Bridging the Gap Between Quality Engineering and Product Management
Bridging the Gap Between Quality Engineering and Product Management
Evan Wiley introduced tools that bridge the gap between the product specified by the product managers and the nuts and bolts of testing.
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How do you bridge the gap between quality engineering and product management?
In October 2019, Evan Wiley from Capital One presented on this topic for an Applitools webinar. Evan introduced a number of cool tools that bridge the gap between the product specified by the product managers and the nuts and bolts of testing. Interested? Read on.
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Evan Wiley spent six years in Quality Engineering at Capital One before moving into product management. In his engineering time, Evan discovered that product managers and quality engineers share complementary views on their products. Product managers envision behaviors that quality engineers execute in their tests.
Evan experienced this relationship directly when he was invited by product managers to attend “empathy interviews.” In these interviews, team members speak with customers to understand the customer’s environment, needs, fears, and expectations. In attending these interviews, Evan heard the first-hand lives of customers who were using the results of his work. These interviews both informed his work in quality engineering and later fueled his move to product management
What Is Quality Engineering?
Evan described the work of quality engineering as finding bugs within products early and often. Noting that the job varies from organization to organization and company to company, Evan described the responsibilities including:
- Manual testing – ensuring that the product can be exercised and behaves as expected
- Test automation – creating automated tests that can be run to assure behavioral coverage without manual intervention
- Production testing – verifying behavior with a production-ready product.
- Test case design – ensuring that tests cover both positive cases, or normal function, as well as negative cases, or handling problematic inputs, internal inconsistencies, and other errors.
- Test execution – running tests and reporting results
- Penetration testing – running tests and reporting results for tests based on known threat vectors
- Accessibility testing – ensuring that customers with known visual and other disabilities can navigate and use the product successfully
Evan noted that the nature of this work changes as products, product delivery platforms, and customer environments evolve. And, things change constantly.
What Is Product Management?
Evan next dove into describing the role of product management. Frankly, describing product management can take a two-day course, and even then not cover what everyone thinks product management might do at their company. I know this as I remain a poorly-hidden closet product manager.
Evan does not try to describe product management comprehensively. Instead, he focuses on how empathy interviews drive product managers to make product decisions. Primarily, Evan says, empathy interviews help product managers become the “voice of the customer.”
One part of empathy interviews guides testing. For example, does your test environment match the customer’s environment? Do your test conditions match the customer’s test conditions?
A larger set of questions helps product managers understand problems their customers try to solve, how to prioritize solutions to these problems, which of these problems need to be higher on the near-term backlog versus further back, and how customers might respond to different marketing messages.
And, when product managers take their products to the field, they can validate a customer’s reaction with expectations from empathy interviews to help make their empathy interviews even more effective. The initial empathy interview forms the basis for product management key performance indicators.
Ultimately, the needs of product managers and quality engineers diverge significantly. But involving quality engineering in customer empathy interviews helps the overlap succeed.
Quality Over Quantity
Evan spends a bit of time discussing how Capital One prioritizes quality over quantity. Evan points out that the company makes this choice, and that the decision permeates the company culture. At Capital One, that goal permeates all engineering – not just quality engineering.
Evan explains with an example from another company.
“If there’s a quality engineer at Facebook, they might have a lot of test cases, and in some cases, they can stand in for the end-user with the knowledge of being a user. So, if they’re testing, say, logout from Facebook, they might think, ‘I can make that simpler for an end-user because I’d want it to be.’ And this insight empowers the quality engineers to work directly with the developers tweak a behavior for an end-user.”
To this end, Evan sees that the whole of engineering contributes to quality over quantity culture. Hiring processes, skill selection, and testing approaches involve transparency that allows for a breadth of experience and diversity of perspectives on the team.
And, this mix of backgrounds leads to cross-training product managers with quality engineers. Bringing both groups together inside Capital One leads, in Evan’s perspective, to better outcomes for customers.
Evan gave the example of testing a set of features across multiple browsers alongside product managers. He was able to show the product managers where the different browsers handled certain functions differently as a way to build the culture of quality at Capital One.
Next, Evan demonstrated the use of Gherkin Scenarios for writing stories that describe the behavior of a product. If you don’t know about Gherkin, it’s basic statements are:
So, for example, Evan talks about the Google home page. He imagines the product manager writes something like this:
These scenarios have several useful properties.
First, they help the product manager describe the detailed behavior a user will experience before any software gets written. Product managers can validate these stories with prospective customers and identify any issues that might impact the behavior of the product.
Second, developers get an understanding of the intended user experience and outcome to plan their coding activity.
Third, engineers can use their experience to determine scenarios that might not have been described and what should be the intended behavior in those situations. And, engineers can ask relevant questions involving both designs as well as behavior.
A Gherkin Example
Imagine some questions that come from the scenario listed above. Here are a few:
- How much time should the user experience between clicking the “Google Search” button and getting a response back?
- What happens when the user has 600ms of latency between the browser and server?
- Since the scenario specifies that the test uses valid text for a Google search, define valid text.
- What about the scenario when the user enters not valid text?
These questions lead to more scenarios, which lead to more complete product specifications, which lead to more complete products. The larger number of scenarios also leads to more complete testing. Quality engineers read these scenarios and begin planning their acceptance tests based on these different scenarios and conditions.
Much of the engineering-product management conversation ends up as quality engineering talking with product management about scenarios – tightening the connection between product management and quality engineering.
