What are the most effective ways to test and debug server-side code?

Effective server-side code testing and debugging: Unit Testing: Test individual code components. Integration Testing: Verify interactions between components. Automated Testing: Use testing frameworks and tools. Logging: Implement detailed logging for error tracing. Code Reviews: Collaborate with peers for code scrutiny. Error Handling: Implement robust error-handling mechanisms. Load Testing: Assess system performance under load. Profiling: Identify performance bottlenecks. Debugging Tools: Utilize debugging tools and IDEs. Test Environments: Set up separate testing environments.

Use unit and integration testing. Implement comprehensive logging. Prioritize error handling. Conduct code reviews. Utilize profiling tools. Leverage language-specific testing frameworks and debugging tools. Code reviews are most underrated, they with extensive review many issue can be remove before code goes to deployment.

Unit testing, integration testing, regression testing are key to ensuring that the software meets the business requirements. Having a test plan and ofcourse orienting the business or users to the UAT environment is valid.

1. Yes, I agree with right tools, But making sure that whole team is using only one set of tools. - Now a days most of the IDE's support all technologies and each team member may prefer different IDE's - Update all IDE related settings(plugins, extensions etc.) in a file and update in the git repo and all team members should use same settings file 2. Integrate static analysers and linters

Learn from your mistakes But don't be afraid to make 'em. Read every manual on your language or platform. Keep them right by your side. After using em like a dictionary read em like a book. Every sentence from cover to cover. For small to medium sized businesses. County to State 10k to 50k user sessions per day Edit your code live on the server. MAKE INCREMENTAL BACKUPS! Start with one variable! Make pipes off of Redhat Bind Bash httpds.conf and SENDMAIL IF your IP or %UserID Display NewCode else show Old Routine Wrap every ifNull isNil onError SHOW YOU ERROR.MSG.DETAILS ELSE Show a Friendly contact name or number AND write their errorMsg.CPUtickTime in an errorMsgDirectory. Automate Everything. Eat sleep & breathe your code!

1. Refactor the code whenever possible 2. One best way to refactor the code is when fixing the defecting or modifying small piece of code. - Writing tests for small piece of code is simpler than writing for whole feature - This will gradually help to refactor whole feature

I agree that one of most important aspect is write testable code, but unfortunately not always you will have this option specially when working on running/legacy system. This will let you with other options like unit test using mocking and integration test.

In my experience, identifying clear requirements is the hardest part of testing. Focus on defining user acceptance, optimizing developer ergonomics, and understanding the natural flow of communication within your organization. Not every company can afford a single business analyst or architect, much less whole teams of either, so identify who is best-positioned to solicit requirements in your organization, and who is best suited to nail down those requirements into *some* kind of specification. If you can do that, the questions of how to structure unit vs integration vs E2E tests will all fall away, because much of that is picking the most ergonomic tool to satisfy requirements. For example, sometimes E2E testing alone is *good enough*.

Tools can only get you so far. They can warn you of CVE-vulnerable code, but they cannot flag bad architecture (which may also mean hard to test architecture). That said, there are a few techniques that can ultimately make your code better. As far as I'm concerned, for now, human interactions are the best way to keep code good (which incorporates clean, performant, testable and most importantly, the right balance between these). For me, pair programming, shipping small chunks of easy-to-review code and continuously seeking feedback from people is the single best tool for making code better. Which, again, means testable.

The "testable code" is also a great controversy. One could say it's a great way for juniors like developers start to create a new feature, others could argue trying to cover all the possible units of code is a waste of time. I believe it's a balance. Testing the core fundamentals of a system is something necessary, and there are standards to follow such as TDD. Although I'd not say they should not necessarly strictly followed.

- Everyone agrees on writing testable code, but in reality, most of the time tests(at least unit tests) are skipped - To avoid this, plan for unit tests in the sprint plan - Use code coverage to make sure unit tests are covered for most of the code

Resharper has been hugely beneficial in pushing me to develop robust automated testing for ASP.NET apps. Its real-time feedback helps enforce good testing hygiene. For unit testing, Resharper automatically runs NUnit tests and reminds me to increase coverage. It also refactors tests for readability. On integration testing, it highlights untested workflows between components. Resharper helps generate tests spanning ASP.NET layers to catch integration bugs

Automated testing is tough because it's a high value task that's invisible to stakeholders, has a benefit that only really pays off in the medium/long term, and doesn't deliver new features to users. These considerations all weigh in when deciding what/where tests should be written. There are constraints on how much time and effort is acceptable to maintain buy-in from all involved. If these constraints are affecting a project, the primary focus should be on functional tests. If nothing else, a server side application should have tests that run at the API level that ensure that each endpoint can validate, authenticate, and properly respond to requests. The ease of use and high value is a great first step from 'not tested' to 'tested'.

