PMD VS SonarQube

PMD and Checkstyle are static analysis tools that check your code on each project build. Gradle allows to apply them easily.

The generated classes should be put into .gitignore. Otherwise, if you have Checkstyle, PMD, or SonarQube in your project, then generated classes can violate some rules. Besides, if you don't put them into .gitignore, then each pull request might become huge due to the fact that even a slightest fix can lead to lots of changes in the generated classes.

- PMD Static Code Analysis tool: https://pmd.github.io/

PMD, Spotbugs, Nullaway: Java linting/static analysis (https://pmd.github.io, https://spotbugs.github.io, https://github.com/uber/NullAway)

PMD, and checkstyle as well.

Nearly every programming language has a static analyzer of its own. For example, golang has gofmt, which is baked into the standard tooling, while Ruby has Rubocop, a community-led project. Even compiled languages like C have their own static analyzer through astyle. However, it can be difficult (and tedious) to run several analyzers across polyglot projects. Fortunately, that’s where a project like PMD can be of assistance. PMD is a static analyzer that allows you to define a standard set of rules that can be applied over multiple languages.

Open up the config/ruleset.xml file, and you’ll find an XML document that lists several rules. These rules map to the issues which PMD will report on. Believe it or not, there are hundreds of Apex rules, and you can find the full set at the PMD repo. You have complete control over which rules to enable. Typically, you’d determine which ones are important by agreeing with your teammates on the ones that matter most. After all, their code will be statically analyzed, too!

While at it you could also point them to static code analyzers such as error_prone, spotbugs and pmd (use all 3 at once - they complement each other in detecting different issues).

For PMD specifically, we use the PMD command line tool (Github) and wire it together with some bash scripting. Most pipelines will allow you to write bash as needed. The SFDX scanner command didn't exist when we implemented this, you might be able to use that instead.

This is the definition of cohesion and there are many great tools to calculate cohesion metrics (depending on the programming language e.g Java). Cohesion metrics belong to a bigger set of metrics called OOP metrics (or ck metrics). Check out the following links: https://github.com/mauricioaniche/ck https://github.com/cqfn/jpeek https://github.com/rodhilton/jasome https://github.com/pmd/pmd

SonarQube https://www.sonarqube.org/

There are commercial tools that can be integrated into a CI pipeline and/or a developer's IDE. I've used SonarQube before, but there are others.

having a code review and analysis tool in CI/CD pipeline can help developers to keep their code clean. some examples of these tools are sonarqube and embold.

Sonarqube Source Code Repository

The generated classes should be put into .gitignore. Otherwise, if you have Checkstyle, PMD, or SonarQube in your project, then generated classes can violate some rules. Besides, if you don't put them into .gitignore, then each pull request might become huge due to the fact that even a slightest fix can lead to lots of changes in the generated classes.

SonarQube allows all developers to write cleaner and safer code. It supports lots of programming languages for scanning (Java, Kotlin, Go, JavaScript). It also supports running unit testing for code coverage. It can be easily integrated with Jenkins and Azure DevOps. Checkmarx, Veracode, and Klocwork also provide similar functionality but these are paid tools.

As for some of our tech stack outside of Next.js for those curious, we use Sass to define CSS and its globals, Jenkins for our CI/CD pipeline, and Sentry for error tracking, all of which have been great to work with so far. Within our testing suite, we utilize Sonarqube, Lighthouse, aXe Core, WebPageTest, @next/bundle-analyzer, and run tests written with Cypress.

I found code reviews to also be tedious but in a different way. We have a large number of tools to review code well, and my company also makes sure to automate checks for code standards, smells and best practices (see sonarqube). The expectation on me as a code reviewer was to criticize to improve the structure and design of our code. Along the way, I was also meant to teach other engineers things.

Ring any bell ? Don't be shy, I know that you are thinking of Sonarqube !