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Empirical Validation of the Usefulness of Information Theory-Based Software Metrics

Software designs consist of software components and their relationships. Graphs are abstraction of software designs. Graphs composed of nodes and hyperedges are attractive for depicting software designs. Measurement of abstractions quantify relationships that exist among components. Most conventional metrics are based on counting. In contrast, this work adopts information theory because design decisions are information. The goal of this research is to show that information theory-based metrics proposed by Allen, namely size, complexity, coupling, and cohesion, can be useful in real-world software development projects, compared to the counting-based metrics. The thesis includes three case studies with the use of global variables as the abstraction. It is observed that one can use the counting metrics for the size and coupling measures and the information metrics for the complexity and cohesion measures.

Identiferoai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-2867
Date10 May 2003
CreatorsGottipati, Sampath
PublisherScholars Junction
Source SetsMississippi State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations

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