Claude Code
performance
Inefficient Algorithm Causing Request Timeouts
An endpoint that processes data times out when dataset size increases. The algorithm works correctly for small datasets but degrades exponentially with larger inputs. Response time jumps from 100ms to 10+ seconds as data volume grows.
The algorithm is correct but has poor time complexity that wasn't apparent at scale.
Error Messages You Might See
Request timeout after 30 seconds
Response time increases exponentially with data size
504 Gateway Timeout with larger datasets
Common Causes
- Nested loops creating O(n²) or O(n³) complexity (sorted list checking for each item)
- Inefficient search: linear search where binary search should be used
- Unnecessary array copying in loop creating O(n²) memory usage
- Recursive algorithm without memoization, recalculating same values
- Sorting inside loops instead of once before loop
How to Fix It
Profile the slow endpoint with realistic dataset size. Look for nested loops and recursive calls. Use appropriate data structures: HashSet for O(1) lookup, sorted array for binary search. Avoid creating new objects in tight loops. Memoize/cache expensive calculations. Consider pagination: process in batches instead of all at once.
Real developers can help you.
AUXLE
I am a Full Stack Developer experienced in building Websites, Web apps and Cross Platform Mobile Apps for Startups and Companies.
Antriksh Narang
5 years+ Experienced Dev (Specially in Web Development), can help in python, javascript, react, next.js and full stack web dev technologies.
Taufan
I’m a product-focused engineer and tech leader who builds scalable systems and turns ideas into production-ready platforms.
Over the past years, I’ve worked across startups and fast-moving teams, leading backend architecture, improving system reliability, and shipping products used by thousands of users. My strength is not just writing code — but connecting product vision, technical execution, and business impact.
Pratik
SWE with 15+ years of experience building and maintaining web apps and extensive BE infrastructure
Tejas Chokhawala
Full-stack engineer with 5 years experience building production web apps using React, Next.js and TypeScript.
Focused on performance, clean architecture and shipping fast.
Experienced with Supabase/Postgres backends, Stripe billing, and building AI-assisted developer tools.
Matt Butler
Software Engineer @ AWS
Omar Faruk
As a Product Engineer at Klasio, I contributed to end-to-end product development, focusing on scalability, performance, and user experience.
My work spanned building and refining core features, developing dynamic website templates, integrating secure and reliable payment gateways, and optimizing the overall system architecture.
I played a key role in creating a scalable and maintainable platform to support educators and learners globally.
I'm enthusiastic about embracing new challenges and making meaningful contributions.
Alvin Voo
I’ve watched the tech landscape evolve over the last decade—from the structured days of Java Server Pages to the current "wild west" of Agentic-driven development. While AI can "vibe" a frontend into existence, I specialize in the architecture that keeps it from collapsing.
My expertise lies in the critical backend infrastructure: the parts that must be fast, secure, and scalable. I thrive on high-pressure environments, such as when I had only three weeks to architect and launch an Ethereum redemption system with minimal prior crypto knowledge, turning it into a major revenue stream.
What I bring to your project:
Forensic Debugging: I don't just "patch" bugs; I use tools like Datadog and Explain Analyzers to map out bottlenecks and resolve root causes—like significantly reducing memory usage by optimizing complex DB joins.
Full-Stack Context: Deep experience in Node.js and React, ensuring backends play perfectly with mobile and web teams.
Sanity in the Age of AI: I bridge the gap between "best practices" and modern speed, ensuring your project isn't just built fast, but built to last.
Krishna Sai Kuncha
Experienced Professional Full stack Developer with 8+ years of experience across react, python, js, ts, golang and react-native. Developed inhouse websearch tooling for AI before websearch was solved : )
Sage Fulcher
Hey I'm Sage! Im a Boston area software engineer who grew up in South Florida. Ive worked at a ton of cool places like a telehealth kidney care startup that took part in a billion dollar merger (Cricket health/Interwell health), a boutique design agency where I got to work on a ton of exciting startups including a photography education app, a collegiate Esports league and more (Philosophie), a data analytics as a service startup in Cambridge (MA) as well as at Phillips and MIT Lincoln Lab where I designed and developed novel network security visualizations and analytics. I've been writing code and furiously devoted to using computers to make people’s lives easier for about 17 years. My degree is in making computers make pretty lights and sounds. Outside of work I love hip hop, the Celtics, professional wrestling, magic the gathering, photography, drumming, and guitars (both making and playing them)
You don't need to be technical. Just describe what's wrong and a verified developer will handle the rest.
Get HelpFrequently Asked Questions
How to identify O(n²) problems?
Double the input size. If time increases by 4x, likely O(n²). If increases by 2x, likely O(n). If no change, probably O(1).
When should binary search be used?
When searching sorted array/list. O(log n) instead of O(n). If unsorted, sort first (O(n log n)) then binary search.
How to optimize recursive algorithms?
Add memoization (cache results). Fibonacci: instead of recalculating fib(5) multiple times, cache it. Or use iterative approach.