Maintaining Code Quality Through Regular Reviews

In the last 11 years of my career, I’ve participated in code reviews almost daily. I’ve sat through 100s of review sessions with seniors and colleagues. Here’s how to make your code reviews smoother, faster and easier: 1. Start with Small, Clear Commits    - Break your changes into logical, manageable chunks. This makes it easier for reviewers to focus and catch errors quickly. 2. Write Detailed PR Descriptions    - Always explain the “why” behind the changes. This provides context and helps reviewers understand your thought process. 3. Self-Review Before Submitting    - Take the time to review your own code before submitting. You'll catch a lot of your own mistakes and improve your review quality. 4. Ask for Specific Feedback    - Don’t just ask for a “review”—be specific. Ask for feedback on logic, structure, or potential edge cases. 5. Don’t Take Feedback Personally    - Code reviews are about improving the code, not critiquing the coder. Be open to constructive criticism and use it to grow. 6. Prioritize Readability Over Cleverness    - Write code that’s easy to understand, even if it’s less “fancy.” Simple, clear code is easier to maintain and review. 7. Focus on the Big Picture    - While reviewing, look at how changes fit into the overall system, not just the lines of code. Think about long-term maintainability. 8. Encourage Dialogue    - Reviews shouldn’t be a one-way street. Engage in discussions and collaborate with reviewers to find the best solution. 9. Be Explicit About Non-Blocking Comments    - Mark minor suggestions as “nitpicks” to avoid confusion. This ensures critical issues get addressed first. 10. Balance Praise and Criticism    - Acknowledge well-written code while offering suggestions for improvement. Positive feedback encourages better work. 11. Always Follow Up    - If you request changes or leave feedback, follow up to make sure the feedback is understood and implemented properly. It shows you’re invested in the process. -- P.S: What would you add from your experience?

Code reviews aren't about finding bugs. If that's all you're doing in reviews, you've already lost. I've seen teams spend hours debating variable names and missing the actual problem: the code works, but nobody else can maintain it. Here's what code reviews actually catch: The junior engineer who hard-coded a feature that should be configurable. Not a bug. But you just locked yourself into technical debt that'll take 6 months to fix. The senior engineer who built something clever. Too clever. It works perfectly but breaks the moment someone else touches it. The architect who designed a system only they understand. No tests. No docs. Just "trust me, it works." Then they go on vacation and the system breaks. These aren't bugs. They're decisions that will hurt you later. Good code reviews ask different questions: • Can someone else debug this at 2am? • Will this still make sense in 6 months? • What happens when we scale 10x? • Are we building the right thing? Most teams optimize code reviews for finding syntax errors. Your IDE already does that. The real value is catching the decisions that look fine today but become disasters tomorrow. If your code reviews only find bugs, you're using them wrong. What's the worst "it works but..." code you've caught in review? #SoftwareEngineering #CodeReview #EngineeringLeadership

100 lines of code: reviewed in 10 minutes. 1000 lines of code: reviewed never. Code reviews exist to catch bugs, improve maintainability, and help teams write better software together. But most engineers treat them like assignments to pass instead of collaborative checkpoints. That mindset kills the process before it starts. ➧ When you're submitting a PR: 1. Keep it small Aim for 10-100 lines of code per pull request. Past 100 lines, reviewers start skimming. Past 500, they stop caring entirely. Large PRs are harder to review, take longer to approve, and make it nearly impossible to catch real bugs. Break your work into isolated, logical chunks. Yes, it's more work upfront. But it ships faster. 2. Write a description Give context. Always. Your reviewer might be on a different team, in a different timezone, or new to the codebase. Don't make them guess what you're solving. If you're fixing a bug, explain what broke and link to the ticket. If it's a visual change, add before/after screenshots. If you ran a script that generated code, paste the exact command you used. Context turns a confusing diff into a clear story. 3. Leave preemptive comments If part of your diff looks unrelated to the main logic, explain it before your reviewer asks. "Fixed a typing issue here while working on the main feature." "This file got reformatted by the linter, no logic changes." These small clarifications save back-and-forth and show you're thinking about the reviewer's experience. ➧ When you're reviewing a PR: 1. Be overwhelmingly clear Unclear comments leave people stuck. If you're making a suggestion but don't feel strongly, say it: "This could be cleaner, but use your judgment." If you're just asking a question, mark it: "Sanity check, is this intentional? Non-blocking, just curious." Over-communicate your intent. Especially with remote teams or people you don't know well. 2. Establish approval standards with your team Decide as a team when to approve vs. block a PR. At Amazon and now at Nielsen, we approve most PRs even with 10+ comments because we trust teammates to address feedback. The only exception: critical bugs that absolutely can't go to production. Without clear standards, people feel blocked by style comments and approvals feel arbitrary. Talk to your team. Set the rules. Stick to them. 3. Know when to go offline Some conversations don't belong in PR comments. If the code needs a major rewrite, if there's a design disagreement, or if you're about to write a paragraph, stop. Ping your teammate directly. Have a quick call. Save everyone time. Leave a comment like "Let's discuss this offline" so they know you're not ignoring it.

