Rating Decision Analysis Based on Ios App Store Data

Erić, Dejan; Bačík, Radovan; Fedorko, Igor

doi:10.12776/qip.v18i2.337

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…Wano and Iio [241] analysed the textual content of 856 reviews from 500 apps in the Japanese App Store, and found that the review styles differed between apps in different categories. In a large scale study, Erić et al [61] studied the star ratings of 48 million reviews mined from 968 popular free and paid Apple apps. They found that the reviews were mostly positive, and that there were significant differences in the distributions between categories, and also between free and paid sections.…”

Section: Requirements Engineeringmentioning

confidence: 99%

A Survey of App Store Analysis for Software Engineering

Martin

Sarro

Jia

et al. 2017

IIEEE Trans. Software Eng.

347

242

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App Store Analysis studies information about applications obtained from app stores. App stores provide a wealth of information derived from users that would not exist had the applications been distributed via previous software deployment methods. App Store Analysis combines this non-technical information with technical information to learn trends and behaviours within these forms of software repositories. Findings from App Store Analysis have a direct and actionable impact on the software teams that develop software for app stores, and have led to techniques for requirements engineering, release planning, software design, security and testing. This survey describes and compares the areas of research that have been explored thus far, drawing out common aspects, trends and directions future research should take to address open problems and challenges.

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Section: Requirements Engineeringmentioning

confidence: 99%

A Survey of App Store Analysis for Software Engineering

Martin

Sarro

Jia

et al. 2017

IIEEE Trans. Software Eng.

347

242

View full text Add to dashboard Cite

show abstract

Understanding the Origins of Mobile App Vulnerabilities: A Large-Scale Measurement Study of Free and Paid Apps

Watanabe¹,

Akiyama²,

Kanei³

et al. 2017

2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR)

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Study on the Vulnerabilities of Free and Paid Mobile Apps Associated with Software Library

Watanabe

Akiyama²,

Kanei³

et al. 2020

IEICE Trans. Inf. & Syst.

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This paper reports a large-scale study that aims to understand how mobile application (app) vulnerabilities are associated with software libraries. We analyze both free and paid apps. Studying paid apps was quite meaningful because it helped us understand how differences in app development/maintenance affect the vulnerabilities associated with libraries. We analyzed 30k free and paid apps collected from the official Android marketplace. Our extensive analyses revealed that approximately 70%/50% of vulnerabilities of free/paid apps stem from software libraries, particularly from third-party libraries. Somewhat paradoxically, we found that more expensive/popular paid apps tend to have more vulnerabilities. This comes from the fact that more expensive/popular paid apps tend to have more functionality, i.e., more code and libraries, which increases the probability of vulnerabilities. Based on our findings, we provide suggestions to stakeholders of mobile app distribution ecosystems.

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Rating Decision Analysis Based on Ios App Store Data

Cited by 4 publications

References 17 publications

A Survey of App Store Analysis for Software Engineering

A Survey of App Store Analysis for Software Engineering

Understanding the Origins of Mobile App Vulnerabilities: A Large-Scale Measurement Study of Free and Paid Apps

Study on the Vulnerabilities of Free and Paid Mobile Apps Associated with Software Library

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