Strategies for Preventing Bugs

Want fewer on-target bugs? Pretend the hardware doesn’t exist. Most embedded developers do this: if (gpio_read(PIN_BUTTON)) { // Do something } It looks harmless, right? But now your logic can’t run unless a button is physically wired to that pin. You’ve just handcuffed your system to a piece of silicon. Now, try this instead: bool is_pressed = read_button_state(); Let read_button_state() handle the hardware. Let the rest of your code just deal with data. That one shift means: - You can now simulate button presses in unit tests - Your logic works the same whether you’re on a dev board, in CI, or shipping to 100k units - You’re no longer blocked waiting for a dev board, you’re already shipping code That’s how you ship faster, break less, and sleep better. ♻️ Repost this if you’re tired of debugging on-target.

One powerful bug prevention technique is "Make Illegal States Unrepresentable", or MISU. For example, say you have a bunch of servers, each assigned a list of tasks, represented by `x = dict[Server, list[Task]]`. Now add a requirement: while not every task is assigned to a server, a task cannot be assigned to two different servers. One way to enforce that is a runtime check that all of the value lists are disjoint. Another is to apply MISU and instead store the data as `y = dict[Task, optional[Server]]`. Now it's literally impossible for a task to be assigned to two servers. The illegal state is unrepresentable. MISU is a powerful technique, but it has a few tradeoffs. The first is that it can come at the cost of ergonomics. Getting the tasks on a server is much easier with `x` than `y`, so if that's 99% of our use case we may want to prioritize that. Second, two requirements can have incompatible MISU representations. Consider the requirement "every server has at least one task". The MISU would be `z = dict[Server, pair[Task, list[Task]]]`, but that doesn't MISU the "no task overlaps" property anymore. You have to pick what you want to enforce with MISU and what you enforce with runtime checks. Finally, some states are undesirable but not illegal— the purpose of the program should be to get us *out* of these states. For example, the tasks might be assigned by a different system that doesn't know about our requirement, so we need to go through the servers and delete the duplicate tasks. If we used `y`, then we can't represent being in the undesirable state, and so can't write code to get us out of the state. I consider MISU a "default good technique". I start by assuming it *is* useful in my code except in specific conditions, rather than assuming it's *only* useful in certain conditions. I like the technique a lot! You tend to see it shared more in statically-typed languages, but it's by no means limited to them, and works perfectly well in dynamic languages too.

You’re shipping more PRs, and shipping them fast. You’re reviewing all your PRs before merging, but you can’t seem to shake off production bugs. What’s going wrong? It's a challenge we've all faced, and by using Hivel a lot of our clients have discovered this issue too. Early on, we thought thorough code reviews were the silver bullet. But reality check: bugs were still slipping through like sneaky ninjas. 🥷 That’s when we realized that while PR reviews are crucial, they're just one piece of the puzzle. However, the real headache comes when these bugs set off a vicious cycle that can disrupt your entire development process. It starts innocently enough: a bug is discovered in production, you halt everything to fix it, then it's back to testing and deploying. But here’s the catch: as you dedicate more time to chasing and fixing bugs, your planned features and enhancements get delayed. ⏳🐛 And guess what? Delayed features lead to rushed coding to meet deadlines, which, you guessed it right, can introduce more bugs. This cycle then repeats, draining your team’s morale and diverting resources away from innovation. It's like trying to paddle upstream against a current of challenges. Breaking this cycle is essential. Here’s how you can do it. 1️⃣ Unit Tests: Amp up your unit testing and catch small bugs before they make it to QA or production. 🕸️ 2️⃣ Simulated Chaos: Introduce "chaos engineering" during testing. Deliberate havoc can reveal your weak spots. ⚙️🔥 3️⃣ Bug Bounties: Encourage friendly competition among your engineers to find hidden bugs. The winner gets the legendary "Bug Buster" title! 🏆🐛 4️⃣ Post-Incident Debriefs: After a bug-triggered incident, hold blame-free discussions. Learnings from failures can become your secret weapon for future success. 💡📝 5️⃣ Thorough refactoring: Identity which repos lead to the highest change failure rate, and dedicate time to refactoring and clearing your tech debt. 6️⃣ Plan for bugs: If your sprint velocity is 100, plan the work only for 60, knowing you will get 40 story points worth of bugs based on your historical data. So, here's the takeaway: PR reviews are vital, but they're not the sole guardians of bug-free code. By weaving in these strategies, you can break the bug-bust cycle and chart a smoother course toward production excellence. Let's share our bug-busting stories! 🚀🐞 #BugHunting #EngineeringLeadership #CodeQualityMatters

