test Case Designing and Development Phase Test cases are designed, created, reviewed, and approved. Existing test cases that are pertinent are examined, revised, and approved. If necessary, automation scripts are created, examined, and approved. Test Environment Setup Post designing and developing the test cases, to establish and replicate the ideal conditions and environmental factors to conduct actual testing activities, the software testing process needs an adequate platform and environment that includes the essential and necessary hardware and software. This phase consists of preparing the testing environment. The test environment establishes the parameters under which the software will be evaluated. Because this is a stand-alone activity, it can run concurrently with the test case development process. The test environment differs from one organization to another. In some circumstances, the testing environment is built up by the developer or tester, while in others, the testing environment is set up by the clients based on their needs and requirements. The testing team prepares for smoke testing while the customer or developer prepares the test environment. The purpose of smoke testing is to validate the test environment by determining its readiness and stability. Entry Criteria The test strategy should be readily available. Smoke test cases should be readily available. The results of the tests should be available. Activities in the Test Environment Setup Phase The test data is set up. The necessary hardware and software have been gathered and a test environment checklist has been created. Network configurations and a test server have been set up. The process for managing and maintaining test environments is outlined and explained. The atmosphere is smoke tested to ensure readiness. Test Execution The QA team is now prepared to engage in some practical testing operations as they have the test cases, test data, and the appropriate testing environment. The testing team executes the test cases in this phase based on the test cases and test planning prepared in the preceding phases, namely the test planning and test case development phases. The test cases that are passed are given a score. When a test case fails, a bug tracking system is used to communicate the defect or problem to the development team. These bugs can also be connected to a test case for future reference. In an ideal world, every failed test case would be associated with a defect. After the development team has addressed the bug, the identical test case is rerun to ensure that it is indeed fixed and works as expected. A report is generated that displays the amount of passed, blocked, failed, or not run test cases, among other information. Entry Criteria Testing strategy documents. Examples of test scenarios. Data from the tests. Activities in the Test Execution Phase Following the test plan, test cases are executed. Contrasting the outcomes achieved with those anticipated. Locating and spotting flaws. Recording the flaws and reporting the found bugs. Mapping faults to test cases and updating the traceability matrix for requirements. Retesting after the development team has corrected or eliminated a bug. Testing for regression (if required). Tracking a flaw until it is fixed. Test Cycle Closure The completion of the test execution phase and delivery of the software product marks the beginning of the test closure phase. This is the phase in which the entire cycle is evaluated. Other testing-related characteristics, such as quality attained, test coverage, test metrics, project cost, adherence to deadlines, etc., are taken into account and analyzed in addition to the test results. The team also analyzes the aspects of the Software Testing Life Cycle process that went well and those that may be improved. To determine the severity and issues, the test case report is generated. The test metrics and closure reports are created after the test cycle is completed. Entry Criteria Report on the execution of the test case. Report on a flaw. The execution of the test cases should be completed. Activities in the Test Cycle Closure Phase Review the entire testing procedure. Discussions take place regarding the need to modify the exit criteria, test plan, test cases, etc. Analysis and examination of test results. All test deliverables, including the test plan, test strategy, test cases, and others, are gathered and kept up to date. Test metrics and the test closure report have been created. The severity and priority of the defects are ordered. Methodologies of Software Testing Life Cycle In software testing, there are various methodologies to carry out the software testing processes. There are four types of methodologies: Waterfall Model V Model Spiral Model Agile Model Waterfall Model One of the earliest process models to be introduced was the waterfall Model. It is quite basic and straightforward to use. It functions similarly to a downward-flowing waterfall. Each phase should be finished before the execution of the next phase in this model, ensuring that no phases overlap. There are five phases in the waterfall model, which are completed one after the other. They are: Requirement analysis System design Implementation System testing System deployment System maintenance Before testing begins, all needs are determined in the first step, referred to as the requirement analysis phase. The developers build the projects workflow in the next step, known as the system design phase. The intended work from the system design phase is implemented in the implementation phase. The testing step follows, with each modules functionality being validated