STRICT: Information Retrieval Based Search Term Identification for Concept Location
Mohammad Masudur Rahman, Chanchal K. Roy

TL;DR
This paper introduces STRICT, a novel method that automatically identifies effective search terms from natural language change requests in software maintenance, improving code location accuracy.
Contribution
STRICT leverages IR techniques TextRank and POSRank to determine term importance based on co-occurrence and syntactic relations, advancing search term identification methods.
Findings
STRICT outperforms baseline methods in 52%-62% of requests
Achieves 30%-57% Top-10 retrieval accuracy
Demonstrates superiority over state-of-the-art techniques
Abstract
During maintenance, software developers deal with numerous change requests that are written in an unstructured fashion using natural language. Such natural language texts illustrate the change requirement involving various domain related concepts. Software developers need to find appropriate search terms from those concepts so that they could locate the possible locations in the source code using a search technique. Once such locations are identified, they can implement the requested changes there. Studies suggest that developers often perform poorly in coming up with good search terms for a change task. In this paper, we propose a novel technique--STRICT--that automatically identifies suitable search terms for a software change task by analyzing its task description using two information retrieval (IR) techniques-- TextRank and POSRank. These IR techniques determine a term's importance…
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