Software Quality Metrics Calculations for Java Programming Learning Assistant System

Khin Khin Zaw, Hsu Wai Hnin, Khin Yadanar Kyaw, Nobuo Funabiki

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A Web-based Java Programming Learning Assistant System (JPLAS) has been proposed to assist Java programming educations in universities. In the code writing problem, the correctness of an answer code from a student is verified by running the test code on JUnit. Besides, their quality should be measured using the metrics to assess them. The currently using plugin could only be measured on eclipse for offline answering in JPLAS. To calculate the metrics and implement in web-based JPLAS, there are several equations that have been reported. In this paper, we find the proper equations to calculate the metrics that provide the same results as from Eclipse plugin. The application results for 45 source codes showed that the adopted metrics equations provide the same results as the plugin.

Original languageEnglish
Title of host publication2020 IEEE Conference on Computer Applications, ICCA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728159256
DOIs
Publication statusPublished - Feb 2020
Event2020 IEEE Conference on Computer Applications, ICCA 2020 - Yangon, Myanmar
Duration: Feb 27 2020 → Feb 28 2020

Publication series

Name2020 IEEE Conference on Computer Applications, ICCA 2020

Conference

Conference2020 IEEE Conference on Computer Applications, ICCA 2020
CountryMyanmar
CityYangon
Period2/27/20 → 2/28/20

Keywords

  • JPLAS
  • JUnit
  • code writing problem
  • test code

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

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