Bad code doesn’t show up overnight. It’s the result of a broken code review culture. It’s the result of months or years of speed over quality. And no, focusing on small things like, “Move this hardcoded string to a constant,” isn’t enough. Code reviews should be where growth happens: • Refactor for clarity. • Catch edge cases early. • Challenge design decisions. • Improve tests, not just add them. • Reinforce clean principles like DRY. When done right, code reviews improve not just the code but the entire team. Thoughts?

Code reviews are about catching “evolvability defects” as much as bugs. When most teams think of code review, they think about spotting bugs. But here’s the reality: only 25% of issues flagged in reviews are actual bugs. The rest? They’re deeper problems that make a codebase harder to maintain and scale over time. These are what we call “evolvability defects.” Evolvability defects don’t crash your system today, but they lead to bottlenecks, tech debt, and friction that will cost your team down the line. Here’s a breakdown of what they look like: → 10% of issues are basic inconsistencies—alignment, spacing, structure. → 33-44% are documentation gaps—comments with missing context, unclear variable names, or lacking structure. → 44-55% are structural problems—inefficient organization, shortcuts that don’t scale, design choices that slow down future development. For developers, effective code review means more than finding bugs. It’s about ensuring code is readable, maintainable, and built to last. For engineering leaders, it’s about risk management. When code review prioritizes evolvability defects, your team’s velocity tomorrow is as strong as it is today. Is your team identifying evolvability defects? They’re what separate short-term fixes from long-term success. #codereview #bito #ai

Stop leaving "corrective" PR comments. You're just creating code monkeys. 🙊 There, I said it. Early in my career, a senior dev left a comment on my code: "Incorrect. Use a different pattern." I felt stupid, and I learned nothing about the why. I just did what I was told. That experience taught me that the goal of a code review isn't just to fix the code. It's to build a better engineer. Something I learned while being a Teaching Assistant for a Software Engineering class but never got to apply in the real world. I could map the learnings 1-1. My philosophy now: A great PR review closes two things: 👇 1. The technical ticket. 2. An invisible ticket in the other developer's confidence. Here's my 3-part framework for reviews that actually coach: 1. Start with a Question, Not a Command: Instead of "Change this," try "What are your thoughts on how this might scale under heavy load?" It invites a discussion. 2. Explain the 'Why' Behind the 'What': Don't just suggest a change. Link to the documentation, a blog post, or an internal principle that explains the reasoning. 3. Compliment the Good Stuff: Find something to praise. "Love how you simplified this logic here." It creates psychological safety and makes the constructive feedback easier to hear. Let's stop correcting and start coaching. 🚀 #Leadership #SoftwareDevelopment #WorkplaceCulture #Mentorship #CodeReview

Unlock the full potential of your data projects with regular code reviews. Here’s what you need to know about them: 𝗪𝗵𝘆 𝗥𝗲𝗴𝘂𝗹𝗮𝗿 𝗖𝗼𝗱𝗲 𝗥𝗲𝘃𝗶𝗲𝘄𝘀 𝗠𝗮𝘁𝘁𝗲𝗿 • 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗖𝗼𝗱𝗲 𝗤𝘂𝗮𝗹𝗶𝘁𝘆: Regular reviews ensure that code is not only functional but also clean and maintainable. They help in identifying potential errors early, saving time and resources in the long run.    • 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗦𝗵𝗮𝗿𝗶𝗻𝗴: They create a platform for team members to share coding practices and insights, which enriches the team’s overall skill set.    • 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: By regularly engaging with your team’s code, you build a deeper understanding of the project and foster a supportive coding culture.    • 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗚𝗿𝗼𝘄𝘁𝗵: Receiving constructive feedback and discussing different approaches to problem-solving contribute significantly to your professional development. 𝗛𝗼𝘄 𝘁𝗼 𝗣𝗲𝗿𝗳𝗼𝗿𝗺 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗖𝗼𝗱𝗲 𝗥𝗲𝘃𝗶𝗲𝘄𝘀 • 𝗣𝗿𝗲𝗽𝗮𝗿𝗲 𝗶𝗻 𝗔𝗱𝘃𝗮𝗻𝗰𝗲: Take the time to review the code before the meeting, noting areas that need clarification or improvement.    • 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Approach reviews as learning opportunities, asking questions to understand decisions and considering alternative solutions together.    • 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗲 𝗖𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝘃𝗲𝗹𝘆: Deliver feedback that is specific, actionable, and focused on the code, not the coder.    • 𝗞𝗲𝗲𝗽 𝗶𝘁 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁: Aim for concise, regular reviews that respect everyone’s time and keep the project moving.    • 𝗙𝗼𝗹𝗹𝗼𝘄 𝘂𝗽: Ensure that actionable feedback from the review is implemented to continuously improve the codebase. Regular code reviews help to increase the quality of your code base and foster an open team environment that supports continuous learning. Have you participated in code reviews in your data role, and what benefits have you observed? ---------------- ♻️ Share if you find this post useful ➕ Follow for more daily insights on how to grow your career in the data field #dataanalytics #dtascience #codequality #teamwork #careergrowth