Bugs Are Inevitable—But Manageable Bugs are a natural part of building any product or MVP. While you can’t eliminate them entirely, the right strategies can help minimize their impact and ensure faster, more efficient development: 1) Automated Testing: Use AI-driven tools to write and run tests, catching issues earlier in the process. 2) Code Reviews with AI Assistance: Leverage AI code analysis tools to identify potential bugs and suggest improvements. 3) Precise Requirement Analysis: Ensure clarity in product requirements to reduce miscommunication and avoid unnecessary complexity. 4) Continuous Integration: Automate build and deployment pipelines to catch bugs immediately after changes are made. 5) Real-Time Monitoring: Use AI for real-time error tracking and diagnostics in production environments. 6)Post-Launch Feedback: Combine user feedback with AI analytics to prioritize and address critical issues. AI is becoming a game-changer in minimizing bugs and speeding up product development. How do you integrate AI or automation to streamline your MVP or product development process?

👉 Why Bug Prevention is More CostEffective Than Bug Detection 👈 Have you ever wondered why some software projects run over budget? It's often due to the hidden costs of bug detection. Let's dive into why focusing on bug prevention can save both time and money. ➡️ The Cost of Bug Detection When bugs are detected late in the development cycle, they can be costly to fix. 🔹 Fixing a bug found during the design phase might cost $100. 🔹 If the same bug is found during the testing phase, it could cost $1,000. 🔹 If the bug is found by the enduser, it could cost $10,000 or more. Why? Because fixing a bug late often requires reworking design, code, tests, and documentation. ➡️ The Benefits of Bug Prevention Early Detection: By embedding quality engineering practices from the start, you catch issues early. Automation Automated tests can identify issues as soon as code is written, preventing them from progressing. Culture of Quality Encouraging a culture where quality is everyone's responsibility leads to better code and fewer bugs. Cost Savings Prevention is cheaper than detection. Every dollar spent on prevention can save you ten times that amount in detection and fixing costs. ➡️ How to Implement Bug Prevention Adopt Test Automation : Implement automated tests to catch issues early. Conduct Regular Code Reviews : Peer reviews can spot potential problems before they become costly issues. Invest in Training : Train your team on the best practices for writing clean, bug free code. ShiftLeft Testing : Start testing early in the development lifecycle. By focusing on bug prevention, you're not just saving money; you're delivering higher quality software, faster. So next time you're planning a project, think about where your money is best spent. Prevention is not just better than cure; it's also more cost effective. What are your thoughts on bug prevention vs. bug detection? Would love to hear your experiences in the comments below!

