Tool summarizes and classifies software issue reports to aid developers and managers
Automatic Assistance to Reduce Information Overload during Software Issue Report Understanding
Software Engineering
Summary
Long and detailed reports about software problems can be hard for developers and managers to quickly understand. The authors created a tool called iSum that automatically organizes and summarizes important parts of these reports. It offers a view for developers to see summaries for individual reports and another for managers to see patterns across many reports. Studies showed that iSum is more accurate than existing tools, helps developers work faster and make fewer mistakes, and aids managers in tracking trends.
What this means in practice
- •For software developers: Automatically generate concise summaries to speed up understanding of long software issue reports during debugging or feature planning.
- •For software project managers: Visualize trends and distribution of different types of information across multiple issue reports to better track project progress and bottlenecks.
Authors
Salma Begum Tamanna, Gias Uddin, Junaed Younus Khan, Lan Xia, Longyu Zhang
Abstract
Modern issue tracking systems are used to log an issue and track it from its inception to closure. Issue reports with diverse discussions from stakeholders can be large and verbose, making them challenging to analyze quickly. Our developer interviews revealed that they struggled with the diverse information in issue reports and demanded automated techniques to classify and summarize information. We designed a tool, iSum (issue summarizer), that helps with the automatic classification and summarization of information types discussed in issue reports. The summarizer offers two views: 1. Developer View takes an issue report as input and outputs visualized summaries of information in the report. 2. Manager View takes a suite of all issue reports under a given software project as inputs and shows the prevalence and trends of different information types across the reports. We evaluated iSum through three studies. 1. In an empirical study over two benchmarks, iSum offers, on average, 11-13% higher F1-scores than state-of-the-art baselines to detect information types. 2. We conducted a user study in task-based setup with 30 developers to determine iSum's effectiveness in issue exploration scenarios. Results showed increased productivity and accuracy with iSum compared to manual inspection. 3. We assessed iSum's feasibility for development and management tasks. It proved useful to both developers and project managers for issue comprehension and trend monitoring.