Debugging the Hard Way: Top Tips for Software Engineers

𝗔 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗺𝗶𝘀𝘁𝗮𝗸𝗲 𝘁𝗵𝗮𝘁 𝘀𝗹𝗼𝘄𝗲𝗱 𝗺𝘆 𝗴𝗿𝗼𝘄𝘁𝗵 𝗲𝗮𝗿𝗹𝘆 𝗼𝗻 I used to think debugging meant 𝗳𝗶𝘅𝗶𝗻𝗴 𝘁𝗵𝗲 𝗲𝗿𝗿𝗼𝗿 𝗺𝗲𝘀𝘀𝗮𝗴𝗲. So I would: * Change the line throwing the error * Add console logs randomly * Patch things until it “worked” And then… the same bug would come back. What I learned later is this: 𝗚𝗼𝗼𝗱 𝗱𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 𝗶𝘀 𝗮𝗯𝗼𝘂𝘁 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺, 𝗻𝗼𝘁 𝘁𝗵𝗲 𝘀𝘆𝗺𝗽𝘁𝗼𝗺. Now, when something breaks, I ask: * What changed recently? * What assumptions does this code rely on? * Where does the data come from, and where does it go? * Is this a code issue, a config issue, or an environment issue? Most production bugs aren’t complex. They’re 𝗺𝗶𝘀𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗼𝗼𝗱. Once I started debugging this way, fixes became cleaner — and confidence improved a lot. If you’re a developer struggling with bugs right now, slow down and trace the flow. The answer is usually there. 𝗪𝗵𝗮𝘁’𝘀 𝗼𝗻𝗲 𝗱𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 𝗵𝗮𝗯𝗶𝘁 𝘁𝗵𝗮𝘁 𝗵𝗲𝗹𝗽𝗲𝗱 𝘆𝗼𝘂 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁? #softwareengineering #debugging #developers #techlearning #codinglife #careergrowth #learninginpublic

🛠 Debugging Truth Every Developer Should Know Here’s the hard truth: 99% of production issues come from assumptions, not syntax errors. Over the years, I’ve learned that the most effective way to prevent hidden bugs is to: 🔹 Ask questions early and often 🔹 Log extensively at every step 🔹 Validate inputs rigorously These small habits save hours (sometimes days) of firefighting later. 💬 I’m curious—what’s the trick you swear by for catching hidden bugs before they become production nightmares? Let’s exchange ideas! #SoftwareEngineering #FullStackDevelopment #CodingTips #TechCareers

"Comments are dead weight. Especially by 2026." We had a production incident last year. A tricky `Kafka` consumer with an old comment explaining its 'logic'. The comment said `if message_type == 'CRITICAL'`, process immediately. Turns out, after a refactor two years ago, it was `if message_priority > 7`. Two different engineers, two different teams, both trusted the comment. Both burned hours debugging why high-priority messages were stuck. It wasn't a bug in the code, really. It was a bug in trust. The code was doing exactly what it was told, but the comment was telling a different story, years out of date. And that's way more insidious to debug than a runtime error. ❌ **The Trap:** Relying on inline comments to explain *how* code works, assuming they'll stay updated. ✅ **The Reality:** Code explains *how*. Tests explain *what* it does. Design docs explain *why*. If the code needs a comment to be understood, the code isn't clear enough. Or the comment is probably lying. What's your strategy for maintaining code clarity without falling into the comment trap? #ProductionLogs #Coding #Engineering #SRE

In my last posts, I shared how backend work isn’t just about logic, and how slowing down helped me understand systems better. Lately, that slower time hasn’t produced much code. It’s produced something else: clarity. A lot of my days now look like: • reading docs carefully • testing edge cases • seeing how systems behave when things go wrong One simple thing I’m realizing: Most bugs aren’t logic bugs. They’re assumption bugs. Assumptions about: • request order • retries • timing • system boundaries Even when a feature looks simple, the thinking behind it rarely is. I’m still learning to think a bit more before building a bit faster. What’s one assumption you once made that later surprised you? #BackendEngineering #SoftwareEngineering #SystemsDesign #LearningInPublic

I realized something while debugging today: When something doesn’t work, my first instinct is to change code. But the faster answer is usually to observe first. Log the input. Log the output. Log what actually happened — not what I expect. Most bugs aren’t complex. They’re just misunderstood behavior. Once I slowed down and watched the system instead of fighting it, the fix became obvious. Good engineering isn’t about writing more code. It’s about seeing clearly. #SoftwareEngineering#Debugging#DeveloperLife#Logging#ImportanceOfBugs

