Best Practices for Code Refactoring

I'm a Software Engineer at AWS, and here are 18 lessons I learned about refactoring code over the last 7 years in 60 seconds. It took me a lot of mistakes to learn these, so you don't have to: 1/ Never assume how code behaves → verify it with tests before changing anything 2/ Refactor in small, reversible steps → big rewrites break things. 3/ Don't change too much at once → reduce the blast radius 4/ Use AI as a refactoring partner → set guardrails, verify with tests, and iterate in small steps 5/ Test before refactors → they protect behaviour, not implementations. 6/ Keep it simple (KISS) → most complexity is accidental 7/ Fix design problems, not symptoms → good architecture prevents bugs 8/ Keep your code DRY → duplication multiplies risk 9/ Performance matters → refactoring isn't just structure, it's behaviour at scale 10/ Legacy code isn't scary → changing it blindly is 11/ Know your goal before refactoring → clarity beats activity 12/ Readable code beats clever code → readable code is easy to maintain in production 13/ Favour composition over inheritance → inheritance adds more complexity 14/ Patterns aren't always your friend → context matters more than theory 15/ Code is for humans → future readers are part of your system 16/ Refactoring is a habit → it's how systems stay healthy over time and avoid "broken windows" 17/ Messy code is a liability → technical debt compounds quietly. 18/ Refactor the code you touch most → optimise for where teams spend time. P.S. What else would you add? --- 🔖 Save this for the next time you're about to "just clean it up" ➕ Follow Abdirahman Jama for practical software engineering tips. #softwareengineering

You know that feeling when you open a class just to add one tiny business rule, and you're staring at a 500-line monster of chained if-else statements? It's a nightmare to test. You can't easily see the second-order effects. And honestly, you're usually just praying you don't break someone else's logic while adding your own. This is incredibly typical in enterprise apps, but we don't have to live with it. Instead of stuffing everything into one massive service, try refactoring it using the Pipeline Pattern. Here is the playbook: 1. Create a Context: Build something like an EligibilityContext to track the state, warnings, and outright rejections. 2. Extract the Rules: Pull those nested if-else blocks out into their own isolated classes that implement a shared interface (like IEligibilityRule). 3. Build the Pipeline: Run those rules sequentially and wire everything up nicely with Dependency Injection. The payoff? Every single rule can now be tested in total isolation. Even better, your architecture finally respects the Open-Closed Principle. you can add or remove rules at will without touching the core pipeline. I just put together a full video walking through exactly how to refactor a messy, real-world Loan Eligibility Service into a clean pipeline in .NET. Check out the full step-by-step refactoring here: https://lnkd.in/dABvRdEP

Don’t break your code during refactoring - there’s a better way. One of my go-to refactoring techniques is Parallel Change. It’s the same concept used in road construction: instead of blocking an entire street until the work is done, you build a detour to keep traffic flowing. Similarly, with Parallel Change, your code continues to function while changes are being implemented. If you’re new to this technique, start small. Practice with simple examples or katas to understand how it works. As you gain confidence, apply it to your day-to-day work - it’s a great way to develop the habit of keeping your code functional throughout the process. When dealing with modernization or legacy projects, this method proves its value even more. It eliminates the headache of fixing broken, non-compiling spaghetti code, allowing you to commit anytime and pause your work without worry. Mastering Parallel Change can make refactoring smoother, safer, and far less stressful. Give it a try - you’ll never want to go back to dealing with broken code.

🚨 When transformation logic is spread all over the repository, it becomes a nightmare to modify, debug, and test. This scattered approach leads to duplicated code, inconsistencies, and a significant increase in maintenance time. Developers waste precious hours searching for where transformations occur, leading to frustration and decreased productivity. 🔮 Imagine having a single place to check for each column's transformation logic—everything is colocated and organized. This setup makes it quick to debug, simple to modify, and easy to maintain. No more digging through multiple files or functions; you know exactly where to go to understand or change how data is transformed. 🔧 The solution is to create one function per column and write extensive tests for each function. 👇 1. One Function Per Column: By encapsulating all transformation logic for a specific column into a single function, you achieve modularity and clarity. Each function becomes the authoritative source for how a column is transformed, making it easy to locate and update logic without unintended side effects elsewhere in the codebase. 2. Extensive Tests for Each Function: Writing thorough tests ensures that each transformation works as intended and continues to do so as the code evolves. Tests help catch bugs early, provide documentation for how the function should behave, and give you confidence when making changes. By organizing your code with dedicated functions and supporting them with robust tests, you create a codebase that's easier to work with, more reliable, and ready to scale. --- Transform your codebase into a well-organized, efficient machine. Embrace modular functions and comprehensive testing for faster development and happier developers. #CodeQuality #SoftwareEngineering #BestPractices #CleanCode #Testing #dataengineering

