dataflow coverage criteria are widely used in software testing, but there is almost no research on low-level dataflow metrics as software defect predictors. Aims: We examine two such metrics in this context: dep-deg...
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(纸本)9789897586477
dataflow coverage criteria are widely used in software testing, but there is almost no research on low-level dataflow metrics as software defect predictors. Aims: We examine two such metrics in this context: dep-degree (DD) proposed by Beyer and Fararooy and a new dataflow metric called dep-degree density (DDD). Method: We investigate the importance of DD and DDD in SDP models. We perform a correlation analysis to check if DD and DDD measure different aspects of the code than the well-known size, complexity, and documentation metrics. Finally, we perform experiments with five different classifiers on nine projects from the Unified Bug dataset to compare the performance of the SDP models trained with and without dataflow metrics. Results: 1) DD is noticeably correlated with many other code metrics, but DDD is not correlated or is very weakly correlated with other metrics considered in this study;2) both DD and DDD are highly ranked in the feature importance analysis;3) SDP models that use DD and DDD perform better than models that do not use dataflow metrics. Conclusions: data-flow metrics: DD and DDD can be valuable predictors in SDP models.
This paper investigates in terms of Kolmogorov complexity the differences between the information necessary to compute a recursive function and the information contained in its graph. Our first result is that the comp...
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This paper investigates in terms of Kolmogorov complexity the differences between the information necessary to compute a recursive function and the information contained in its graph. Our first result is that the complexity of the initial parts of the graph of a recursive function, although bounded, has almost never a limit. The second result is that the complexity of these initial parts approximate the complexity of the function itself in most cases (and in the average) but not always. (C) 2002 Elsevier Science B.V. All rights reserved.
A software metric is a tool that should be used in the development of quality software. The properties that define good software vary but encompass reliability, complexity, efficiency, testability, understandability, ...
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A software metric is a tool that should be used in the development of quality software. The properties that define good software vary but encompass reliability, complexity, efficiency, testability, understandability, and modifiability. The Henry metric measures the complexity of dataflow within a module and the complexity of inter-module communication. This thesis is an extension of a previous thesis titled AdaMeasure' that calculated the Halstead metric. The present design and implementation is a tool that computes the Halstead and Henry metrics for Ada programs.
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