What are effective strategies for debugging unfamiliar code?

Most support personal don't have knowledge of original code. Having an incident/interruption are the situation people get to code and often unfamiliar. Best way to understand and debug/fix an issue is to understand the business logic the code is implementing. If you are good on business logic mapping the code and debug is a breeze.

Understanding the context of unfamiliar code is an iterative process that may require a combination of exploring documentation, reviewing comments, exploring requirements and specifications (if there are any), analyzing dependencies, investigating version control history, running the code, tracing the main execution path, identifying key data structures and variables, try to connect with the original developer for guidance, use debugging tools and analyze test cases, seek related documentation or community engagement and taking detailed notes to organize your understanding. During all these processes, one should stay patient, and persistent, and should not hesitate to seek help or clarification from others including StackOverflow or others.

I have learned the following effective strategies for debugging unfamiliar code: Understand what the code is supposed to do. Use the debugger to step through the code line by line. Read the documentation to understand the code's design. Log key variables and operations to track down the bug. Ask for help from a more experienced developer if needed.

Code, in and of itself, is nothing but a series of symbols. Understanding the business context and requirements is fundamental to the solution. The most perfect code ever shoes nothing if it doesn’t deliver to at least one requirement.

Don't discount asking the people. Yes, code should be able to speak for itself with its structure, naming conventions and use of patterns. There may even be documents. None of these information sources compare to asking someone who has experience with the codebase. Another developer will be able to distill the code's history and purposes as well as highlight known pitfalls. Plus it is always a good story!

This i agree with- tied to the problem. Even if we are talking about a fundamental issue with architecture - we need to look at the business problem we are trying to solve. It is acceptable to make architectural mistakes if we meet business needs.

Reproducing a problem reliably is a crucial step toward understanding and fixing it. The more accurately you can reproduce the problem, the easier it becomes to identify the root cause and implement a solution. To effectively reproduce and debug code problems, we should create a controlled environment, understand issue triggers, document, automate where possible, test different inputs and conditions, and collaborate for accurate issue verification and resolution.

Reproducing the problem is a fundamental step in the debugging process, and it's crucial for gaining insights into the issue at hand. By using the same environment, data, and steps that triggered the problem, you can observe the issue firsthand, which often provides valuable information. It allows you to identify the symptoms, understand the frequency and severity of the problem, and pinpoint the specific area of code that may be responsible. This methodical approach not only helps in confirming the issue but also serves as a starting point for debugging and testing potential solutions. Remember that accurate and reproducible testing scenarios are essential for effective debugging and troubleshooting.

For rare or difficult issues, you may need to go to the source. Even though production data is not usually available to a developer, there is always a time for an exception to the rule. If you cannot reproduce a bug using test data, ask to get a copy of the real, production data. This may highlight a previously unknown edge case.

If possible try to simplify what it takes to reproduce the bug, especially if submitting to a 3rd party. Reproducing the bug is crucial to debugging and verifying that a fix works.

While I kind of get the idea of getting a production copy of data may seem easy, with elevated concern on data security and compliance, I think a different approach may be suitable on regulated environment.

Sometimes using a debugger to attach to a running code can be difficult due to networking or security rules, or possibly the containerization strategy. When this happens, hive off the troublesome code into a simpler runtime, i.e. a console application. This will allow you to examine the algorithm without having to deal with the server architecture.

Great comments from all the enthusiasts. In general this is a most common problem where tribal knowledge or tacit knowledge is lost in transition. This is not only a tech problem but also a problem how engineering management is done and complexity varies based on if this is a vendor transition or hostile take over or attrition. A systematic engineering approach from system overview, HLD and LLD helps. There are tools which help with reverse engineering as well on legacy code. Documentation and well commented code helps as well. Team topologies also plays an important role. If you are enterprise, consider platform engineering aspects.

Using Breakpoints and Debuggers works but I believe, that sometimes adding some code to log the data or exception handling helps more to explore/understand it's state. i.e. if the available has the data or is null.

Application-level message logging can be very useful when debugging distributed or multi-threaded applications. Setting severity level to DEBUG or TRACE to allow filtering is also a good idea.

If you cannot find the stack trace, first enable logging. Secondly, enable logging of unknown errors. Thirdly, look for code which is swallowing the real exception and thus hiding the stack trace from view. Alter this code to either disable it, if possible, or add a log message for the full exception at each such handler. Be aware that changing error handling behaviour permanently could have side effects, resulting in further bugs.

A stack trace in unfamiliar code is helpful for pinpointing and understanding the issue's origin, code flow, and variable values, facilitating efficient debugging and problem resolution.

I start learning a codebase by reading it's unit tests, if no unit tests exist for a part, I try writing them to figure out what the author wanted to acheive by looking at how other parts of the code use this part. Many a times when I debug an unfamilar codebase, I look at the variable values in debugger and then create unit tests to remember the state of the class being debugged. Also many a times It is not easy to add unit tests which prompts me to refactor the code, these initial refactorings are done carefully just to make unit testing possible: e.g. add new constructors to allow a class to achieve a certain state. Make private functions accessible to the unit tests to assert their outcome. So test and refactor is my main tools.

When refactoring unfamiliar code, start by understanding it thoroughly, identify problem areas, create tests, and adhere to coding standards. Break down complex logic, use descriptive names, and modularize the code. Make gradual changes, use version control, and seek feedback. Document your process, measure the impact of changes, and iterate over time to improve code quality and maintainability.

With each bug fixed, it is a great practice to add an automated unit test which verifies the new, correct behaviour. This way, if the bug re-occurs, the test should catch it very quickly and prevent it from reaching production. I would argue that creating missing unit tests should always precede any refactoring of the codebase.

Unfamiliar code comes with the territory in the world of collaborative development. Understand the inputs/expected outputs for the code modules Start with small pieces. Try executing the small pieces in debug mode (either through debugger or with Debug ON) Add your own debug statements if required. Execute the code snippets and analyze the output to get familiarity with the expected functionality. As you gain familiarity, solve some simple bugs and then move to complex situations

To attain optimal results, setting clear goals is imperative. 1. Initiate by comprehensively reviewing the code to identify all dependencies. 2. Employ a proficient Integrated Development Environment (IDE), such as Visual Studio or VS Code. Utilize features like breakpoints, conditional breakpoints, or quick watch to gain insight into the data flow and execution. 3. Employ output mechanisms, such as printing to the console or triggering alerts, to facilitate pinpointing the root cause. 4. If logging mechanisms are enabled, meticulously examine the logs to uncover and diagnose the issue. Above all, maintain patience throughout the debugging process. Debugging is an art form that grows sharper with experience.

Look at the version control history. This will tell you where the last changes were made. Walk back through the last few changes. This should take your directly to the problem area.