Many people miss this part. If you can't write unit test cases at least write Integration tests. A good set of test cases helps a lot when we fix a bug in it or update the logic and add a new feature to it. Test cases work like documentation also. A new team member joins the team or someone who is not familiar with that part of the code these automation test cases help them a lot in working on that code.

Test the things that matter. Are you reloading the application you're building to walk through a complicated user-flow step-by-step? Write a test. Does customer support *keep* bothering you on your lunch break to report the *same* broken feature? Write a test. Is it a fancy UI feature that won't disrupt the user if it breaks? Don't write a test...at least not until you've tested everything else, learned everything else useful relevant to the project, and find yourself with sufficient slack. Also think about automated testing from a higher level: how well-tested are your dependencies? Is there an off-the-shelf validation library that's well-maintained and well-tested? Use it instead of giving yourself more tests to write.

The most effective approach is to establish a logging system for debugging in a production environment. Log user activities with timestamps as well as errors, ensuring that you can trace the precise source of an issue. When designing a logging system from scratch, make sure to categorize logs using specific keys. Additionally, create a new log for each day and segregate logs based on the entities within your system to expedite the troubleshooting process

In my current job, we have built an entire activity logs system. The activity logs include user actions, inputs, and the backend functions called to respond to the request. So, how do we use it for debugging? We first identify the activity where the bug is occurring. Next, we check the input format. We take the inputs from step 2 and pass them to the backend function. We then simulate the activity and observe the data propagation until we receive a response. Finally, once we get something out of scope, this is when the bug reveals itself.

It's important to keep in mind that we don't need to "reinvent the wheel". There are tons of logging tools such as Elastic Stack that provide us real time code analysis, performance check, observability and vulnerability issues and so much more. And also, every IDE usually have great debbugging tools, we should just make good use of it.

Tools like IntelliJ, slf4j, Zipkin and Sleuth provide a great help for Java( Spring ) developer. Specially when you use advance log analysis tool like NewRelic, AppDynamic or OpenTelemetry

Remote debug techniques vary according to each condition and situation. Tools like ELK are indispensable for platform visibility. My team and I are trying to replicate the environment where errors occurred. Having dockerised micro-service architecture is also a big opportunity to catch & solve issues on the fly since all developers can easily reproduce issues on their locals by using proxy connections.

I believe fundamentally, you can start with unit tests and ensure there is adequate code coverage. Next will be integration tests to verify how the solution works with other services. Load test is another kind of test you can use to check how your solution performs under immense load. And as much as possible, automate.

When I hire an electrician I expect them to not just get my power restored but I expect them to do it professionally. As developers we must strive to write testable software and we must include necessary time when giving user story estimates. The most value in my opinion comes from testing the seams of our software, these entry points such as API endpoints are the contracts we make with our users. This is difficult to achieve in a repeatable and fast way on legacy systems where business logic spread across application and database, but there must be a gradual strategy to migrate to a lesser/weaker coupled future version of the codebase. Fast feedback is best as part of CICD.If it gets to customers its too late.#IncrementallyGetThere

Remember that server-side infrastructure can reference multiple APIs with different availability and response structure, and multiple databases in different states of consistency. Dummy data is your friend, even if it's just a simple JSON file that you type up by hand. If you want to simplify things, help whoever delivers requirements/specifications to do so in a JSON file with example use cases. If you can only get them to put it in a bulleted list, that's a start. Now you don't need multiple requirement and specification documents if they aren't actually helpful: just unify everyone's communication and get people as high up as possible in your organization to start thinking and communicating in terms of use cases that can drive tests.

Remember random data is not very good for testing, I would rather recommend a random data generator with always a specific `seed` for every run to have the same data. There's a dark side of testing, if the test is overly complex and not properly documented or even with a lurking bug there, is very hard in the future to spot the error, that's why is recommended tests to as small as possibly. If you write a unit test +300 LoC you're probably doing it wrong.

Beyond choosing the right tools and align their settings between team members, writing testable code, writing automated tests and having logs and monitoring in place, I found that the quality of code is improved by two other things: 1 - adoption of tools for continuous integration, in order to have build and deploy pipelines on which all the stakeholders agree upon and to allow developers a controlled access to test and staging environments, reducing the time-to-release and allowing QA teams to test latest versions of software on staging environments. 2 - Adoption of tools to measure software quality and discover antipatterns, possible bugs, security issues, third party libraries vulnerabilities early hence mantaining overall code quality.