Write Tests Like Your Users, Not Like Your Code Unit tests matter. They prevent regressions, make refactoring safe, and document behavior. But many tests don’t test behavior — they test implementation. The Problem Calling internal methods or checking private variables means: - UI can be broken, yet tests pass - Bindings aren’t really tested - Tests break on the refactor even if the behavior is the same Behaviour Driven Mindset - Don’t test how it works. - Test what the user experiences. Example Components have a button and a label Clicking button changes label text ❌ Bad test: - Call changeText() - Check labelText = "Clicked" ✅ Behaviour-driven test: - Find button from DOM - Click it - Read label from DOM - Assert text changed (Because users click buttons, not methods.) Coverage vs Real Testing - You can have 90%+ coverage and still miss real bugs. - Unit tests are not just for code coverage, they are for behaviour coverage. Without behaviour-driven tests: - Coverage looks good - Product can still be broken Takeaway If your test can pass while the UI is broken, …it’s not testing the right thing. Test behavior. Test like a user. Not like a compiler. #UnitTesting #BDD #BehaviourDrivenDevelopment #TestingMindset #SoftwareEngineering #CleanCode #FrontendTesting #BackendTesting #QualityEngineering #TechLeadership #DevMindset #Refactoring #EngineeringCulture #TestingStrategy

Something that took me time to understand as a developer: Good code is not about clever solutions. It’s about clear ones. Code that: – is easy to read – is easy to change – is easy to explain usually wins in the long run. Most production problems don’t come from bad syntax. They come from unclear thinking. Simple code is a skill. What makes code “good” for you? #SoftwareEngineering #DeveloperLife

Most Developers Debug Symptoms, Not Systems ♂️♂️ And that’s why the same bugs keep coming back. You can chase: • error messages • stack traces • quick fixes from Stack Overflow But if you don’t understand why the system behaves the way it does, problems resurface in new forms. Here’s what developers often overlook 👇🏾 System boundaries: where responsibilities start and end Assumptions: what your code believes to be true Dependencies: what breaks when something changes Invariants: what must always hold Failure modes: how things degrade under stress When you grasp these, debugging becomes reasoning — not guessing. Refactors become safer. Scale becomes intentional. Because bugs aren’t random. They’re consequences. Stop patching symptoms. Start understanding systems. Which mistake cost you the most time to unlearn? 👇🏾 Let’s compare scars. #SoftwareDevelopment #debugging #Letsconnect

𝗦𝘁𝗼𝗽 𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝗿𝗮𝗻𝗱𝗼𝗺 𝗹𝗶𝗻𝗲𝘀 𝗼𝗳 𝗰𝗼𝗱𝗲 𝗵𝗼𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗯𝘂𝗴 𝗱𝗶𝘀𝗮𝗽𝗽𝗲𝗮𝗿𝘀. 𝗧𝗵𝗮𝘁 𝗶𝘀𝗻’𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴. I once spent 4 hours fixing a “simple” bug. I was panic-coding. Changed a variable. Refresh. Didn’t work. Added a console.log. Refresh. Didn’t work. Rewrote the function. Refresh. Crashed. That’s when I realized I was using the 𝗦𝗵𝗼𝘁𝗴𝘂𝗻 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 — firing everywhere and hoping something hits. Good debugging requires being a Sniper, not a gambler. Here’s the 𝗕𝗶𝗻𝗮𝗿𝘆 𝗦𝗲𝗮𝗿𝗰𝗵 𝗗𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 I now follow:🚀 ✅ 𝗥𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝗲 𝗳𝗶𝗿𝘀𝘁, 𝗳𝗶𝘅 𝗹𝗮𝘁𝗲𝗿 If you can’t make the bug happen consistently, you can’t fix it. Find the exact sequence of actions that breaks the system. ✅ 𝗜𝘀𝗼𝗹𝗮𝘁𝗲 𝘁𝗵𝗲 𝗯𝗹𝗮𝘀𝘁 𝗿𝗮𝗱𝗶𝘂𝘀 Don’t read 500 lines of code. Comment out half the file. Bug still exists? → It’s in the remaining half. Bug gone? → It was in the code you hid. Repeat until you’re left with the 5 lines that actually matter. ✅ 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗲𝗿𝗿𝗼𝗿 (𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗿𝗲𝗮𝗱 𝗶𝘁) Most juniors see red text and jump to StackOverflow. Experienced engineers read the stack trace. The computer is literally telling you what’s wrong: 𝗖𝗮𝗻𝗻𝗼𝘁 𝗿𝗲𝗮𝗱 𝗽𝗿𝗼𝗽𝗲𝗿𝘁𝘆 𝗼𝗳 𝘂𝗻𝗱𝗲𝗳𝗶𝗻𝗲𝗱 𝘛𝘳𝘶𝘴𝘵 𝘵𝘩𝘦 𝘭𝘰𝘨𝘴. 𝘋𝘦𝘣𝘶𝘨𝘨𝘪𝘯𝘨 𝘪𝘴 10% 𝘴𝘺𝘯𝘵𝘢𝘹 𝘢𝘯𝘥 90% 𝘴𝘵𝘢𝘺𝘪𝘯𝘨 𝘤𝘢𝘭𝘮. 𝘋𝘰𝘯’𝘵 𝘭𝘦𝘵 𝘵𝘩𝘦 𝘣𝘶𝘨 𝘱𝘢𝘯𝘪𝘤 𝘺𝘰𝘶. 𝘐𝘴𝘰𝘭𝘢𝘵𝘦 𝘪𝘵. 𝘛𝘳𝘢𝘱 𝘪𝘵. 𝘚𝘲𝘶𝘢𝘴𝘩 𝘪𝘵. Building things that matter! Pranjal Agarwal #Engineering #Debugging #SDE #Mindset #CareerGrowth #Programming #Productivity