Announcing Bito’s free open-source sponsorship program. Apply now

Get high quality AI code reviews

Uncover Performance Bottlenecks with AI

Uncover Performance Bottlenecks with AI

Table of Contents

Slow code can lead to frustrating delays for users, hinders application scalability, and consumes more server resources. These hidden costs increase server maintenance fees and degrade overall application performance.

Additionally, developers face significant challenges in identifying performance bottlenecks.

Bito’s AI Code Review Agents can help. This intelligent tool analyzes pull requests to identify slow or resource-inefficient code.

The Agent’s specialized /review performance command instructs the AI to perform detailed code analyses, pinpointing performance issues. It provides valuable insights into how code performs against benchmarks and standards.


Let’s look at an example.

Pinpointing performance issues in code using AI

The Problem

The AI Code Review Agent flags a potential performance issue with the line payload = jwt.decode(token, get_settings().SECRET). The concern is that get_settings() might be fetching the secret key dynamically without proper caching. If this function involves file I/O operations or other slow processes, it could negatively impact performance, especially if get_settings() is called repeatedly. 

The Solution

The Agent suggests a solution to address this performance bottleneck. It recommends ensuring that get_settings() is cached using an appropriate strategy like lru_cache. This caching mechanism stores the results of the function in memory, eliminating the need for repeated slow operations like file I/O. The code suggestion provided by the Agent modifies the code to achieve this: 

# Before (original code)
payload = jwt.decode(token, get_settings().SECRET)


# After (improved code with caching)
settings = get_settings()
payload = jwt.decode(token, settings.SECRET)

How to Get Started?

Follow this simple guide to integrate the Agent with your repository.  

After that, trigger an AI Code Review Agent analysis by entering the command /review performance in a comment box below the pull request. Submit the comment, and the agent will analyze the code for performance issues, providing valuable feedback directly within the pull request.

Picture of Nisha Kumari

Nisha Kumari

Nisha Kumari, a Founding Engineer at Bito, brings a comprehensive background in software engineering, specializing in Java/J2EE, PHP, HTML, CSS, JavaScript, and web development. Her career highlights include significant roles at Accenture, where she led end-to-end project deliveries and application maintenance, and at PubMatic, where she honed her skills in online advertising and optimization. Nisha's expertise spans across SAP HANA development, project management, and technical specification, making her a versatile and skilled contributor to the tech industry.

Picture of Amar Goel

Amar Goel

Amar is the Co-founder and CEO of Bito. With a background in software engineering and economics, Amar is a serial entrepreneur and has founded multiple companies including the publicly traded PubMatic and Komli Media.

Written by developers for developers

This article was handcrafted with by the Bito team.

Latest posts

Recent releases: Pick your AI model, create PR from IDE, integrated Linter feedback, and more

PEER REVIEW: Shubham Gupta, Chief Technology Officer at ToolJet

Ultimate Java Code Review Checklist

Ultimate Python Code Review Checklist

13 Best Java AI Coding Tools 2024 [Free & Paid]

Top posts

Recent releases: Pick your AI model, create PR from IDE, integrated Linter feedback, and more

PEER REVIEW: Shubham Gupta, Chief Technology Officer at ToolJet

Ultimate Java Code Review Checklist

Ultimate Python Code Review Checklist

13 Best Java AI Coding Tools 2024 [Free & Paid]

From the blog

The latest industry news, interviews, technologies, and resources.

Get Bito for IDE of your choice