against the criteria. The next phase is the deployment phase, followed by the maintenance phase, which is an ongoing process. During this phase, the developers address any issues arising from the softwares use over time. When a problem occurs, the developer patches it and the software returns to testing. This process is repeated until all flaws have been resolved. Advantages of the Waterfall Model There is a review procedure and defined deliverables for each phase. There is no overlapping between the phases because they are completed one at a time. It works effectively for projects with well-defined requirements that do not change over the development process. Disadvantages of the Waterfall Model It does not demonstrate good results for lengthy projects. It carries a great deal of danger and uncertainty. It performs terribly for projects with a high or moderate likelihood of required modifications. For complex, object-oriented tasks, it performs mediocrely. The entire project may be abandoned if the scope is modified along the life cycle. In the last stages of the life cycle, the functional software is produced. V-Model The waterfall model is an out-of-date model with numerous flaws and limitations. As a result, the V-Model was created to overcome those limits. The verification and validation model is another name for the V-Model. It is seen as a development of the waterfall model. The tasks in the V-Model are completed simultaneously. On the left-hand side, it depicts software development operations, while on the right-hand side, it depicts the testing phases in progress. It means that each element of the software development cycle is inextricably linked to the phases of software testing. This model likewise follows the waterfall approach, as there are no stages that overlap, and the next phase begins once the previous phase has been completed. The testing phase must be planned concurrently with the software development phase in this architecture. The verification phase begins after the designing or planning phase, followed by the coding phase, and finally, the validation step. This phase also includes module design, which ensures that all modules are compatible with one another. The coding step begins after the verification phase is completed. The coding is carried out in accordance with the standards and rules. The validation phase follows the coding phase. The software is tested, including unit testing, integration testing, system testing, and acceptance testing, to ensure that it meets the customers needs and expectations and that it is defect-free. Advantages of the V-Model It is simple to comprehend and operate. Its ease of use makes it much more manageable. There is no overlapping of phases. It’s ideal where the needs are clear, such as minor projects. Each phase has its evaluation procedure and set of deliverables. Disadvantages of the V-Model Not recommended for complex, object-oriented programs. Unsuitable for lengthy projects. Not suitable for projects when there is a medium to high likelihood that a requirement may change during the project. Spiral Model The V-Model and the waterfall Model are recommended only for smaller projects where the requirements are specified clearly. Spiral models are suitable for larger projects. The Sequential Linear Development Model and the Iterative Development Process Model are combined in this paradigm. This means it’s similar to the waterfall approach but focuses on risk assessment. In the spiral mode, a particular activity is done in one iteration. This is why it is called spiral. The same procedure is followed for every spiral created to construct the whole software. There are four phases in the spiral model. They are: Identifying objectives Risk analysis Develop and test Review and evaluate The sole variation between the phases of the waterfall and spiral model is the risk analysis. Advantages of the Spiral Model Unlike the previous two models, it enables changes to be accommodated. However, the requirements should be expressed clearly and should not change throughout the process. It enables users to test the system at an early stage. Requirements are captured more precisely. It provides for the division of the development process into smaller segments, allowing for the creation of the riskier parts early, resulting in better and more exact risk management. Disadvantages of the Spiral Model The procedure is very intricate. It is impossible to predict the projects completion date in advance. Low-risk initiatives shouldn’t employ it because it can be costly and unnecessary. There is no end to the spiral iteration. As a result of the several intermediary steps, excessive documentation is required. Agile Model To overcome these challenges, longer iterations of testing and development are used in the agile paradigm throughout the software testing life cycle. It is currently the most popular model. If you are still working on the waterfall methodology, it is high time to move to the agile methodology. Here are some of the points you need to know while moving from waterfall to agile testing. Customers have the ability to make adjustments to the project to improve it and eliminate defects. In other words, any errors discovered during testing can be rectified or amended on the spot without interrupting the testing process. Teams must now automate their test cycles due to the current trend in enterprises toward agile development. This enables them to advertise new features more quickly and gain an advantage. There are seven phases included in the agile methodology. They are: Plan Design Develop Test Deploy Review Launch It is essential to follow the