DevOps Your Skill: Static Code Quality Analysis

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DevOps Your Skill: Static Code Quality Analysis

In this article, we discuss how to add static code quality analysis to your Alexa Skill pipeline and its importance in the day-to-day Alexa Skills development.

· DevOps Zone ·
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Without a doubt, one of the aspects a developer should pay more attention to is trying to always generate understandable, maintainable, and clear code — in short, to generate clean code.

During the development of code (modules, libraries), it is important to integrate objective tools that measure the status of the code and provide the information to know its quality and thus be able to detect and prevent problems: duplicate functions, excessively complex methods, code low quality, non-standard coding style.

These checks are automated in the continuous integration system (CircleCI) and are executed in each new version of the software.


Here you have the technologies used in this project

  1. ASK CLI - Install and configure ASK CLI.
  2. CircleCI Account - Sign up here.
  3. Node.js v10.x.
  4. Visual Studio Code.


ESLint is a tool for identifying and reporting on patterns found in ECMAScript/JavaScript code, with the goal of making code more consistent and avoiding bugs. We can find two types of rules. Some aimed at guaranteeing the quality of our code, such as the detection of declared variables or functions that are not being used in our code, and others aimed at guaranteeing that the format of our code maintains certain homogeneity, such as the use of semicolons at the end of our instructions, spacing, etc.

ESLint allows us to automatically fix almost all the rules.


You can install ESLint using npm. --save-dev is used to save the package for development purposes. Example: unit tests, minification.



npm install eslint --save-dev


Once we have ESLint installed, we have to configure it. With ESLint, you can define your own rules, and in addition, you can also use a set of rules defined by a lot of big companies such as Airbnb, Facebook, or Google. These sets of rules are used by most of the npm packages.

In our case, we are going to use the StrongLoop set of rules from IBM. This package can be installed with the following command:


Now, it is time to configure this set of rules. First, we have to create the file .eslintrc.json in lambda/cutom folder:


As you can see, we extend from StrongLoop rules, and we add some extra configurations:

  1. We set ecmaVersion to 2019 in order to check the code with the modern format of JavaScript standard
  2. In the envwe set to true the following properties:
    1. es6 like ecmaVersion, this is because of the JavaScript version.
    2. node because we are in a Node.js project.
    3. mocha due to the use of this library in our unit tests.
  3. Finally, I have changed the max-len rule setting it to 120 characters instead of 80 defined by strongloop set of rules.

The last step is to define the .eslintignore located in the same folder in order to specify the files that we do not want to check their style.

It is something like .gitignore file:

Properties files


Once we have everything configured, we have to set up the reports we are going to use to check our code quality.

The first report we need to set up is the JUnit report. This report will generate a .xml file as output that CircleCI is going to use to print the lint results:

CirclCI output

We are going to move one step forward. We want to know a little bit more about our ESLint analysis in every pipeline execution.

This is why we are going to add the eslint-detailed-reporter npm package to generate a beautiful HTML report with more information rather than the above explained:


This is how this report looks like:

ESLint Report

All these reports will be stored in lambda/custom/reports/eslint/ folder.


Now it is time to integrate it into our package.json to use it in our pipeline with npm run commands!

So, in this file, we are going to add the following commands in the script JSON node:

  1. lint: this command will execute the ESLint check and generates the JUnit report:
    1. eslint . --format junit --output-file reports/eslint/eslint.xml
  2. lint-fix: this will automatically fic most of the code style errors_
    1. eslint --fix .
  3. lint-html: this command will execute the HTML report using the npm package explained above:
    1. eslint . -f node_modules/eslint-detailed-reporter/lib/detailed.js -o reports/eslint/report.html

Pipeline Job

Everything is fully installed, configured, and integrated. Let's add it to our pipeline!

This job will execute the following tasks:

  1. Restore the code that we have downloaded in the previous step in /home/node/project folder
  2. Run npm run lint to execute the ESLint checker.
  3. Run npm run lint-html to execute the ESLint HTML report. It will be executed always, regardless of if the job succeeds or fails.
  4. Store the JUnit report as CircleCi test artifacts.
  5. Store the HTML report as an artifact of this job.
  6. Persist again the code that we will reuse in the next job



The quality of static analysis tools depends on various factors. The main ones are usually efficiency, clarity of your error reports, and a low percentage of false negatives. An advantage of static analysis tools is that they are usually easy to use. many are integrated directly into the IDE and only require the execution of only one simple command as we have seen with ESLint.

That's all folks!

You can find the code in my GitHub.

I hope it will be useful! If you have any doubts or questions, do not hesitate to contact me or put a comment below.

Happy coding!

alexa, alexa skill, alexa skill development, alexa skills, alexa skills developer, alexa skills development, circleci, devops, eslint, javascript

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