Section 1: Publication
Publication Type
Journal Article
Authorship
Bhattacharjee A, Roy B, and Schneider KA
Title
Supporting program comprehension by generating abstract code summary tree
Year
2022
Publication Outlet
in Proceedings of the 44th International Conference on Software Engineering (ICSE 2022) New Ideas and Emerging Results track, 5pp., Pittsburgh, PA, USA, May
DOI
ISBN
ISSN
Citation
Bhattacharjee, A., Roy, B., and Schneider, K. A., (2022). Supporting program comprehension by generating abstract code summary tree. in Proceedings of the 44th International Conference on Software Engineering (ICSE 2022) New Ideas and Emerging Results track, 5pp., Pittsburgh, PA, USA, May 2022.
https://doi.org/10.1145/3510455.3512793
Abstract
Reading through code, finding relevant methods, classes and files takes a significant portion of software development time. Having good tool support for this code browsing activity can reduce human effort and increase overall developer productivity. To help with program comprehension activities, building an abstract code summary of a software system from its call graph is an active research area. A call graph is a visual representation of the caller-callee relationships between different methods of a software system. Call graphs can be difficult to comprehend for a large code-base. Previous work by Gharibi et al. on abstract code summarizing suggested using the Agglomerative Hierarchical Clustering (AHC) tree for understanding the codebase. Each node in the tree is associated with the top five method names. When we replicated the previous approach, we observed that the number of nodes in the AHC tree is burdensome for developers to explore. We also noticed only five method names for each node is not sufficient to comprehend an abstract node. We propose a technique to transform the AHC tree using cluster flattening for natural grouping and reduced nodes. We also generate a natural text summary for each abstract node derived from method comments. In order to evaluate our proposed approach, we collected developers’ opinions about the abstract code summary tree based on their codebase. The evaluation results confirm that our approach can not only help developers get an overview of their codebases but also could assist them in doing specific software maintenance tasks.
Plain Language Summary
Section 2: Additional Information
Program Affiliations
Project Affiliations
Submitters
Publication Stage
Published
Theme
Presentation Format
Additional Information
Computer Science Core Team, Refereed Publications