Iterative Refactoring Strategies for Software Projects

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.

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

𝐑𝐞𝐟𝐚𝐜𝐭𝐨𝐫𝐢𝐧𝐠 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐟𝐚𝐢𝐥. 𝐑𝐞𝐟𝐚𝐜𝐭𝐨𝐫𝐢𝐧𝐠 𝐫𝐨𝐮𝐭𝐢𝐧𝐞𝐬 𝐬𝐮𝐜𝐜𝐞𝐞𝐝. Every six months, someone proposes a "tech debt sprint." Leadership approves it. Two weeks of cleanup. Then back to features. Three months later, the codebase looks the same. Six months later, the same conversation. The pattern fails because it treats refactoring as an event instead of a practice. What works: the Boy Scout rule, enforced. Every feature touches code. Every touch leaves it slightly better. Not a complete rewrite, a slight improvement. Rename that confusing variable. Extract that duplicated logic. Add that missing test. Make it stick through code reviews that ask "what did you improve?" and weekly recognition for good cleanups. The math is simple. Ten engineers, five PRs each per week, one minor cleanup per PR. That's 2,500 micro-improvements per year. No sprint needed. No business case required. No permission asked. The catch: it requires discipline. It requires leaders who explicitly set the expectation: "Every PR includes one small cleanup." And it requires understanding that "just ship the feature" accumulates the debt that makes the next feature take twice as long. Refactoring isn't something you schedule. It's something you build into how you work. 𝐖𝐡𝐚𝐭'𝐬 𝐭𝐡𝐞 𝐥𝐚𝐬𝐭 𝐩𝐢𝐞𝐜𝐞 𝐨𝐟 𝐜𝐨𝐝𝐞 𝐲𝐨𝐮𝐫 𝐭𝐞𝐚𝐦 𝐥𝐞𝐟𝐭 𝐛𝐞𝐭𝐭𝐞𝐫 𝐭𝐡𝐚𝐧 𝐭𝐡𝐞𝐲 𝐟𝐨𝐮𝐧𝐝 𝐢𝐭?

We burned $200,000 rewriting perfectly good code.   And we were proud of it. We had a legacy monolith.   JavaEE, spaghetti logic, no tests.   Everyone hated touching it.   “Let’s just rewrite it in Kotlin,” I said. “It’ll take two months.” The team cheered.   We froze features on the old app.   We started building the “dream system.”   Clean architecture.   Microservices.   100% test coverage. Two months passed.   We were 30% done. Then the bugs in the old system started piling up.   Sales needed a new feature *now*.   But we couldn’t add it to the new system (not ready).   And we didn’t want to touch the old system (waste of time). So we did nothing.   We stalled. Six months in, we had two broken systems.   The old one was rotting.   The new one was missing half the edge cases the old one handled for free.   (Turns out that “ugly” if-statement in line 400 was keeping a million-dollar client happy.) The turn came when the CEO walked in.   “If we don’t ship a feature this quarter, we’re out of money.” We killed the rewrite that day.   Went back to the JavaEE monolith.   Refactored it piece by piece.   Strangled it slowly instead of murdering it. It wasn’t sexy.   But we shipped. Here’s the lesson:   A rewrite is a decision to stop delivering value for months, hoping you’ll be faster later.   You usually won’t be.   You’ll just be faster at writing bugs you already fixed five years ago. One clear, actionable thing:   Never rewrite.   Refactor until the old code disappears. What’s the worst “we’ll just rewrite it” disaster you’ve ever seen? #SoftwareArchitecture #Refactoring #LegacyCode #EngineeringManagement #HowNotToBreakProduction