This guide walks you through the code quality features of Matter AI, which helps identify and fix code quality issues in your code.

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Code Quality Analysis

We follow a large list of anti-patterns for multiple languages and frameworks to identify code quality issues.

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Anti-patterns Analysis and Fix

Here’s an example list of performance-related topics that Matter AI can identify and help fix:

Inefficient Loops

Redundant computations, inefficient collection iteration, nested loops with high complexity

UI Rendering Bottlenecks

Excessive DOM manipulations, layout thrashing, unoptimized images and assets

CPU-Intensive Operations

Blocking the main thread, inefficient algorithms, unnecessary calculations

Database Performance

N+1 queries, missing indexes, inefficient joins, connection management

Memory Leaks

Unclosed resources, circular references, accumulating event listeners

Inefficient Data Structures

Using wrong data structures for specific operations, poor data organization

I/O Bottlenecks

Synchronous file operations, blocking I/O, inefficient resource handling

String Manipulation

Inefficient string concatenation, excessive regular expressions, encoding issues

Excessive Object Creation

Creating objects in loops, unnecessary object allocation, object pooling issues

Network Bottlenecks

Unoptimized API calls, excessive data transfer, connection management

Caching Problems

Missing cache implementation, ineffective cache invalidation strategies

Lazy Loading Issues

Improper implementation of lazy loading patterns, premature loading

Serialization Overhead

Inefficient serialization/deserialization of large objects, format selection

Resource Contention

Thread contention, lock contention, connection pool exhaustion

Synchronization Issues

Over-synchronization, lock granularity problems, deadlocks

Inefficient Algorithms

Using algorithms with poor time complexity, brute force approaches