phases one after the other. It’s also critical to remember that to ensure apps are prepared for the real world, they must be tested in real-world user conditions. This also implies that teams must have immediate access to real devices with real operating systems and browsers loaded for testing. Now, keeping up with such an internal device lab requires a lot of money, time, and effort. The best way to avoid cost and effort is to opt for a cloud-based web testing platform. LambdaTest, a cloud-based cross-browser testing platform, is the right fit here. It provides a cloud-based scalable infrastructure and provides an online browser farm of 3000+ browsers, devices, and OS combinations. You can use LambdaTest with the online Selenium Grid’s power to run thousands of parallel tests in a matter of seconds, reducing test execution time and providing faster feedback on code changes. Advantages of the Agile Model The processes are divided into many individual models in the agile model so that developers can work on them separately. It presents a method for software testing and development that is iterative and incremental. It gives the consumer an early peek at the project and allows them to make regular decisions and modifications. When compared to the other models, the agile technique is considered an unstructured model. Between testing sessions, problems, errors, and defects can be corrected. It necessitates less planning, and the project, or the testing process, is completed in short iterations. With plenty of advantages, it is suitable for organizations to stick to the agile methodologies. Best Practices of Software Testing Life Cycle Below are some of the best practices that are followed in the Software Testing Life Cycle. When deciding on the scope of testing, consult with important business users. User feedback is used to identify essential business processes. As they consume most of the users time and resources, it ensures that the test strategy covers testing for those essential business operations. Determine the most common faults or problems that negatively influence the user experience. Testing is planned with a clean user experience for important processes. Testing is planned to ensure that the product meets all user requirements. Conclusion Identifying faults in the last stage of an SDLC is no longer an effective approach. A company must also concentrate on a variety of other daily duties. Spending too much of your valuable time testing and correcting bugs can stifle productivity. After all, it will take longer to produce less output. It’s critical to make efficient use of time and resources to make the testing process go more smoothly. Following a systematic STLC allows you to fix bugs quickly and improves your works quality. Happy testing!

Artificial Intelligence (AI) in software testing shows great promise in ensuring high-quality software without the manual drudgery of endless units and integrated proofing. With AI, delivery times will be reduced from minutes to seconds, and vendors and customers will experience a software renaissance of inexpensive and user-friendly computer applications. Unfortunately, the luxury of inexpensive storage space, blazing fast processing rates, readily available AI training sets, and the internet have converged to turn this promise into overblown hype. Googling "AI in software testing" reveals an assortment of magical solutions promised to potential buyers. Many solutions offer to reduce the manual labor involved in software testing, increase quality, and reduce costs. In addition, vendors promise that their AI solutions will solve software testing problems. The Holy Grail of software testing — the magical thinking goes — is to take human beings, with their mistakes and oversights, out of the software development loop and make the testing cycle shorter, more effective, and less cumbersome. The question is - should that be the main focus, and is it even possible? The Reality Taking humans out of the software development process is far more complex and daunting in the real world. Regardless of using Waterfall, Rapid Application Development, DevOps, Agile, and other methodologies, people remain central to software development since they define the boundaries and the potential of the software they create. In software testing, the "goalposts" are always shifting as business requirements are often unclear and constantly changing. User demands usability change, and even developer expectations for what is possible from the software can shift. The initial standards and methodologies for software testing (including the term quality assurance) come from the world of manufacturing product testing. Within this context, products are well-defined, with testing far more mechanistic compared to software, whose traits are malleable and often changing. Software testing is not applicable to such uniform, robotic methods of assuring quality. In modern software development, many things can't be known by developers. For example, user experience (UX) expectations may have changed since the first iteration of the software. Or there are higher expectations of faster screen load times or speedier scrolling needs, or users no longer want lengthy scrolling down a screen because it is no longer in vogue. Whatever the reason, AI can never on its own anticipate or test for what its creators could not envision, so there can be no truly autonomous AI in software testing. Creating software testing "Terminator" may pique the interest of the media and prospective buyers, but this deployment is a mirage. Instead, software testing autonomy makes more sense within the context of AI working