TASSAL: Autofolding for Source Code Summarization

被引:11
|
作者
Fowkes, Jaroslav [1 ]
Chanthirasegaran, Pankajan [1 ]
Ranca, Razvan [2 ]
Allamanis, Miltiadis [1 ]
Lapata, Mirella [1 ]
Sutton, Charles [1 ]
机构
[1] Univ Edinburgh, Sch Informat, Edinburgh EH8 9AB, Midlothian, Scotland
[2] Oval Off, Tractable, 11-12 Oval, London E2 9DT, England
基金
英国工程与自然科学研究理事会;
关键词
D O I
10.1145/2889160.2889171
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
We present a novel tool, TASSAL, that automatically creates a summary of each source file in a project by folding its least salient code regions. The intended use-case for our tool is the first-look problem: to help developers who are unfamiliar with a new codebase and are attempting to understand it. TASSAL is intended to aid developers in this task by folding away less informative regions of code and allowing them to focus their efforts on the most informative ones. While modern code editors do provide code folding to selectively hide blocks of code, it is impractical to use as folding decisions must be made manually or based on simple rules. We find through a case study that TASSAL is strongly preferred by experienced developers over simple folding baselines, demonstrating its usefulness. In short, we strongly believe TASSAL can aid program comprehension by turning code folding into a usable and valuable tool. A video highlighting the main features of TASSAL can be found at https://youtu.be/_yu7JZgiBA4.
引用
收藏
页码:649 / 652
页数:4
相关论文
共 50 条
  • [1] Autofolding for Source Code Summarization
    Fowkes, Jaroslav
    Chanthirasegaran, Pankajan
    Ranca, Razvan
    Allamanis, Miltiadis
    Lapata, Mirella
    Sutton, Charles
    [J]. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2017, 43 (12) : 1095 - 1109
  • [2] A review of automatic source code summarization
    Zhang, Xuejun
    Hou, Xia
    Qiao, Xiuming
    Song, Wenfeng
    [J]. Empirical Software Engineering, 2024, 29 (06)
  • [3] Distilled GPT for source code summarization
    Chia-Yi Su
    Collin McMillan
    [J]. Automated Software Engineering, 2024, 31
  • [4] Recommendations for Datasets for Source Code Summarization
    LeClair, Alex
    McMillan, Collin
    [J]. 2019 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES (NAACL HLT 2019), VOL. 1, 2019, : 3931 - 3937
  • [5] Pyramid Attention For Source Code Summarization
    Chai, Lei
    Li, Ming
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [6] A Survey of Automatic Source Code Summarization
    Zhang, Chunyan
    Wang, Junchao
    Zhou, Qinglei
    Xu, Ting
    Tang, Ke
    Gui, Hairen
    Liu, Fudong
    [J]. SYMMETRY-BASEL, 2022, 14 (03):
  • [7] Recommendations for Datasets for Source Code Summarization
    LeClair, Alex
    McMillan, Collin
    [J]. arXiv, 2019,
  • [8] Distilled GPT for source code summarization
    Su, Chia-Yi
    McMillan, Collin
    [J]. AUTOMATED SOFTWARE ENGINEERING, 2024, 31 (01)
  • [9] Code Structure-Guided Transformer for Source Code Summarization
    Gao, Shuzheng
    Gao, Cuiyun
    He, Yulan
    Zeng, Jichuan
    Nie, Lunyiu
    Xia, Xin
    Lyu, Michael
    [J]. ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 2023, 32 (01)
  • [10] Contextual Information Enhanced Source Code Summarization
    Hu, Tian-Xiang
    Xie, Rui
    Ye, Wei
    Zhang, Shi-Kun
    [J]. Ruan Jian Xue Bao/Journal of Software, 2023, 34 (04): : 1695 - 1710