期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：9
DOI：10.15680/IJIRCCE.2015. 0309068
出版社：S&S Publications
摘要：Every software Industry requires the quality of code. Formal specifications are mathematically basedtechniques whose purposes are to help with the implementation of systems and software. They are used to describe asystem, to analyze its behavior, and to aid in its design by verifying key properties of interest through rigorous andeffective reasoning tools. These specifications are formal in the sense that they have syntax, their semantics fall withinone domain, and they are able to be used to infer useful information.Measuring Code Quality to Improve Specification Mining is used to create a set of design principles for codemodularization and produce set of metrics that characterize software in relation to those principles. Some metrics arestructural, architectural, and notions. The structural metrics refer to inter module-coupling based notions. Thearchitectural metrics refer the horizontal layering of modules in large software systems. Here we are using three typesof contributions coupling, cohesion, and complexity of metrics to modularize the software.These contributions measure were primarily at the level of how the individual classes were designed from thestandpoint of how many methods were packed into the classes, the depth of the inheritance tree, the inheritance fan-out,coupling between objects created by one object invoking a method on another object.Other contributions that have also used function call dependencies to characterize software modularization.Modularization algorithm is based on the combination of coupling and cohesion metrics. This is used to findmodularization quality.
关键词：Specification mining; machine learning; software modularization; code metrics; program understanding