in tandem with humans. AI Stages Software testing AI development essentially has three stages of development maturity: Operational Process Systemic The overwhelming majority of current AI-enabled software testing is at the Operational stage. At its most basic, Operational testing involves creating scripts that mimic the routines human testers perform themselves hundreds of times. The "AI" in this instance is far from intelligent and may help with items like shortening script creation, repeated executions, and storing results. Process AI is a more mature version of Operational AI with testers using Process AI for test generation. Other uses may include test coverage analysis and recommendations, defect root cause analysis and effort estimations, and test environment optimization. Process AI can also facilitate synthetic data creation based on patterns and usages. Process AI can also provide an additional set of "eyes" and resources to offset some of the risks that testers take on when they are setting up the test execution strategy. In actual application, Process AI can help make testing easier after code has been modified. Manual testing often sees testers retesting the entire application, looking out for unintended consequences of a code change. On the other hand, Process AI can recommend a test to a single unit (or limited impact area) instead of a wholesale retest of the entire application. At this level of AI, we find clear advantages in development time and cost. Unfortunately, in Systemic AI's third stage, the future can become a slippery slope of unrequited promises. Systemic AI One of the reasons systemic — or fully autonomous — AI testing is not possible (at least for now) is because of the enormous amounts of training the AI would require. Testers can be confident that Process AI will suggest a single unit test to adequately assure software quality. With Systemic AI, however, testers cannot know with high confidence that the software will meet all requirements. If AI at this level was truly autonomous, it would have to test for all conceivable requirements - even those that have not been imagined by humans. They would need to then review the autonomous AI's assumptions and conclusions. It would take a great deal of time and effort to verify these to provide a high level of confidence that the AI was accurate in its assumptions. Autonomous software testing can never be fully realized because humans wouldn't trust it, which would defeat the purpose of working toward full autonomy in the first place. Training AI Though fully autonomous AI is a myth, AI that supports and extends human efforts at software quality is a worthwhile pursuit. In this context, humans can bolster AI: testers must consistently monitor, correct, and teach the AI with ever-evolving learning sets. The challenge is to train the AI while assigning risks to various bugs within the tested software. This training must be an ongoing effort, in the same way, autonomous car makers train AI to make the distinction between a person crossing a street and a bicycle rider. Testers must train software testing AI with past data to build their confidence in the AI's capabilities. Truly autonomous AI in testing needs to project future conditions — developer-induced and user-induced — which it cannot do based on historical data. Instead, trainers train AI based on data sets according to the trainers' own biases. The biases put limits on the possibilities that AI can explore the same way blinders keep a horse from wandering off an established path. Increasingly biased AI becomes increasingly untrustworthy. Confidence becomes low that the AI is performing as expected. The best the AI can be trained to do is deal with risk probabilities and arrive at risk mitigation strategies ultimately assessed by humans. Risk Mitigation Ultimately, software testing is about managing testers' confidence. They weigh the probable outcomes of initial implementations and changes to code that could cause problems for developers and users alike. Unfortunately, confidence can never be 100% that software testing has fully explored every possibility of an application breaking down. Whether manually performed by humans or autonomously, there is an element of risk in all software testing. Testers must decide the test coverage based on the probability of the code causing problems. They must also use risk analysis to decide what areas to focus on outside the coverage area. Even if AI determines and displays relative probabilities of software failure at any point in the chains of user activity, a human still needs to confirm the calculation. AI offers possibilities for software continuity that are influenced by historical biases. However, humans would still not have a high confidence level in the AI's risk assessment and prescriptions to mitigate risk. AI-enabled software testing tools should be practical and effective to produce realistic results for testers while alleviating the testers' manual labor. The most exciting — and potentially disruptive — deployment of AI in software testing is at the second level of AI development maturity: Process AI. As a Katalon researcher noted, "the biggest practical usage of AI applied for software testing is at that process level, the first stage of autonomous test creation. That would be when I can create automated tests that can be applied by and for me." Autonomous and self-directed AI that replaces all human involvement in the software testing process is hype. It is far more realistic and desirable to expect that AI can extend and supplement human efforts and shorten test times. It's also in the not-too-distant future.

