Debugging is an essential skill for any developer, but it can also be frustrating, time-consuming, and error-prone. How do you learn from debugging mistakes or challenges, and improve your code quality and productivity? In this article, we will share some tips and best practices for debugging effectively and efficiently.
Debugging is not just a technical task, but also a mental one. You need to adopt a debugging mindset, which means being curious, persistent, and logical. Curiosity helps you ask the right questions and explore different possibilities. Persistence helps you overcome obstacles and keep trying until you find the solution. Logic helps you reason about the problem and the code, and avoid assumptions and biases.
While Debugging, keep in mind the following :- 1) Always log/print and read the errors properly. If you don't understand them, search on the net or check the documentation. 2) If something worked earlier & doesn't now, try to figure out what was modified(Version Control/git to the rescue). At times package/system updates can cause things to break as well. 3) Mismatch in data types or variable names is problematic. Misplaced indents or brackets cause problems too. 4) Understand the logical flow of the module/program to figure out what triggers the bug. 5) Document the bug and keep a track of how it was resolved for future reference.
Identifying frequent patterns, thoroughly analysing problems, and aggressively looking for solutions through peer cooperation and documentation are all part of learning from debugging mistakes. Understanding the underlying problems and coming up with workable solutions are aided by experimenting and trying various strategies. While constant iteration and improvement help one's debugging abilities and coding habits to become more refined over time, documentation of the debugging process and lessons gained guarantees that similar errors may be averted in the future.
Debugging is a journey of investigation. Finding clues, coming with theories for issues and identifying suspects are key skills. Without evidence, debugging would be impossible. Logs, traces, events are your clues. Using those, identify potential causes and further create evidence to support your theory or throw it away. Your job is come up with evidence to support or reject a theory. When time is the essence, you should be able to divide and conquer. Remember every tool is available to you, don't forget to use them.
Be curious, persistent, and logical. Curiosity helps you explore options, persistence keeps you going, and logic helps you analyze the problem without assumptions.
1. Read log errors carefully: Analysing logs in detail is key to understanding the root cause. Also, performing functionality analysis before debugging ensures you're targeting the right part of the code. 2. Add breakpoints strategically: Instead of adding breakpoints to consecutive lines or methods, focus on key areas to efficiently identify where things go wrong. 3. Use logs/prints for clarity: Logging or printing relevant information helps trace the flow and spot issues more clearly. 4. Once the error is identified, explore the best solution: After finding the error or exception, evaluate different approaches and choose the most effective one for a permanent fix.
Debugging tools and techniques can vary according to the language, framework, and platform you are working with. Common debugging tools include debuggers, which allow you to inspect and manipulate code as it runs, logs that record events and messages generated during execution, tests that check the correctness and functionality of code, and code reviews that review code for errors, bugs, style, performance, and readability. Debugging tools can help you trace the flow of your code, identify anomalies or exceptions, prevent bugs, refactor code, and follow best practices.
Get familiar with key debugging tools like debuggers, logging tools, and version control systems. Make a checklist of tools you need for each project to help you find and fix issues more easily.
In order to fix a bug, you must first reproduce and isolate it. This involves finding a way to reliably trigger the bug and narrowing down the code causing it. To do this, you should use a consistent and controlled environment, with the same settings, data, inputs, and outputs as when the bug occurred. Additionally, minimize external factors that may interfere or vary. It is also important to use a minimal and relevant example by removing any unnecessary or unrelated code, data, or features that are not involved in the bug. Lastly, use a systematic and methodical approach to test your code such as dividing it into smaller parts, checking the inputs and outputs of each part, and using binary search or elimination to locate the source of the bug.
Apply the following steps: 1) Understand that bugs are at times specific to a certain configuration and at others the result of some inconsistency in a framework. 2) Try to get as much information as you could about the system on which the bug occurred and the steps that could be taken to reproduce it. 3) Try to reproduce it on a Virtual/Physical Device with identical or similar configurations. 4) Identify what might be causing it, check the modules involved and its code base. Understand the logical flow of the program to pinpoint the issue. 5) If none of the above works try to get more information about the system on which it occurred and check for similar bugs reported w.r.t the framework being used in the application.
When you find a bug, write down the steps to reproduce it. Use a controlled environment to limit variables. This practice helps you identify the issue faster and creates a reference for future bugs.
Once you have reproduced and isolated the bug, it is necessary to understand and fix it. To do this, you can use a hypothesis and experiment method by forming a plausible explanation of why the bug occurs based on observations and knowledge, then testing it with experiments. Alternatively, you can use a compare and contrast method by comparing your code with a working or expected version to identify differences or discrepancies that may be causing the bug. Lastly, you can use a trial and error method by trying different solutions or alternatives and evaluating their effects on the bug.
Once you've isolated the bug, break your code into smaller parts and analyze each section. Use print statements or logs to track what’s happening in your code. This will help you understand the problem and test possible fixes.
I usually approach debugging by first isolating the issue and then forming a hypothesis about its cause. From there, I test different solutions, either by comparing with a working version or through trial and error. Each bug is an opportunity to refine my problem-solving skills and deepen my understanding of the code.
After fixing a bug, it is important to reflect on what you have learned from the debugging process and apply it to future projects. This includes documenting and communicating the bug, analyzing and preventing similar bugs, and reviewing and refactoring your code. Doing so can help you and others avoid or resolve similar bugs in the future, as well as improve your documentation, communication, design, coding, review, and refactoring skills.
After fixing a bug, write a short report explaining what caused it and how you solved it. Share this with your team to help everyone learn. Set aside time for regular code reviews to improve overall code quality.
Without evidence, debugging would be impossible. Logs, traces, events are your clues. Using those, identify potential causes and further create evidence to support your theory or throw it away. Your job is come up with evidence to support or reject a theory. When time is the essence, you should be able to divide and conquer. Remember every tool is available to you, don't forget to use them.
Some tips for python scripts: Improper indentation in python within codeblocks containing multiple if-else statements and even in general can result in logical issues even though the interpreter might not always report them. Never ever use module, datatype or function names as is for a variable, it won't usually throw errors but something gets broken especially if you store scripts in the same directory as your interpreter.