Title: TextRank Based Search Term Identification for Software Change Tasks,
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.