A framework for measuring and evaluating program source code quality

Hironori Washizaki, Rieko Namiki, Tomoyuki Fukuoka, Yoko Harada, Hiroyuki Watanabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)

Abstract

The effect of the quality of program source code on the cost of development and maintenance as well as on final system performance has resulted in a demand for technology that can measure and evaluate the quality with high precision. Many metrics have been proposed for measuring quality, but none have been able to provide a comprehensive evaluation, nor have they been used widely. We propose a practical frame-work which achieves effective measurement and evaluation of source code quality, solves many of the problems of earlier frameworks, and applies to programs in the C programming language. The framework consists of a comprehensive quality metrics suite, a technique for normalization of measured values, an aggregation tool which allows evaluation in arbitrary module units from the component level up to whole systems, a visualization tool for the evaluation of results, a tool for deriving rating levels, and a set of derived standard rating levels. By applying this framework to a collection of embedded programs experimentally, we verified that the framework can be used effectively to give quantitative evaluations of reliability, maintainability, reusability and portability of source code.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages284-299
Number of pages16
Volume4589 LNCS
Publication statusPublished - 2007
Externally publishedYes
Event8th International Conference on Product-Focused Software Process Improvement, PROFES 2007 - Riga
Duration: 2007 Jul 22007 Jul 4

Other

Other8th International Conference on Product-Focused Software Process Improvement, PROFES 2007
CityRiga
Period07/7/207/7/4

Fingerprint

Maintainability
Reusability
Evaluation
Computer programming languages
Programming Languages
Agglomeration
Visualization
Metric
Comprehensive Evaluation
Quantitative Evaluation
Portability
Normalization
System Performance
Aggregation
Maintenance
Framework
Costs
Technology
Costs and Cost Analysis
Module

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Washizaki, H., Namiki, R., Fukuoka, T., Harada, Y., & Watanabe, H. (2007). A framework for measuring and evaluating program source code quality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4589 LNCS, pp. 284-299)

A framework for measuring and evaluating program source code quality. / Washizaki, Hironori; Namiki, Rieko; Fukuoka, Tomoyuki; Harada, Yoko; Watanabe, Hiroyuki.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4589 LNCS 2007. p. 284-299.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Washizaki, H, Namiki, R, Fukuoka, T, Harada, Y & Watanabe, H 2007, A framework for measuring and evaluating program source code quality. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4589 LNCS, pp. 284-299, 8th International Conference on Product-Focused Software Process Improvement, PROFES 2007, Riga, 07/7/2.
Washizaki H, Namiki R, Fukuoka T, Harada Y, Watanabe H. A framework for measuring and evaluating program source code quality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4589 LNCS. 2007. p. 284-299
Washizaki, Hironori ; Namiki, Rieko ; Fukuoka, Tomoyuki ; Harada, Yoko ; Watanabe, Hiroyuki. / A framework for measuring and evaluating program source code quality. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4589 LNCS 2007. pp. 284-299
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