1- What is test coverage, and why is it important?
2- Should you do 100% test coverage? What should you consider while determining the right level of test coverage?
3- How does static analysis testing differ from unit testing?
4- What are some common tools used for static analysis testing in JavaScript?
5- How can developers enforce static analysis rules across their team projects?
6- What is CI/CD and why are automated testing and CI/CD important?
7- How can Husky and GitHub Actions help enforce CI/CD practices?
Room 1:
- Ahmed Isam
- Ahmad Qarany Farhan
- Didam Goran
- Mohammed Nazm
- Sarah Mustafa
- Sajad Ismael
- Shvan Abdulhakeem
Test coverage refers to the percentage of code covered by unit tests. It's important because it helps ensure all code is tested and reduces the likelihood of regressions being introduced. Tests provide documentation of how code is expected to behave and allow refactoring safely.
100% coverage isn't always feasible or necessary. Consider business needs, risk levels of each code section, cost of additional testing, and whether all code lends itself to being tested. Coverage should be maximized for critical and complex code, while less risky code may not need as much testing.
Static analysis checks code for bugs and errors without running the code, unlike unit tests which execute code snippets. It catches logic errors like unused variables and missing cases. Unit tests validate behavior through execution. Static analysis is faster and catches problems early in the development cycle.
For JavaScript, common static analysis tools include ESLint, JSHint, and Prettier for linting/formatting code. TypeScript also adds type checking capabilities. These help enforce code quality and standards.
Static analysis rules can be defined in configuration files checked into version control. Tools like ESLint can then be run during CI/CD to check code commits comply with standards before merging. This ensures consistency across the codebase.
CI/CD automates the build, test and deployment process. It helps catch errors quickly, improves code quality through testing, and facilitates faster, more reliable software releases. Automated testing is a key part of CI/CD as it prevents regressions and ensures code quality.
Husky and GitHub Actions help implement CI/CD best practices. Husky runs scripts like linting and testing on commit/push. GitHub Actions can run tests and deploy code automatically on code changes through pull requests and merges. Together they ensure code quality and prevent bugs from being introduced or released to production.