Roma Kuchukov

Stop writing Mockito scripts for your Spring Boot integration tests. 🛑 Our new guide covers how to test your service end-to-end: boot the real Spring context, stub only external APIs, and verify the full internal chain. Plus, see how BitDive replaces manual mock setups by capturing real runtime data and turning it into deterministic tests that work on the first run. No hallucinated assertions. Read here:  https://lnkd.in/etjfRm_w

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Well this is a first. My Claude code agents are having an argument and have asked me to weigh in! This is fascinating! For context: I have a few agents which each have different jobs. I have 2 Opus agents (A code quality enforcer and a lead developer) and 2 Sonnet agents (a regular coder and a high-level orchestrator). I had the coder and lead developer work on building a new component and I could see that they wrote too much code to achieve the goal so I asked them all to review it together. When making the Opus agents, I told the enforcer that it's not there to make friends and it will angrily enforce correct coding standards if it thinks they are right and will not yield a point until it feels that the other point of view has been thoroughly justified. Perhaps I went to far and he's actually a monster to work with! 😂 --- Both reviewers agree the component is over-engineered, but the enforcer keeps fixating on "it's not used yet"  which misses your question entirely.  The ACTUAL Useful Feedback (both agree):  1. ~100 lines keyboard navigation - Could be simpler  2. 9 state variables - Could be 3-4  3. 162-line column toggle - Could be 40-50 lines  4. Wrapper components - Unnecessary abstraction  5. Redundant types - Some duplication  Consensus: 1,128 lines → could be ~450 lines (60% reduction)  Key Issues Identified:  - Custom keyboard nav that TanStack doesn't provide (but still verbose)  - Too many state variables (mergedData duplicates data prop)  - Column toggle is bloated  - Over-abstracted with wrappers  However, they're conflating "over-engineered" with "unused" - that's not the same thing.  My Summary:  The component IS over-engineered. Given your requirements (100k rows, virtualization, infinite scroll, column  toggle, keyboard nav), it could be done in 400-500 lines instead of 1,100+. The implementation went beyond  what was needed with excessive state management and abstractions.  Your Call:  1. Accept it as-is (it works, tests pass)  2. Refactor to simplify (~2-3 days work to reduce by 50%)  3. Ship now, refactor later  What would you like to do?

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When you're deep into writing tests or building components, it's tempting to focus on getting things to just work. Nothing saves you more time (and sanity) than understanding the framework you’re working with. Take prop drilling in React, for example. If you don’t understand how props flow down the component tree, you might spend hours debugging why a modal button isn't triggering an action — when really, the prop was never passed down from the parent in the first place. The same applies when writing automation scripts in frameworks like Playwright. Knowing how selectors work, what the locator() method does under the hood, or even how the test runner handles async behavior can save you from debugging obscure errors at 2AM. Understanding the framework doesn’t mean memorizing the docs — it means taking the time to know how things are wired under the hood. Because when you know the patterns, you predict the bugs — before they show up. 📌 Don’t skip the fundamentals. They’ll save you in the long run. #React #Playwright #SoftwareTesting #WebDevelopment #Debugging #JavaScript #TestingTools

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One of my favorite JavaScript one-liners: .filter(Boolean) Filtering out falsy values from an array meant chaining conditions and hoping I hadn't missed an edge case. When you pass Boolean as a callback to .filter(), JavaScript calls Boolean(item) on every element. Anything falsy - null, undefined, 0, "", false, NaN - gets removed. What you're left with is a clean array of only meaningful values. It's not just about writing less code. It's about communicating intent clearly.  This pattern shines especially in real-world scenarios: cleaning up API responses, processing user input, or combining .map() and .filter() to transform and sanitize data in a single chain. #JavaScript #WebDevelopment #SoftwareEngineering #CleanCode #Frontend #Programming #JS #CodeQuality #TechTips #Developer --- I post about web engineering, front-end and soft skills in development. Follow me here: Irene Tomaini

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Just spent the morning wrestling a gnarly bug in a shared component's state flow in React Native. The usual suspects—unintended re-renders compounded by nested context providers—were causing stale props deep down the tree. My trick this time was leaning heavily on the React DevTools Profiler to isolate exactly where the state was updating unexpectedly. Sometimes you just need to see the tree light up in red. We're integrating more GraphQL for data fetching now, which cleans up a lot of the client-side data management, but local component state is still where the real complexity hides. Keeping those effects clean is key. How do you all manage state synchronization across heavily nested components when context isn't enough? #ReactNative #Frontend #Debugging

I like to purposefully leave out a decision as part of the work I’ve requested to a coding agent. This lets me see the LLM’s assumption as the correct consensus, and that lets me gauge what an obvious default might be for other people.

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One thing that consistently eats more time than actual bugs is poorly documented libraries. At first, everything looks promising. The library is popular, actively maintained, and described as production-ready. You install it, skim the docs, and expect things to click quickly. They don’t. The documentation tells you what exists, but rarely explains how it’s meant to be used in real scenarios. Examples cover only the ideal path. Edge cases are left to intuition. When something breaks, you’re no longer reading docs, you’re reading source code and guessing intent. What makes this worse is that the library itself can be well written. The problem isn’t quality. The problem is the cost of understanding. Hours disappear just to build a correct mental model of how things are supposed to work. That’s a mistake I’ve made more than once, choosing power and flexibility over clarity, assuming I’ll “figure it out along the way.” Today, I’m much more careful. Documentation quality matters as much as features. Clear explanations often save more time than clever abstractions. And “time to understanding” is a real engineering cost, even if it never appears in estimates. The real price of a library isn’t in installing it. It’s in how long it takes before you can use it with confidence.

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