Semantic metrics for software products

A. Mili, A. Jaoua, M. Frias, Rasha Gaffer Mohamed Helali

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Like all engineering disciplines, software engineering relies on quantitative analysis to support rationalized decision making. Software engineering researchers and practitioners have traditionally relied on software metrics to quantify attributes of software products and processes. Whereas traditional software metrics are typically based on a syntactic analysis of software products, we introduce and discuss metrics that are based on a semantic analysis: our metrics do not reflect the form or structure of software products, but rather the properties of their function. At a time when software systems grow increasingly large and complex, the focus on diagnosing, identifying and removing every fault in the software product ought to relinquish the stage to a more measured, more balanced, and more realistic approach, which emphasizes failure avoidance, in addition to fault avoidance and fault removal. Semantic metrics are a good fit for this purpose, reflecting as they do a system's ability to avoid failure rather than its proneness to being free of faults.

Original languageEnglish (US)
Pages (from-to)203-217
Number of pages15
JournalInnovations in Systems and Software Engineering
Volume10
Issue number3
DOIs
StatePublished - Sep 2014

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • Error maskability
  • Functional redundancy
  • Requirements flexibility
  • Semantic metrics
  • State redundancy
  • Syntactic metrics

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