Legacy code: it’s a mess. No one wants to touch it. But it pays the bills. You open a file and it’s like walking into a maze: → No comments. → 300-line functions. → Variable names like ‘temp3’ and ‘doSomething()’. It’s a nightmare. But here’s the reality: most of us don’t get to start fresh. The code works, and rewriting it isn’t practical. Your job? Make it better without breaking it. Here’s how you can approach it: 1. Understand before you refactor. Don’t just dive in and start deleting things. Read it. Map it out. Use tools to speed this up. Ex - Bito can summarize logic or explain what a function or entire files does in plain English. Saves hours. 2. Write tests first. If there are no tests, you’re flying blind. Write some coverage before you change anything, so you know if it breaks. 3. Fix small, high-leverage things. → Rename variables (’temp3’ → ’averageTemp’). → Split up massive functions. → Add comments where the logic is dense. Small changes compound over time. 4. Leave it better than you found it. If you struggled to figure something out, document it. Add a test. Refactor the worst parts. Legacy code is how we got here… it’s alive, it’s evolving. Don’t hate it. Maintain it. And when you’ve got the right tools, the process doesn’t have to be painful. I’ve seen teams clean up years of spaghetti with AI tools that: → Identify unclear code. → Suggest refactors. → Catch bugs early. The goal isn’t to “modernize” everything. It’s to make legacy code easier to extend, understand, and trust. Fix what matters. Move fast. Don’t break things. #bug #code #ai #developer

🔥 𝗦𝗢𝗟𝗜𝗗 𝗶𝗻 𝗔𝗻𝗱𝗿𝗼𝗶𝗱 — 𝗳𝗿𝗼𝗺 𝗯𝘂𝘇𝘇𝘄𝗼𝗿𝗱 𝘁𝗼 𝗰𝗹𝗲𝗮𝗻 𝗰𝗼𝗱𝗲 Most Android projects become harder to maintain as they grow—ViewModels overloaded, messy dependencies, bloated interfaces. That’s where SOLID principles rescue us. Let’s see how each applies to Android dev (with real examples). 👇 Problem: ViewModels doing UI + business logic + network + caching. Solution: Extract UseCases (e.g. LoginUseCase) → ViewModel only exposes UI state. ✅ O – Open/Closed Problem: Adding new screen states = editing enums & when blocks everywhere. Solution: Use sealed classes → add new states without touching existing code. ✅ L – Liskov Substitution Problem: Subclasses break expectations (override badly, throw errors). Solution: Define interfaces for behavior, use careful base classes (e.g. Fragments). ✅ I – Interface Segregation Problem: Huge interfaces force unused methods (e.g. adapters with click + long click + swipe). Solution: Split into smaller contracts → classes only implement what they need. ✅ D – Dependency Inversion Problem: ViewModels depending directly on concrete Repositories/DataSources → tightly coupled, hard to test. Solution: Depend on interfaces/abstractions instead of concrete classes. Inject the implementation (via constructor or DI tools like Hilt/Dagger/Koin). 💡 Why It Matters Testable code → easier mocking. Maintainable structure → safe refactors. Scalable apps → adding features without breaking others. Clean separation → everyone in the team codes with confidence. 📌 Try this today: Pick your largest ViewModel → extract one UseCase + one interface. You’ll feel the difference immediately. ⚡ 👉 Question: Which SOLID principle do you struggle most to apply in your Android projects? Drop it in comments—I’ll share some practical refactoring examples. #AndroidDev #Kotlin #CleanArchitecture #MVVM #SOLID #DeveloperTools #MobileDev #CodeQuality #DesignPatterns

