Probabilistic Models for Software Quality Analysis
نویسندگان
چکیده
Improving the qualities of software systems is an important issue in software engineering. Software engineers need to know the information about software quality as early as possible in software development. Measuring the program complexity of software systems is the most straightforward approach to analyze software quality. In this paper, we propose five Stack-based Markov (SBM) models to measure program complexity from different viewpoints. Relationships between each proposed SBM model and software quality are investigated. Empirical study reveals that these SBM models have positive impact on software quality factors. These findings could help software development organizations to predict and control their software quality in the early stage of software development.
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