𝐓𝐨 𝐚𝐥𝐥 𝐐𝐀 𝐭𝐞𝐚𝐦𝐬 𝐚𝐧𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐦𝐚𝐧𝐚𝐠𝐞𝐫𝐬 𝐬𝐭𝐫𝐢𝐯𝐢𝐧𝐠 𝐟𝐨𝐫 𝐩𝐞𝐫𝐟𝐞𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐲: Do you ever wonder why, despite rigorous testing, bugs still slip into production? Here’s the fix: 𝐌𝐚𝐬𝐭𝐞𝐫𝐢𝐧𝐠 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐭𝐡𝐞 𝐛𝐮𝐠𝐬 It's a common misconception that extensive testing alone can fully protect your software from bugs in production. This oversight can lead to significant churn, a nightmare for any software company. The key is not just to test, but to ensure that every update and release undergoes thorough, automated checks. This method dramatically reduces the incidence of bugs reaching your users and mitigates the risk of increased churn. 𝐇𝐨𝐰 𝐚 𝐬𝐡𝐢𝐟𝐭 𝐢𝐧 𝐭𝐞𝐬𝐭𝐢𝐧𝐠 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡 𝐜𝐚𝐧 𝐦𝐚𝐤𝐞 𝐚𝐥𝐥 𝐭𝐡𝐞 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞: ➡️ 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Empowering not only QA automation engineers but also manual testers, product managers, business analysts, and developers to collaboratively build tests that integrate seamlessly into CI/CD pipelines is crucial. ➡️ 𝐏𝐫𝐞𝐯𝐞𝐧𝐭𝐢𝐨𝐧: Automating the validation of all functionalities helps prevent potential failures before they turn into costly problems, safeguarding user satisfaction. ➡️ 𝐈𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧: Encouraging every team member to contribute to creating robust, reliable tests makes the testing process more inclusive and thorough. To recognize that preventing bugs is about ensuring that they never reach production in the first place is a transformative approach to QA. We're not just enhancing testing, we're redefining it as a proactive, team-wide effort. Prevent bugs, not just discover them. Elevate your software quality and transform potential pitfalls into unparalleled performance. With this proactive approach, redefine your QA strategy to ensure your software becomes the solution they need, not a step in the problem chain. 🚀 #QualityAssurance #AITestingTools #AIAgent

From 15 to 50 bugs 🐞 are introduced every 1000 lines of code Fixing bugs takes at least 30 minutes longer than writing a line of code ⏳ How do you deal with this daunting reality? Let me give you my take on it. First, we must accept that no matter what we do, some bugs will be made into production. That's inevitable. That's why it's mindful of having a strategy to prevent and deal with bugs. Two key parts teams have to find adequate answers: 1. Preventing Bugs: Setting a strategy to reduce bugs getting into production drastically 2. Dealing with Bugs: Tactic to report bugs and use tools (e.g. Jam.dev) to accelerate bugs resolutions Now, let’s go into more detail on how to nail these parts. 1. Preventing Bugs The higher the test coverage, the more bugs you prevent. Yet, that's a double-edged sword. High test coverage comes with a cost, which you need to be aware of that. I've been in teams with a zero-bugs policy. As a result, software engineers continuously worked to increase test coverage and would drop whatever they were working on to fix bugs. That didn't help us improve the value created. On the contrary, it slowed us down. Some learnings from me: - 80%+ of test coverage is good enough - Production environment replica helps you run real-world tests and prevent undesired surprises - Structured code review sets a minimum bar for code quality 2. Dealing with bugs Some unpleasant and annoying bugs will get to your product. A bad decision is dealing with them on the fly. Someone reports the bug, and software engineers start debugging to find something. That's a poor use of their time, and fixing the bug will be unnecessarily long. The more information related to your bug, the quicker a software engineer can fix it. In the past, screenshots and devices were good enough, but now we're better equipped than that. You can use tools like Jam.dev to gather more information to accelerate troubleshooting and help developers act directly on the problem source. Better yet, it's a free Chrome extension. Critical parts to dealing with bugs: - Don't put all bugs in the same bucket. Understand how many users are impacted and how critical the impact is - Avoid interrupting software engineers if you lack information about the bug - Use tools like Jam.dev to gather relevant information to accelerate bug fixing Key Takeaways . Bugs are normal. Don't panic when you face them . Having a sustainable balance between test coverage and a sound strategy to deal with bugs will help you balance software quality and value creation . Zero bug policy dramatically reduces value creation Let's learn from each other. How do you prevent and deal with bugs? Have a lovely day, David