Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
156 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

TextRank Based Search Term Identification for Software Change Tasks (1807.02263v1)

Published 6 Jul 2018 in cs.SE and cs.IR

Abstract: During maintenance, software developers deal with a number of software change requests. Each of those requests is generally written using natural language texts, and it involves one or more domain related concepts. A developer needs to map those concepts to exact source code locations within the project in order to implement the requested change. This mapping generally starts with a search within the project that requires one or more suitable search terms. Studies suggest that the developers often perform poorly in coming up with good search terms for a change task. In this paper, we propose and evaluate a novel TextRank-based technique that automatically identifies and suggests search terms for a software change task by analyzing its task description. Experiments with 349 change tasks from two subject systems and comparison with one of the latest and closely related state-of-the-art approaches show that our technique is highly promising in terms of suggestion accuracy, mean average precision and recall.

Citations (18)

Summary

We haven't generated a summary for this paper yet.