Evan did not talk about it, but a tool like Cucumber reads in Gherkin scenarios to help build test automation.
Visual Validation Baselines
From there, Evan moved on to talk about visual validation. For visual validation, Evan talked about Applitools – a tool he uses at Capital One.
First, Evan spoke about the idea of user acceptance testing. When you run through the scenarios with product managers, you will end up with the screens that were described. You want to capture the screen images and go through them with product managers to make sure they meet the needs of the customers as understood by the product management team.
Part of the testing involves capturing images, and that means following your Gherkin scenarios to make sure you capture all the right steps. Evan showed some examples based on a Google page and describing how those test steps in the Gherkin scenarios became captured visual images. Evan pointed out that these visual images begin to define how the application should behave – a baseline for the application.
As you go through the different pages, you can complete the baseline acceptance tests. Once you have a saved good baseline, you know the state of an accepted page going forward.
If you find a behavior you don’t like, you can highlight the behavior and share it with the developers.
You can find problems during visual testing that do not appear in development. For instance, someone realizes you need to test against some smaller viewport sizes. Or, you test a mobile app, but not the mobile browser version.
So, you build your library of baseline images for each test condition. You make sure to include behaviors on target browsers, operating systems, and viewport sizes in your Gherkin scenarios. As it turns out, with Applitools, your collection of completed baselines makes your life much easier going forward.
Visual Validation Checkpoints
Next, Evan dove into using Applitools for subsequent tests.
Once you develop your test cases and run them through Applitools, you have baselines. As you continue to develop your product, you continue to run tests through Applitools. Each test you run and capture in Applitools can be compared with your earlier tests. A run with no differences shows as a pass. A run with differences shows up as “unresolved.”
Evan showed how to deal with an unresolved difference. He inspected one difference, saw it was due to an expected change, and accepted the difference by clicking the “thumbs-up” button in the UI. In this case, the checkpoint automatically becomes the new baseline image. He inspected another difference. In this case, the difference wasn’t one he wanted. He clicked the “thumbs-down” button in the UI. He showed how this information becomes a “failed” test, and how the information of the can get routed back to developers.
Unlike other visual testing tools you have used, Applitools uses computer vision to identify visual differences. The Visual AI engine can ignore rendering changes at the pixel level that do not result in user-identifiable visible differences. And, there are other capabilities for maintaining applications, such as handling changes that displace the rest of the content on pages or managing identical changes that occur on multiple pages.
Quality Over Velocity
Evan went back to discuss the company culture about prioritizing quality. Capital One developed an engineering culture over time to focus on quality. Any decision to emphasize delivery over quality must be documented and validated. Release decisions at Capital One end up being team decisions, as the whole team is responsible for both the content and quality of a release. So, the entire decision to deliver quality products brings product management, product development, and quality engineering teams together with a common purpose.
Evan noted that, in his experience, other companies approach these problems in different ways. The culture at Capital One makes this kind of prioritization possible. Cross-training makes this delivery possible because cross-training makes all team members aware of priorities, approaches, and tools used to deliver quality. The result, says Evan, is a high-performing team and consistency of meeting customer expectations.
Questions About Quality Engineering
A questioner asked Evan if Quality Engineering at Capital One had sole responsibility for quality. Evan said no. Evan pointed out that he spoke from his perspective, and while Quality Engineering came up with the approach to validate product quality, the whole team – product management, development, and quality engineer – participated in the testing. The approach helped the team deliver a higher quality product.
Another questioner asked about the benefit of getting customer knowledge directly to Quality Engineering. That’s valuable, Evan said. For example, during an empathy interview, a customer raises the question of a specific problem they have when trying to execute something specific. During the interviewer, the interviewer dives deeper into this issue. The result is a more complete understanding of the customer use case, the expected behavior, and the actual behavior observed. This results in both better test cases as well as future enhancements.
Questions About Visual Testing and Tools
A questioner asked if Gherkin scenarios made sense in all situations. Not always, said Evan. Gherkin scenarios make great sense when fitting into behavior for development to create and quality engineering to test. Evan thought about cases, such as technical debt cases, for which the intended behavior may not be user behavior.
Another questioner asked about the value of visual testing to Capital One. Evan talked about finding ways to exercise a behavior, capture the results, and share the results with product people. Test pass/fail results could not capture the user experience, but visual test results do so as part of the visual testing solution. One example Evan gave was for a web app that had an unexpected break on a mobile browser, due to the different browser behavior on a different operating system.
Without visual testing, the error condition would likely not have been caught in-house. If Capital One were only using manual tests, the condition might not have been covered if the specific device version was not included in the test conditions. With the automated visual tests, they found the problem, saved the image, and used that as a new Gherkin scenario in the next release.
Questions About Product Management and Quality Engineering
Next, Evan was asked about how to integrate product management and quality engineering more closely. Evan said he wasn’t sure how to do this in the general case. At Capital One, the need for engineers and product managers to collaborate on issue grooming, with the ability to capture the visual behavior during a test run, improved the ability of the engineers and product managers to agree on issues that needed to be addressed, in what priority, and for what purpose.
Finally, Evan was asked how to get Product Management to involve engineering more closely. Evan focused on empathy interviews as ways to align engineering and product management, and Gherkin scenarios as tools to bring a common language for both development and test requirements. Evan also talked about his own transition from Quality Engineer to Product Manager – and how he went from being tool-and-outcome focused to customer-and-strategy focused.
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