How Do Android Developers Improve Non-Functional Properties of Software?

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{callan2022,

• author = "James Callan and Oliver Krauss and Justyna Petke and Federica Sarro",
• title = "How Do {Android} Developers Improve Non-Functional Properties of Software?",
• journal = "Empirical Software Engineering",
• year = "2022",
• volume = "27",
• pages = "Article 113",
• note = "Topical Collection:Software Performance",
• keywords = "genetic algorithms, genetic programming, genetic improvement, Non-Functional property optimisation, Android optimisation, Mining android, Execution time, Bandwidth, Frame rate, Memory, NFP",
• publisher = "Springer",
• ISSN = "1382-3256",
• URL = "https://discovery.ucl.ac.uk/id/eprint/10145101/",
• URL = "https://discovery.ucl.ac.uk/id/eprint/10145101/1/Petke_Callan2022_Article_HowDoAndroidDevelopersImproveN.pdf",
• URL = "https://rdcu.be/cZPhl",
• DOI = "doi:10.1007/s10664-022-10137-2",
• size = "42 pages",
• abstract = "Nowadays there is an increased pressure on mobile app developers to take non-functional properties into account. An app that is too slow or uses much bandwidth will decrease user satisfaction, and thus can lead to users simply abandoning the app. Although automated software improvement techniques exist for traditional software, these are not as prevalent in the mobile domain. Moreover, it is yet unknown if the same software changes would be as effective. With that in mind, we mined overall 100 Android repositories to find out how developers improve execution time, memory consumption, bandwidth usage and frame rate of mobile apps. We categorised non-functional property (NFP) improving commits related to performance to see how existing automated software improvement techniques can be improved. Our results show that although NFP improving commits related to performance are rare, such improvements appear throughout the development life-cycle. We found altogether 560 NFP commits out of a total of 74408 commits analysed. Memory consumption is sacrificed most often when improving execution time or bandwidth usage, although similar types of changes can improve multiple non-functional properties at once. Code deletion is the most frequently used strategy except for frame rate, where increase in concurrency is the dominant strategy. We find that automated software improvement techniques for mobile domain can benefit from addition of SQL query improvement, caching and asset manipulation. Moreover, we provide a classifier which can drastically reduce manual effort to analyse NFP improving commits.",
• notes = "Used by \cite{callan:2024:GI}",

}

Genetic Programming entries for James Callan Oliver Krauss Justyna Petke Federica Sarro

Citations