How can you effectively test your code before a deadline?

Requirements Grasp: - Understand project requirements for testing. Prioritized Scenarios:- - Break down functionality into key test scenarios. Efficient Automation: - Automate critical tests for efficiency. Code Coverage Analysis: - Analyze for thorough testing. Integration & Edge Testing: - Verify integration, handle edge cases. Performance Check: - Assess code performance. Regression Check: - Ensure changes won't impact existing functionalities. Team Communication: - Communicate testing plans for coverage. Time Management: - Allocate time wisely, including buffers. Continuous Testing: - Implement for ongoing validation.

Oui, il est possible de tester efficacement votre code avant une échéance en suivant quelques bonnes pratiques : 1. Planification des tests : Identifiez les fonctionnalités critiques à tester en priorité et élaborez un plan de test en conséquence. 2. Tests unitaires : écrivez des tests unitaires pour chaque composant de votre code afin de vérifier son bon fonctionnement de manière isolée. 3. Tests d'intégration : Assurez-vous que les différents modules ou composants interagissent correctement en réalisant des tests d'intégration. 4. Tests de régression : Réexécutez les tests existants pour vous assurer que les modifications récentes n'ont pas introduit de régressions.

If possible, automate your tests to speed up the testing process. Use testing frameworks and tools to automate unit tests, integration tests, and regression tests, allowing you to run them quickly and repeatedly. Before deadline, it is crucial to defining goals, identifying test cases, and prioritizing them based on importance. Then, monitor test results, analyze metrics, and iterate on your testing process to improve effectiveness.

Automated tests are the need of the hour. I prefer adding tons of automated unit tests, plenty of integration tests and some end-to-end tests for the applications I work on. This ensures that we are shipping code with high confidence. The testing pyramid is an incredible visual representation of how automated testing is done in software. This was introduced by Mike Cohn in his book, Succeeding with Agile. The base of the pyramid comprises of unit tests, and the very top of the pyramid are end?to?end tests with integration tests left in the middle. As we go up in the pyramid, the tests are slower and more expensive. Tools like Jest, Enzyme are good for automated unit tests, and I personally like Cypress and Playwright for E2E tests.

Rapid Feedback: - Provides quick feedback on code changes, enabling swift issue resolution. Coverage Improvement: - Broadens test coverage, including edge cases and various input scenarios. Resource Optimization: - Optimizes resource use by freeing up human testers for complex scenarios. Efficiency Boost: - Automation speeds up critical test processes, saving time in code validation. Regression Testing Efficiency: - Swift and accurate execution of regression tests to prevent unintended impacts. Consistency: - Automated tests ensure consistent and reliable results, eliminating manual variability. Reliability Enhancement: - Contributes to a more reliable final product by maintaining a consistent testing approach.

It's important to note that some sort of manual check/test is still required even with automated tests. Automated tests are there primarily to make sure the new changes are not breaking existing functionality.

Consistency and Standards: - Enforces coding standards for improved code quality. Best Practices Adherence: - Ensures compliance with best practices and coding guidelines. Collaborative Learning: - Fosters a collaborative learning environment within the team. Knowledge Sharing: - Promotes shared understanding among team members about the code. Error Detection: - Identifies and corrects errors early in the development process.Risk Mitigation: - Reduces the risk of bugs and enhances overall software reliability. Efficiency Improvement: - Catches issues early, saving time and effort in later debugging stages.

Ensuring any production deployments are done through pull requests are very helpful as an additional line of check, even when you are the one approving your own code.

Performance Benchmarking: - Assesses the performance of the code under different conditions, ensuring optimal functionality. Error Discovery: - Uncovers environment-specific errors that might not be apparent in a single testing environment. Real-world Simulation: - Mimicking various user environments provides a more realistic simulation of usage conditions. Compatibility Assurance: - Ensures compatibility across a range of platforms and devices, enhancing user experience. Security Validation: - Testing in different environments helps uncover potential security vulnerabilities across setups. Environment Variability: - Testing in diverse environments identifies issues related to different operating systems, browsers, and configurations.

Quality Improvement: - Use bug reports as valuable feedback to continuously improve code quality. Issue Tracking: - Systematically track and log identified bugs using a dedicated issue tracking system. Prioritization: - Prioritize reported bugs based on severity and impact, addressing critical issues first. Documentation: - Thoroughly document each bug, including steps to reproduce and expected versus actual behavior. Continuous Monitoring: - Regularly monitor the bug tracking system to stay proactive in resolving issues and preventing regression. Clear Communication: - Maintain clear communication within the team regarding bug status, resolutions, and any necessary follow-up actions.

You should continue to run tests even after the deadline by the way… Even if the produced software is not changed too much after that (which is a bad signal, because it means it’s not used enough), you can program jobs that run your pipelines weekly or so, preventing your code to rot, due to obsolete dependencies for example.

In startup world writing tests at the beginning should not be the priority, however when product market fit is achieved it's worth incrementally adding tests to the most critical parts of the software.