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Analyzing Evolution Patterns of Object-Oriented Metrics: A Case Study on Android Software

Analyzing Evolution Patterns of Object-Oriented Metrics: A Case Study on Android Software

Ruchika Malhotra, Megha Khanna
Copyright: © 2019 |Volume: 6 |Issue: 3 |Pages: 18
ISSN: 2334-4598|EISSN: 2334-4601|EISBN13: 9781522568469|DOI: 10.4018/IJRSDA.2019070104
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MLA

Malhotra, Ruchika, and Megha Khanna. "Analyzing Evolution Patterns of Object-Oriented Metrics: A Case Study on Android Software." IJRSDA vol.6, no.3 2019: pp.49-66. http://doi.org/10.4018/IJRSDA.2019070104

APA

Malhotra, R. & Khanna, M. (2019). Analyzing Evolution Patterns of Object-Oriented Metrics: A Case Study on Android Software. International Journal of Rough Sets and Data Analysis (IJRSDA), 6(3), 49-66. http://doi.org/10.4018/IJRSDA.2019070104

Chicago

Malhotra, Ruchika, and Megha Khanna. "Analyzing Evolution Patterns of Object-Oriented Metrics: A Case Study on Android Software," International Journal of Rough Sets and Data Analysis (IJRSDA) 6, no.3: 49-66. http://doi.org/10.4018/IJRSDA.2019070104

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Abstract

Software evolution is mandatory to keep it useful and functional. However, the quality of the evolving software may degrade due to improper incorporation of changes. Quality can be monitored by analyzing the trends of software metrics extracted from source code as these metrics represent the structural characteristics of a software such as size, coupling, inheritance etc. An analysis of these metric trends will give insight to software practitioners regarding effects of software evolution on its internal structure. Thus, this study analyzes the trends of 14 object-oriented (OO) metrics in a widely used mobile operating system software, Android. The study groups the OO metrics into four dimensions and analyzes the trends of these metrics over five versions of Android software (4.0.2-4.3.1). The results of the study indicate certain interesting patterns for the evaluated dimensions, which can be helpful to software practitioners for outlining specific maintenance decisions to improve software quality.