학술논문

Pangolin: An SFL-Based Toolset for Feature Localization
Document Type
Conference
Source
2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE) Automated Software Engineering (ASE), 2019 34th IEEE/ACM International Conference on. :1130-1133 Nov, 2019
Subject
Computing and Processing
Visualization
Software
Task analysis
Tools
Feature detection
Java
Feature extraction
Spectrum-based Fault Localization
Program Understanding
Maintenance and Evolution
Language
ISSN
2643-1572
Abstract
Pinpointing the location where a given unit of functionality-or feature-was implemented is a demanding and time-consuming task, yet prevalent in most software maintenance or evolution efforts. To that extent, we present PANGOLIN, an Eclipse plugin that helps developers identifying features among the source code. It borrows Spectrum-based Fault Localization techniques from the software diagnosis research field by framing feature localization as a diagnostic problem. PANGOLIN prompts users to label system executions based on feature involvement, and subsequently presents its spectrum-based feature localization analysis to users with the aid of a color-coded, hierarchic, and navigable visualization which was shown to be effective at conveying diagnostic information to users. Our evaluation shows that PANGOLIN accurately pinpoints feature implementations and is resilient to misclassifications by users. The tool can be downloaded at https://tqrg.github.io/pangolin/.