empirical evaluation of metrics on aspect-oriented programs An empirical evaluation of metrics on aspect-oriented programs

   The quality evaluation of software metrics measurement is considered as the primary indicator of imperfection prediction and software maintenance in various empirical studies of software products. However, there is no agreement on which metrics are compelling quality pointers for new software dev...

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Veröffentlicht in:UHD Journal of Science and Technology Jg. 3; H. 2; S. 74 - 86
Hauptverfasser: Ghareb, Mazen Ismaeel, Allen, Garry
Format: Journal Article
Sprache:Englisch
Veröffentlicht: University of Human Development 23.10.2019
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ISSN:2521-4209, 2521-4217
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Zusammenfassung:   The quality evaluation of software metrics measurement is considered as the primary indicator of imperfection prediction and software maintenance in various empirical studies of software products. However, there is no agreement on which metrics are compelling quality pointers for new software development approaches such as aspect-oriented programming (AOP) techniques. AOP intends to enhance programming quality by providing fundamentally different parts of the systems, for example, pointcuts, advice, and intertype relationships. Hence, it is not evident if quality characteristics for AOP could be extracted from direct expansions of traditional object-oriented programming (OOP) measurements. Then again, investigations of AOP do regularly depend on established static and dynamic metrics measurement; notwithstanding the late research of AOP in empirical studies, few analyses been adopted using the International Organization for Standardization 9126 quality model as useful markers of flaw inclination in this context. This paper examination we have considered different programming quality models given by various authors every once in a while and distinguished that adaptability was deficient in the current model. We have testing 10 projects developed by AOP. We have used many applications to extract the metrics, but none of them could extract all AOP Metrics. It only can measure some of AOP Metrics, not all of them. This study investigates the suitable framework for extract AOP Metrics, for instance, static and dynamic metrics measurement for hybrid application systems (AOP and OOP) or only AOP application.
ISSN:2521-4209
2521-4217
DOI:10.21928/uhdjst.v3n2y2019.pp74-86