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STUDYING THE EVOLUTION OF SOFTWARE THROUGH ENTROPY METRICS

机译:通过熵度量研究软件的演变

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Based on the information theory definitions and mathematical characterizations of entropy measures, several entropy metrics were suggested for measuring the information content of software. These metrics are the Hartley, Shannon and generalized metrics. In addition to validating the utility of such metrics as indicators of software information content, this paper demonstrates their use in studying the evolution of a large software system. It is shown that studying the evolution of the modules within the system reveals the different module behaviors that are concealed when the full system is viewed at the top level. Thus, it is not enough to consider software evolution from the top level only.
机译:根据信息理论的定义和熵测度的数学特征,提出了几种熵测度来度量软件的信息量。这些指标是Hartley,Shannon和广义指标。除了验证诸如软件信息内容指标之类的度量的效用之外,本文还演示了它们在研究大型软件系统的演变中的用途。研究表明,研究系统内部模块的演化过程会揭示在顶层查看整个系统时所隐藏的不同模块行为。因此,仅从顶层考虑软件演进是不够的。

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