Functional testing is concerned with the functionalities that enable the software system or application to work as per the required functional specifications and business requirements. Accessibility testing is concerned with the web application’s accessibility. It ensures the disabled community can easily access a website or specific application. The UI design and usability are pondered and worked upon in the accessibility testing process. In functional testing, the focus is on ensuring that a given input should provide the desired output. In this article, you will learn the differences between accessibility and functional testing. What Is Accessibility Testing? It is a testing method that uses assistive technologies to make sure that a website or application is fully accessible and can be easily accessed by disabled people. Assistive technologies include a special keyboard, screen magnification, screen reader, and speech recognition software. Accessibility testing should abide by WCAG (Web Content Accessibility Guidelines) standards for optimal testing outcomes. What Is Functional Testing? It is a testing method wherein a software system is validated against the functional specifications/requirements. Each function’s output is checked against the user’s expectations. A predetermined set of specifications are tested against the application’s functionalities. It is a black-box testing technique that is not concerned with the application’s source code. The Strategic Significance of Accessibility Testing Accessibility testing requires as much energy, focus, and attention as other kinds of functional testing. Changes must be made to browser and phone settings to rely on voice assistance, change zoom levels, enlarge fonts, etc. The world of digital media is growing exponentially. Thus, the market for websites and digital applications is embraced by various industries such as banking, education, retail, insurance, etc. Hence, applications should be developed according to the accessibility guidelines, which, in turn, can also prove to be of great help to the disabled community. There are many countries where fully accessible websites and applications have become mandatory. Websites and applications built according to accessibility guidelines can reach a wider audience and thus look forward to expanding their brand. Another essential aspect of accessible websites is that they will have rich text, which can help to improve the SEO ranking of the specific website. The Strategic Significance of Functional Testing This testing ensures that the application’s functionality is working as intended. Potential issues are identified early in the development process and fixed at the earliest. This, in turn, ensures that the software application being built is safe and secure. The number of errors is considerably reduced. Organizations can save substantial costs and time in the long run. The objective is to ensure that the key expected outputs are delivered to the end user. All the client-specific requirements mentioned in the software requirement specifications and business requirement specifications document should be incorporated into the functional testing process. A functional tester focuses on analyzing and working on the application’s individual pieces within the context of the whole application. The functional tester looks into specific items, and then the integration points are identified between those items and other parts of the application so that a strategy can be formulated to inspect those weak points. Types of Accessibility Testing Manual Code Review As per research, approximately 80% of the WCAG 2.0 standards and 100% of the updated WCAG 2.1 standards should be undertaken manually, which means the code should be reviewed manually. Manual testers must have the necessary WCAG experience and technical review knowledge. They should also be able to inspect the CSS, HTML, and JavaScript aspects that conform to WCAG standards. Automated Testing Specific accessibility issues are quickly identified and remediated through the automated testing platform to improve accessibility. User Experience (UX) Review The inspection of larger site design elements is considered in the UX review so the accessibility and usability aspects can be tested accordingly. UX review analyzes the following factors: Logical page layout Visual structure Menu functionality Button size. User Testing Disabled people will test the website and application and then provide feedback on quantifying the accessibility factor. Types of Functional Testing: Unit Testing It is a testing method where the smallest components of the code, known as “units,” are tested individually. A