HookLens: Visual Analytics for Understanding React Hooks Structures

TL;DR

HookLens is an interactive visual analytics tool designed to help React developers understand complex hook dependencies and identify anti-patterns, significantly improving code comprehension and maintainability.

Contribution

This paper introduces HookLens, a novel visual analytics system specifically tailored for understanding React Hooks structures and dependencies, validated through user studies.

Findings

HookLens improves accuracy in detecting anti-patterns.

Participants using HookLens outperform those using conventional editors.

HookLens surpasses LLM-based coding assistants in anti-pattern detection.

Abstract

Maintaining and refactoring React web applications is challenging, as React code often becomes complex due to its core API called Hooks. For example, Hooks often lead developers to create complex dependencies among components, making code behavior unpredictable and reducing maintainability, i.e., anti-patterns. To address this challenge, we present HookLens, an interactive visual analytics system that helps developers understand howHooks define dependencies and data flows between components. Informed by an iterative design process with experienced React developers, HookLens supports users to efficiently understand the structure and dependencies between components and to identify anti-patterns. A quantitative user study with 12 React developers demonstrates that HookLens significantly improves participants' accuracy in detecting anti-patterns compared to conventional code editors. Moreover, a comparative study with state-of-the-art LLM-based coding assistants confirms that these improvements even surpass the capabilities of such coding assistants on the same task.