Here's how you can design software that is easy to test and debug.

A modular design approach is most fundamental to successfully building a complex software system. It does not have to be all microservices, though. A "majestic monolith" (DHH) is fine, and may even be a better approach for many teams. Inside this monolith, however, you must have a modular design with components that talk to each other via well-defined interfaces and that can be tested independently. Designing such interfaces requires experience and discipline.

Effective tests allow teams to move fast with confidence in the era of continuous delivery. Unit tests sits on the base of the test pyramid, number of unit tests usually outnumbers any other type of tests. Modular design makes it easy to write unit tests and validate be behavior in isolation.

I know few simple tips: 1) Break your code into smaller, manageable modules. 2) Keep your code organized and easy to follow. 3) Reduce dependencies between different parts of your code. 4) Implement robust error handling mechanisms. 5) Use logging to track the flow of your program and identify issues.

A modular design approach entails dividing your software into smaller, independent modules for separate testing. This simplifies complexity and facilitates fault isolation. Each module should fulfill a single responsibility and communicate with other system parts via clearly defined interfaces. This allows you to write unit tests for each module, validating its behavior in isolation and streamlining the testing process while ensuring thoroughness.

It's important to mention approaches like Domain Driven Design or Hexagonal Architecture. Using those you can separate layers of your codebase that bring some peace of mind - it's easier to write code, make changes, read it for someone unfamiliar with it, and write proper tests.

Decoupling your application's logic from its user interface and data storage components is crucial. This separation enables you to test the business logic independently, without being tied to specific user interfaces or databases. Utilize design patterns such as Model-View-Controller (MVC) or similar architectural patterns to achieve this separation effectively. When components are decoupled, you can utilize mock objects or stubs during testing to simulate the behavior of dependencies, simplifying the debugging process.

While creating a modular design, I use (among other things of course) two aspects: ‘Need to know aspect’, according to which modules have reason to exist only if there is something unique, they ‘need to know’. For example, making an async Http request producing Json can be seen as a unique know-how, which other parts of a program do not need to have, but can benefit from. ‘Early decision aspect’, according to which modules have reason to exist only if they are making a unique decision and reducing the decision burden on dependent modules. For example, a compliance-related decision can be made at the earliest stages of creating a trade. But these design techniques are complicated and should be a subject for a special article.

The only way to really do it for the long term in a sustainable way is to build a scripting interface (python) which is tied to all the functionality/options which can be recorded as you conduct your testing and can be replayed easily. We have a very slim QA team for 10+ million lines of code and the only way in which it is possible is with this philosophy.

Automated testing is indispensable in modern software design. Establish a suite of automated tests comprising unit tests for individual components and integration tests for component interactions. Employ testing frameworks compatible with your programming language and tools capable of running tests automatically post-build or during continuous integration. This safeguards against new changes breaking existing functionality and facilitates early bug detection.

Effective error handling is paramount for developing testable and debuggable software. Establish clear and consistent error handling policies throughout your codebase. Utilize exceptions to signal error occurrences and ensure they are caught and managed appropriately. Additionally, logging errors with ample context is essential for diagnosing issues in production environments. This comprehensive approach to error handling enhances the reliability and maintainability of your software.

Consider forcing a minimal amount of test coverage. For example, make a pull request not mergeable if unit test coverage is less thant 85%.

Implement CI/CD pipelines to automate the build, integration, testing, and deployment of software changes. CI/CD pipelines enable frequent and reliable delivery of software updates, reduce the risk of integration issues, and ensure the stability and reliability of the software design.

Proper error handling is not only about throwing exceptions to indicate an error and logging with the appriopriate detail. Another important factor is *not* "breaking the stack trace". I've seen many developers who use try/catch blocks in every method they write and if they can't do anything useful with the exception, they throw it again from the catch block. This hides the original source of the error and makes it very difficult to troubleshoot. Only handle exceptions in your code when you can do something useful with them, such as adding additional context or logging them. Otherwise, let the platform do its job.

Define and adhere to a consistent error handling strategy across the entire codebase. This includes establishing conventions for error representation, handling, and reporting to ensure uniformity and predictability in error handling behavior.

Exception handling is one of important aspect of system. It help team identifing defect as environmental or application. Keeping centerlised exception always be best practice. Keep stack stace in exception handling

Readable code is necessary in maintaining application in long run. Code should be self explanatory. Write brief comment for complex logic that help other to enhance functionality and fix defect.

Readable code is important from maintenance point of view as code is more important for humans in maintaining than computers which will do what humans say. Following may be helpful tips 1. use proper names for variables, verbs for functions according to your domain. 2. Functions should be short and concise and should be testable. 3. Use domain driven design technique, Behavior driven design techniques. 4. Use wherever possible OOAD, and interface techniques, reusable patterns, etc.

When a method is complex your mind wasn't clear on how to model the phenomenon at hand. It may help to, when discussing the phenomenon, be aware of your using of nouns and verbes.

The simplest way to design your software, so it's easy to test tand debug is by using the approach of 🥁 test-first. Test-first development will ensure your system is decoupled and it can be tested. Well, this approach enforces the system to show these qualities.

Some developers tend to code only considering the happy path, which means, for example, that if the argument provided is not what is expected, the code will break. A good approach would be to encourage a culture of creating tests with a more complete coverage strategy, which tests the code with the most unexpected arguments, and ensures that the code works anyway. Ideally a dedicated QA team would be able to catch those cases.

To design a software that is easy to use and debug: 1. Focus on user experience with intuitive interfaces and clear documentation. 2. Employ modular design and abstraction to isolate issues and reduce complexity. 3. Implement robust logging, error handling, and testing practices. 4. Provide debugging tools and techniques for developers to diagnose and resolve issues efficiently.

Limit number of Direct class references, try to always use Interfaces and avoid public static methods when possible. Use IOC and automated injection, this will allow you to easily modify your implementations without rewriting your tests