unit can be an object, method, function, etc. These tests are really small and thus can be written and executed quickly. These tests are designed in such a way that only a single section of code is covered for verifying its functionality. Smoke Testing The most crucial parts of the application are verified using this testing method. Smoke testing makes sure that the application is functional at the basic level. If it’s not functional, then the application cannot be moved to other levels of testing. Sanity Testing The basic functionality is verified without going into the finer details of the application code. A ‘sanity check’ ensures that the new code performs as expected. Integration Testing It is a testing method that determines whether two or more modules that have been integrated can work as expected. The objective is to analyze and evaluate the module’s behavior when they are integrated with other modules. Regression Testing It ensures that the changes introduced to the code do not alter the existing functionalities of the application. The objective is to ensure that the existing functionalities are not altered, despite making changes and updates to the code or introducing a new feature. User Acceptance Testing It is a testing method where an end-user will test the application or product in a real-time environment. User feedback plays a key role, as the feedback will help the team further enhance the product’s quality. UI/UX Testing It is also known as “visual testing,” wherein the application’s GUI (Graphical User Interface) is thoroughly evaluated. The performance of the UI components, such as text fields, buttons, menus, etc., is verified to ensure that the user experience is up to the mark. Pros and Cons of Accessibility Testing Pros Testing can be conducted on various devices. Specific areas in an application that requires extra attention are pointed out. Time and effort are saved to a considerable extent. Cons Some techniques and coding errors can result in non-compliance and cannot be reported. A good amount of configuration and tuning is required to minimize false positives. Accessibility testing cannot be eliminated in its entirety. Pros and Cons of Functional Testing Pros It ensures that an application’s functionality is working as per the required expectations. The safety and security of the application are adequately met. The product quality is enhanced. The system is tested under different scenarios and conditions. Testing plans can be revised, and progress can be tracked accordingly. Cons It is a time-consuming process as a lot of technical details need to be worked on continuously. It cannot be relied upon entirely, as only the core functionalities are tested thoroughly. It is a tedious process, which, in turn, leads to slow test times and some bugs being missed.

The yearly increase in iOS device sales has set the bar high for the assured success of iOS. However, when it comes to testing these devices, purchasing devices with various HW specs and iOS devices isn't viable for SMEs and startups. Additionally, there are better testing solutions than manual testing due to scalability and low-efficiency concerns. Although iOS is still a more closed operating system than Android, you may use various free and open-source technologies to build effective automated tests. It makes iOS app testing activities simpler and more efficient for developers and testers using a cloud-based testing solution. Here are some automated testing frameworks with code examples that you can use to test your iOS applications. Appium One of the most popular open-source solutions, Appium helps users manage hybrid, mobile, or native apps for Android, iOS, and Windows. It enables developers and testers to build automated tests for mobile applications, enabling them to produce high-quality software more quickly and at lower risk. Appium Benefits Appium is free-to-use and open-source. It supports all WebDriver-compatible languages like Java, Objective-C, and JavaScript. Its developers created it using the same JSON wire protocol as Selenium, making the transition easy for QA testers and mobile developers. Appium tests native, mobile web, and hybrid applications and is compatible with iOS and Android operating systems. It has the support of a sizable and active community that offers users ongoing assistance and troubleshooting. For unit testing, pick a supporting framework like XCTest or XCUITest. Its cross-platform compatibility allows it to reuse test scenarios across mobile and online channels. It is the benchmark for iOS WebDriver development. Appium Disadvantages Adds to the learning curve by requiring users to comprehend the Appium