Every software developer thinks “Why is the code so messy ?”, “Why didn’t the code author think about this ?”, “Why does the service lack tests ?”, “What a ridiculous variable name ?”. But does anyone go an extra mile to fix this ? 😣 😠 The answer is No. We are so busy developing new features, we accept things the way they are, & don’t work on Tech debt. This eventually slows the development. ⏲ ⏲ If you are in a similar situation, then you should definitely adopt the Boys Scout rule. Let’s understand how you can improve the quality of your software by applying this rule. 📚 📚 Boys Scout rule says - “Always leave the camp ground cleaner than you found it”. If you find mess on the ground, you clean it up regardless of who might have made it. You intentionally improve the environment for the next group of campers. 🌐 🌐 When you apply the same principle to programming, you refactor the existing code while developing new features. You work on improving the surrounding code and it doesn’t have to be a huge improvement. You shouldn’t make the code worst with your contributions. Here are few ways in which you can apply the Boy Scout rule  :- 1️⃣ Code smells - Remove redundant code, unused variables, unused imports. 2️⃣ Refactoring - Remove code duplication, improve readability and reduce complexity. 3️⃣ Test automation - Add unit tests and integration tests. 4️⃣ Documentation - Improve the comments, include more details, add run books. 5️⃣ Knowledge sharing - Share your expertise with the team and encourage everyone to follow the same practice. By incorporating these practices, you can contribute to a cleaner, more maintainable codebase and avoid the accumulating technical debt. When you apply small improvements consistently, it impact is significant and improves the overall quality of your codebase. 🚀 🚀 Let me know in the comments below what else can we include to improve the code quality while applying the Boy Scout rule. Also, if you have applied this rule in the past, share your experience in the comments. 📢 📢 For more such posts, follow me. #refactoring #codingskills #softwareengineering #softwaredevelopment

Back then, I laughed. Now, I deeply understand what he meant. 😅 Most engineers don’t intentionally create bad code. But deadlines, feature rushes, and "we’ll refactor later" moments slowly pile up. And before you know it — the codebase becomes a museum of past decisions nobody wants to touch. That’s why most developers hate working on legacy code — not because it’s old, but because it’s unpredictable. It carries too many assumptions, hidden dependencies, and forgotten TODOs. Here are a few things that helped me deal with legacy systems better 👇 1. Respect the context. The old code wasn’t written by fools — it was written under different constraints. Understand why before you rewrite. 2. Document what you discover. Every small fix or insight can save someone else hours later. Leave breadcrumbs for future devs. 3. Refactor slowly, not emotionally. Don’t try to “clean everything.” Change only what you can test, measure, and maintain. 4. Automate the safety net. Even a few unit tests can make refactoring less scary. 5. Leave it better than you found it. Even small cleanups — better naming, comments, or separation — add up over time. Legacy code isn’t just “old code.” It’s a story of trade-offs, lessons, and evolution. So the next time you see a // TODO, remember — you’re writing history. Write it kindly. ✍️ Follow Abhay Singh for more such reads and don't forget to checkout the free interview resources here : https://lnkd.in/gT7acAgd Thanks.

7 habits that make your code "Senior" 1. Leave things slightly better The big refactor isn't coming. Those tickets get cut. While you're there: rename that variable, split that function, explain that edge case. Small improvements compound. 2. Make it testable If you can't test it easily, you built it wrong. Hard to test = too many dependencies, hidden state, or doing too much. These are the same things that make code hard to understand and modify. Testable code is maintainable code. 3. Write code that's easy to change Easy to modify when requirements shift. Can you rip this out without breaking everything? That's the test. 4. Explain your decisions Put the README in the repo. Put the "why" next to the code. Put the architecture decision in a file they'll actually find. Don't explain what the code does. Explain why you chose this over alternatives. 5. Kill bad ideas while they're cheap That elegant abstraction? That clever pattern? Try it in a spike branch. Give it 2 hours max. If it feels complicated, it is complicated. Delete it. 6. Choose simple over clever New library or 20 lines of code? Generic framework or straightforward config? Elegant abstraction or boring if-statement? Simple wins. 7. Delete more than you add Best PR is often removing code. That unused function? Gone. That one-caller abstraction? Inline it. Every line you don't write can't break.

Backend engineers who work with legacy code know the struggle. Nothing is documented. Nothing has tests. And somehow, it's running in production serving thousands of users. You want to rewrite everything. But that's rarely the answer. The better approach: • Understand why it works before changing it. • Refactor in small, safe increments. • Add tests around the edges first. Legacy code isn't bad code. It's code that solved yesterday's problems with yesterday's knowledge. Respect what it accomplished. Then make it better.