Wie können Sie einen Fehler in Ihrem Code effektiv aufspüren? (2024)

Working at big techs here is I learnt to identify problem, Light the Way: Never skip logging! Add detailed logs of key states and variables to illuminate the bug's path.Track the Clues: Quantify your logs with metrics in tools like AWS CloudWatch. Identify anomalies that expose the bug's hiding spot.Query Logs: Backend Beacons: For backend systems, analyze query logs. These request logs reveal the bug's entry point and its journey through the code.Error Echoes: Error logs are crucial, but dig deeper. Backtrack through them like following breadcrumbs, each error leading closer to the root cause.

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Identify the problem is most important step ,try to achieve it fast using debugging tools. After fixing the bug it is important that review,refactoring is properly done. Just make sure you don't open a new bug after solving one

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Writing the unit test cases helped me to find the bugs easily. Try to cover 100%-line coverage to find the bug. In Big Projects it is very difficult to find the bugs, to make it easy for debugging, ensure you have the logs covered in all the corner scenarios. Watch out where the log didn't get executed. This way you can identify the problem easily.

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I follow the approach of commenting some parts of the code to debug faster and make some assumptions in the variables. At this line, predict the possible values and mock them, if your bug disappears, see why you are not getting the correct value. Assume you have 50 lines of the code in your function, Bug is present in the 27 line of the code, Make sure you have gone all the 20 lines of code and see if you are getting the correct values. If you are confident, remove the debug points from the above 20 lines. Go for the Next lines of execution.

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Once you have a clear understanding of the problem, narrow down the potential causes by examining relevant code sections or modules. Utilize techniques like binary search or divide and conquer to isolate the problematic code.

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Write a failing test and THEN fix the bug. If you cannot write a failing test, you don't udnerstand the bug and SHOULD NOT be fixing it. Every bug should have a test. You can later refactor some of these into your acceptance tests. After you fix the bug, regress the code by running the full test suite. Circular bugs are the worst (fixing A causes B, fixing B causes A) and an indication you don't have enough tests written.

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Upon discovering a bug, proceed with the necessary fix. If your solution requires a logic change, ensure a clear understanding of its scope and the areas it influences. - This becomes especially critical when modifying an existing API; make sure to communicate your changes effectively to the API users. - Moreover, take a retrospective look at the areas not addressed in your project to mitigate the risk of future bugs.

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After pinpointing the root cause, implement a solution that addresses the issue directly. Consider potential side effects and test your fix thoroughly to ensure it resolves the problem without introducing new bugs.

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Reflect on the bug and the code surrounding it. Evaluate if there are any patterns or practices that contributed to the issue. Take the opportunity to refactor code for clarity, maintainability, and to prevent similar bugs in the future.

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After fixing a bug, reviewing and refactoring your code is essential. This step involves scrutinizing your code for errors, inefficiencies, or suboptimal practices that could cause future issues. Leveraging code reviews, peer feedback, or self-assessment helps elevate code quality and readability. Implement refactoring techniques like method extraction, variable renaming, or expression simplification to enhance modularity and maintainability. Such practices not only address immediate concerns but also improve the overall health of your codebase, making it more robust and easier to manage over time.

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Document the bug, its cause, and the steps taken to fix it. Share this information with your team or relevant stakeholders to foster knowledge sharing and prevent others from encountering the same issue.

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Debugging extends beyond solving technical issues; it includes documenting and communicating your findings. Utilize version control and issue trackers to log the bug's history and resolution status. Incorporating comments in your code helps maintain a record for future reference. To effectively share your solution with others, employ documentation generators, create diagrams, or write summaries. These tools facilitate clear explanation of the problem and the implemented fix, aiding both current team members and future developers. Effective documentation and communication ensure that your solution is understood and can be built upon, enhancing the collective knowledge and efficiency of your team.

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Reflect on the debugging process to identify areas for personal or team improvement. Consider if there are any tools, techniques, or approaches that could streamline future debugging efforts.

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Indeed, debugging serves as a valuable learning and improvement opportunity. Enhance programming skills by delving into the root cause of the bug, comprehending the logic behind the fix, and understanding the broader implications of your code. Use debugging as a tool for preventing future bugs by recognizing and sidestepping common mistakes, adhering to best practices and standards, and adopting a proactive testing mindset. This continuous learning and improvement loop ensures ongoing development, contributing to more resilient and efficient coding practices over time.

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Debugging is also give the opportunity to learn and improving your knowledge in depth in any problems by passing different test cases with different bugs. We can test different cases with different data structure or technique that increases our logical thinking and helps other problems .

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The key is testing in terms of the behavior and having that test build for each class invovled in the function. It also requires naming pieces of your software consistently and with terms that relate to the business function and behavior.I built a system to create NACHA files for credit card processing. OO with each object named after the line in the file with children that helped build the line as a collection in the line. First test, it failed. Finding the named line and the column, I flipped the logic and sent out a corrected file before the meeting ended. Naming matters.Testing is more difficult, but centering on behavior, and building tests for that behavior on each layer makes it easy to find the issues.

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