architecture and the principles of native apps/ selectors. It depends on a series of open-source parts that you must install separately in a version that supports the others. Appium Sample Code for WebDriver driver.findElement(By.id("com.example.app:id/radio0")).click(); driver.findElement(By.id("com.example.app:id/radio1")).click(); driver.findElement(By.id("com.example.app:id/radio2")).click(); driver.findElement(By.id("com.example.app:id/editText1")).click(); driver.findElement(By.id("com.example.app:id/editText1")).sendKeys("Simple Test"); driver.findElement(By.name("Answer")).click(); Calabash Another excellent cross-platform framework that is compatible with Android and iOS apps is Calabash. Calabash test written in Cucumber is one of the framework's main distinctions from other frameworks: this means that while the test is basic and easy to read, even for non-technical individuals, an automation system can still execute the tests because we write it like a specification. Calabash Code Sample Feature: Answer the Question feature Scenario: As a valid user I want to answer app question I wait for text "What is the best way to test application on hundred devices?" Then I press Radio button 0 Then I press Radio button 1 Then I press Radio button 2 Then I enter text "Simple Test" into field with id "editText1" Then I press view with id "Button1" Earl Grey Earl Grey is an open-source iOS UI automation framework and Google's response to XCUITest for testing iOS apps. Only iOS devices can use Earl Grey, and developers must write tests in Swift or Objective-C. Earl Grey's primary advantage is that it extends Espresso's synchronization capabilities to iOS app automation testing, ensuring that the automation is not attempting to act while the app is in use. EarlGrey Advantages Easy to add, either directly or through CacaoPods, to an iOS project A versatile framework with effective internal component synchronization features The complete framework is open source. Combined with XCode EarlGrey Sample Code // Objective-C - (void)testInvokeCustomSelectorOnElement { [[EarlGrey selectElementWithMatcher:grey_accessibilityID(@"id_of_element")] performAction:[GREYActionBlock actionWithName:@"Invoke clearStateForTest selector" performBlock:^(id element, NSError *__strong *errorOrNil) { [element doSomething]; return YES; // Return YES for success, NO for failure. } ]]; } XCUITest On iOS devices like iPads and iPhones, XCUITest is a test automation framework for UI testing mobile apps and online applications. It's a piece of Apple's testing infrastructure. XCUITest offers a framework that enables programmatic identification and interaction with UI components from other testing tools. By 2022, the only UI interaction library for iOS supported is XCUITest, which replaced the outdated UIAutomator technology. XCUITest Advantages You can use Swift or Objective-C to write both your application and test code, and both can be modified entirely within XCode and stored in the same repository. Because XCUITest and iOS work so well together, tests might run more quickly than with competing frameworks. By creating test code while observing user interactions with a linked Simulator or Real Device, XCode's "Record" feature enables testing. You can then modify the recorded test code to produce a trustworthy, repeatable test, saving time during test creation. Testers can use XCUITest to locate elements by the element's title, label, value, or placeholder value. For testing purposes only, XCUIElements can also have a specific "accessibility identifier" that makes finding elements quick and simple. XCUITest Drawbacks Every computer your team uses to run XCUITest, including tester computers and CI/CD setups, must have XCode installed. It would be best to run the tests using the XCUITest runner; you cannot run the XCUITest code independently of the XCUITest framework. Swift and object-C are the only available programming languages. XCode Sample Code - (void) testAdditionPerformance { [self measureBlock:^{ // set the initial state [calcViewController press:[calcView viewWithTag: 6]]; // 6 // iterate for 100000 cycles of adding 2 for (int i=0; i<100000; i++) { [calcViewController press:[calcView viewWithTag:13]]; // + [calcViewController press:[calcView viewWithTag: 2]]; // 2 [calcViewController press:[calcView viewWithTag:12]]; // = } }]; } Conclusion Trying to set up your testing capabilities is a challenge. Moreover, iOS device testing requires expertise. Test automation platforms can help test iOS devices. These platforms let you connect to SIM-enabled iOS devices worldwide. Through such platforms, you can get actionable insights that can help you improve your iOS app.