Mobile app and app store analysis, testing and optimisation

Harman, Mark; Al-Subaihin, Afnan A.; Jia, Yunyi; Martin, William H.; Sarro, Federica; Zhang, Yuanyuan

doi:10.1145/2897073.2897076

Cited by 14 publications

(8 citation statements)

References 30 publications

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“…Our study also has other findings for these sub-fields, and several findings concerning app testing of relevance to the wider software testing branch of research [15]. The observation that a study on app store developers can have actionable conclusions for so many different software engineering communities, highlights the crosscutting nature of this relatively recent phenomenon in software development and deployment.…”

Section: Introductionsupporting

confidence: 64%

“…For this research question, and to set the scope of this paper, we consider the Software Engineering Body of Knowledge (SWEBOK) [23] areas 1 through 5 as the software engineering life cycle stages; namely software requirements, design, construction, testing and maintenance. The Software Engineering (SE) research community has indeed highlighted the opportunities and challenges introduced by such an ecosystem [15] [25]. Software engineering researchers sought to leverage information found in the app store to guide mobile developers during requirements engineering [26] [47].…”

Section: Research Questionsmentioning

confidence: 99%

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App Store Effects on Software Engineering Practices

Al-Subaihin

Sarro

Black

et al. 2021

IIEEE Trans. Software Eng.

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In this paper, we study the app store as a phenomenon from the developers' perspective to investigate the extent to which app stores affect software engineering tasks. Through developer interviews and questionnaires, we uncover findings that highlight and quantify the effects of three high-level app store themes: bridging the gap between developers and users, increasing market transparency and affecting mobile release management. Our findings have implications for testing, requirements engineering and mining software repositories research fields. These findings can help guide future research in supporting mobile app developers through a deeper understanding of the app store-developer interaction.

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Section: Introductionsupporting

confidence: 64%

Section: Research Questionsmentioning

confidence: 99%

App Store Effects on Software Engineering Practices

Al-Subaihin

Sarro

Black

et al. 2021

IIEEE Trans. Software Eng.

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“…In the line of work carried out by the UCLAppA 4 team (Al-Subaihin et al 2015;Harman et al 2016) a feature is defined as "a claimed functionality offered by an app, captured by a set of collocated words in the app description and shared by a set of apps in the same category (Finkelstein et al 2017)." Harman et al were the first to carry out feature extraction from app descriptions by identifying feature list locations that follow a conventional pattern (Finkelstein et al 2017;Harman et al 2012).…”

Section: Apps' Feature Extraction From Artefacts Written In Natural Lmentioning

confidence: 99%

Empirical comparison of text-based mobile apps similarity measurement techniques

et al. 2019

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Context Code-free software similarity detection techniques have been used to support different software engineering tasks, including clustering mobile applications (apps). The way of measuring similarity may affect both the efficiency and quality of clustering solutions. However, there has been no previous comparative study of feature extraction methods used to guide mobile app clustering. Objective In this paper, we investigate different techniques to compute the similarity of apps based on their textual descriptions and evaluate their effectiveness using hierarchical agglomerative clustering. Method To this end we carry out an empirical study comparing five different techniques, based on topic modelling and keyword feature extraction, to cluster 12,664 apps randomly sampled from the Google Play App Store. The comparison is based on three main criteria: silhouette width measure, human judgement and execution time. Results The results of our study show that using topic modelling, in addition to collocationbased and dependency-based feature extractors perform similarly in detecting app-feature similarity. However, dependency-based feature extraction performs better than any other in finding application domain similarity (ρ = 0.7, p − value < 0.01).

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“…App Stores and their ecosystems have been studied and researched extensively; for instance in 2016, Martin et al performed a comprehensive survey of research related to the app store ecosystem [14]. Harman et al introduces two relevant topics: app store analysis app testing and optimisation [9], yet does not discuss possible relationships between these topics. Sibaihin et al discusses alpha and beta testing by humans using facilities provided by the app store [1]; their paper does not cover pre-launch testing, other release management tools, or Android Vitals.…”

Section: Related Workmentioning

confidence: 99%

“…https://exodus-privacy.eu.org/ 8 https://developer.android.com/distribute/best-practices/develop/android-vitals9 ("Installs on Active Devices (devices online in the past 30 days with this app installed. )…”

mentioning

confidence: 99%

Better Android apps using Android vitals

Harty¹,

Müller

2019

Proceedings of the 3rd ACM SIGSOFT International Workshop on App Market Analytics

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Google provides Android Vitals, a set of reports and tools for Android Developers as part of Google Play Console. Android Vitals can help developers improve their Android apps after an app has been launched by providing information on how their app is performing in key areas such as battery use, performance, and stability (freezes and crashes). Android Vitals also provides various comparisons, including against global bad behavior thresholds, against various peer groups of apps, and across releases of this app. Developers confirm Android Vitals notifies them of relevant problems and they found it valuable even if they also use crash reporting and mobile analytics. The underlying data is used by Google to assess the relative quality of Android apps; and the perceived quality may materially affect the visibility of an app in the Google Play Store. Yet little is known about the tools. This paper outlines various experiences from the developers' perspective of using Android Vitals with several popular Android apps to help open discussions and suggest further research areas. It introduces an open source project, created as part of our work, that enables developers to download pertinent data, particularly crash reports. The data can be analysed both by the development team and others. A particular benefit of this tool is to make the data available outside of the Google platform, which allows developers and (indirectly) researchers to develop additional analysis techniques not currently provided by the platform. CCS CONCEPTS • Software and its engineering → Application specific development environments; Software testing and debugging; Empirical software validation.

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Mobile app and app store analysis, testing and optimisation

Cited by 14 publications

References 30 publications

App Store Effects on Software Engineering Practices

App Store Effects on Software Engineering Practices

Empirical comparison of text-based mobile apps similarity measurement techniques

Better Android apps using Android vitals

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