if (!high_Quality_Code_Review) { code_Quality.suffers(); } The biggest challenge when it comes to code reviews is time. We all want to provide thoughtful feedback that improves the codebase without spending endless hours dissecting lines of code. – Deliver high-quality feedback. – Do it efficiently. – Minimize the back-and-forth between the author and reviewer. Here’s how to do it: 1. Start with the Change Description Always start with the PR (Pull Request) Description: ↳Understand the Goal: What problem is this change solving? Why is it necessary now? Does it align with the product or technical vision? ↳ Key Design Insights: Look for architectural decisions and trade-offs. Is the proposed solution justified, or are there better alternatives? ↳ Clarity Check: If the PR description needs to be more specific or complete, request the author to refine it. It’s better to clarify the intent than to misunderstand the implementation. 2. Focus on the Interface First Now, move on to the interface, not the implementation. ↳Abstraction: Does the interface present a clean abstraction? Is it intuitive for others to use? A good abstraction hides unnecessary details and provides a natural way for other parts of the system to interact with the component. ↳ Naming Conventions: Are the names of methods, classes, or variables clear and self-explanatory? Names should reflect their purpose without needing additional comments. ↳Contracts: -Does the interface define clear inputs, outputs, and side effects? - Inputs and Preconditions: What does the function or class expect? - Outputs and Postconditions: What does it guarantee? - Side Effects: Are there implicit changes, such as modifying global state? 3. Review the Implementation and Tests Last Once the interface is solid, dive into the implementation. Here’s how to structure your review: ↳ Correctness: –Does the implementation meet the intended functionality? –Test it against the stated goals in the PR description. ↳Edge Cases: Does the code handle unexpected inputs gracefully? –What happens if something goes wrong (e.g., network issues, null inputs)? – Can someone unfamiliar with the change understand the logic quickly? –Use proper indentation, modularization, and logical flow. –Is the solution simpler than necessary? ↳Efficiency: Does the code perform well under expected load? - Are there any unnecessary loops or expensive operations? - Is memory or CPU usage optimized? ↳ Test Coverage Checklist - Do the tests cover all important scenarios, including edge cases? - Tests should be simple and obvious. Avoid abstracting tests too much, even if it involves repetition. - If this change fixes a bug, ensure there’s a regression test to prevent it from resurfacing. - For changes with performance implications, validate them under real-world conditions.

9 code review practices your team should follow to go from Good → Great projects. (these helped my team deliver 100s of projects without wasting hours fixing bugs) 🟢As a team: ➡️Establish goals and expectations beforehand: for example: + functional correctness + algorithmic efficiency + improving code quality + ensuring code standards are met ➡️Use code review tools Use: (GitHub PRs, GitLab MRs, and Atlassian Crucible). + easily track changes + streamline the review process ➡️Automate code checks:  It will help you to: + find syntax errors + avoid common issues + reduce code style violations and potential bugs. 🟡As a reviewer: ➡️Start early, review often:  do this to: + catch issues early + prevent technical debt + ensure that code meets project requirements. ➡️Keep reviews small and focused:  you get: + an easier process + shorter turnaround time. + better collaboration in the team ➡️Balance speed and thoroughness:  + do comprehensive reviews  + but avoid excessive nitpicking ➡️Give constructive feedback: always be: + specific, actionable, and respectful + focus on improvement rather than criticizing.  + make a space for open communication to answer questions & give clarifications. 🟠As a reviewee: ➡️follow up on feedback:  + don’t take the comments personally + actively work on feedback after the session + make necessary revisions and follow up to confirm ➡️Follow coding standards:  focus on improving: + readability + maintainability Remember - mutual respect during the code reviews is crucial for a great team culture! – P.S: If you’re a Sr. Software engineer looking to become a Tech Lead or manager. I’m doing a webinar soon. Stay tuned :)

How can we vibe code while still maintaining code quality? Over the past year, I've shifted 95% of my development from manually writing code to using coding agents. I wrote this blog on some tricks I learned to work successfully with agents: https://lnkd.in/gZzPGzhU Some background is that we're working on the coding agent OpenHands: https://app.all-hands.dev/ It's a pretty complex project with a Python backend, TypeScript frontend, extensive use of docker, etc. etc. So maintaining code quality is paramount. Trick 1: lean heavily on static analysis tools. If writing in a weakly typed language like Python, use type annotations and checking w/ mypy or pyright. Lint with a tool like ruff, and make sure that you use pre-commit so the agent doesn't "forget". Trick 2: practice test-driven development. Agents often get lazy and commit code that doesn't really fix your problem. But if you ask them to write tests first before writing any code to fix things, this results in much better results. Trick 3: use continuous integration. This allows you to make sure that tests are run on every pull request. Agents can be asked to monitor github actions and fix any resulting bugs. Trick 4: customize instructions for repositories. Each repository may have slightly different rules, so you can customize prompts and setup scripts for your repo. Trick 5: perform two-tiered code review. In big software projects code review is standard, but when working with agents, we first have the person who invokes the agent review the agent's code as a draft PR, then a second review review the full PR. This is just an initial list, so if you have any feedback on the tricks I wrote here, or other suggested ones I'd love to hear them. And there's many more details in the blog at the top of the thread!