RACK: Code Search in the IDE using Crowdsourced Knowledge

TL;DR

RACK is an IDE tool that improves code search by translating natural language queries into API-based searches using crowdsourced knowledge from Stack Overflow, making code retrieval more effective and user-friendly.

Contribution

It introduces a novel approach that automatically mines and translates natural language queries into API-based searches using Stack Overflow data, integrated within the IDE.

Findings

Effective retrieval of relevant code snippets from open-source projects.

Improved code search accuracy with natural language queries.

Seamless integration within the IDE environment.

Abstract

Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus require carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective query for code search is both challenging and time consuming for the developers. In this paper, we propose a novel code search tool--RACK--that returns relevant source code for a given code search query written in natural language text. The tool first translates the query into a list of relevant API classes by mining keyword-API associations from the crowdsourced knowledge of Stack Overflow, and then applies the reformulated query to GitHub code search API for collecting relevant results. Once a query related to a programming task is submitted, the tool automatically mines relevant code snippets from thousands of open-source projects, and displays them as a ranked list within the context of the developer's programming environment--the IDE. Tool page: http://www.usask.ca/~masud.rahman/rack