Code Comprehensibility Evaluation for Java Class based on LDA Topic Model

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The rapid development of the current software industry has produced a large amount of software, to evaluate the quality of a software code is difficult, which is also not conducive to software maintenance and iteration. Among them, software comprehensibility is one of the most important factors for software maintainability, and it is one of the indispensable elements for software quality evaluation. However, most of the existing software quality evaluation only stay in the concept level, lack of corresponding evaluation methods. From the perspective of java class code, this paper constructs a comprehensibility evaluation method for java class code based on LDA topic modeling, implements the software class code intelligibility evaluation, and quantifies the experimental results using clustering algorithm and WordNet similarity calculation method. Experiments show that the proposed method can clearly distinguish the comprehensibility of class code and obtain reliable evaluation results of software class code intelligibility.

Original languageEnglish
Title of host publicationProceedings - 2021 8th International Conference on Dependable Systems and Their Applications, DSA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages491-498
Number of pages8
ISBN (Electronic)9781665443913
DOIs
StatePublished - 2021
Event8th International Conference on Dependable Systems and Their Applications, DSA 2021 - Yinchuan, China
Duration: 11 Sep 202112 Sep 2021

Publication series

NameProceedings - 2021 8th International Conference on Dependable Systems and Their Applications, DSA 2021

Conference

Conference8th International Conference on Dependable Systems and Their Applications, DSA 2021
Country/TerritoryChina
CityYinchuan
Period11/09/2112/09/21

Keywords

  • Code Comprehensibility
  • K-means clustering
  • LDA topic modeling
  • Software quality evaluation

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