Fragmentation Problem in Android

Park, Je-Ho; Park, Young Bom; Ham, Hyung Kil

doi:10.1109/icisa.2013.6579465

Cited by 16 publications

(3 citation statements)

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“…The problem of mobile device fragmentation is well-known and is considered as one of the most difficult aspects of the mobile testing [9][10][11]. In particular, this paper addresses the problem of the selection of the optimal set of devices for testing as often discussed by the software engineering practitioners' community in numerous forums and blogs.…”

Section: B Using Combinatorial Methods To Provide Coverage Of the Dementioning

confidence: 99%

Using Combinatorial Approaches for Testing Mobile Applications

Vilkomir

Amstutz

2014

2014 IEEE Seventh International Conference on Software Testing, Verification and Validation Workshops

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Device-specific faults are very common for mobile software applications. To avoid such faults and guarantee the reliability and quality of mobile applications, sufficient testing is required on different mobile devices, which is expensive and time-consuming. This makes the task of the optimal selection of mobile devices for testing important and interesting from both practical and theoretical points of view. The suggested approach in this paper is based on combinatorial methods for coverage of each device characteristics. The initial results of the experimental investigation using comparisons with a random selection of devices are provided and show that the proposed approach is effective and promising.

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Section: B Using Combinatorial Methods To Provide Coverage Of the Dementioning

confidence: 99%

Using Combinatorial Approaches for Testing Mobile Applications

Vilkomir

Amstutz

2014

2014 IEEE Seventh International Conference on Software Testing, Verification and Validation Workshops

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“…Furthermore, it can also create security vulnerabilities, as older versions of Android may have a different levels of security than the latest version [251]. Several factors contribute to the fragmentation of Android versions, including the slow pace of updates from device manufacturers, many different Android devices on the market, and the fact that some devices are no longer supported by their manufacturers [252]. This can make it difficult for users and developers to ensure that their devices and apps are running the latest version of the Android.…”

Section: Version Fragmentationmentioning

confidence: 99%

Smartphone Security and Privacy: A Survey on APTs, Sensor-Based Attacks, Side-Channel Attacks, Google Play Attacks, and Defenses

et al. 2023

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There is an exponential rise in the use of smartphones in government and private institutions due to business dependencies such as communication, virtual meetings, and access to global information. These smartphones are an attractive target for cybercriminals and are one of the leading causes of cyber espionage and sabotage. A large number of sophisticated malware attacks as well as advanced persistent threats (APTs) have been launched on smartphone users. These attacks are becoming significantly more complex, sophisticated, persistent, and undetected for extended periods. Traditionally, devices are targeted by exploiting a vulnerability in the operating system (OS) or device sensors. Nevertheless, there is a rise in APTs, side-channel attacks, sensor-based attacks, and attacks launched through the Google Play Store. Previous research contributions have lacked contemporary threats, and some have proven ineffective against the latest variants of the mobile operating system. In this paper, we conducted an extensive survey of papers over the last 15 years (2009–2023), covering vulnerabilities, contemporary threats, and corresponding defenses. The research highlights APTs, classifies malware variants, defines how sensors are exploited, visualizes multiple ways that side-channel attacks are launched, and provides a comprehensive list of malware families that spread through the Google Play Store. In addition, the research provides details on threat defense solutions, such as malware detection tools and techniques presented in the last decade. Finally, it highlights open issues and identifies the research gap that needs to be addressed to meet the challenges of next-generation smartphones.

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“…According to our finding F8, there are more than 19,000 device models in our dataset. Such a fragmentation brings significant challenges to software engineering practices for mobile apps, such as app design, development, maintenance, quality assurance, and revenue generation [45], [46], [47], [48]. A recent study [49] (in 2013) showed that 94% of mobile-app developers who avoid the Android platform cite fragmentation as the main reason.…”

Section: Addressing Device-specific Featuresmentioning

confidence: 99%

Characterizing Smartphone Usage Patterns from Millions of Android Users

Lü

Liu

et al. 2015

Proceedings of the 2015 Internet Measurement Conference

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The prevalence of smart mobile devices has promoted the popularity of mobile applications (a.k.a. apps). Supporting mobility has become a promising trend in software engineering research. This article presents an empirical study of behavioral service profiles collected from millions of users whose devices are deployed with Wandoujia, a leading Android app-store service in China. The dataset of Wandoujia service profiles consists of two kinds of user behavioral data from using 0.28 million free Android apps, including (1) app management activities (i.e., downloading, updating, and uninstalling apps) from over 17 million unique users and (2) app network usage from over 6 million unique users. We explore multiple aspects of such behavioral data and present patterns of app usage. Based on the findings as well as derived knowledge, we also suggest some new open opportunities and challenges that can be explored by the research community, including app development, deployment, delivery, revenue, etc.Index Terms-mobile apps, app store, user behavior analysis !

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Fragmentation Problem in Android

Cited by 16 publications

References 0 publications

Using Combinatorial Approaches for Testing Mobile Applications

Using Combinatorial Approaches for Testing Mobile Applications

Smartphone Security and Privacy: A Survey on APTs, Sensor-Based Attacks, Side-Channel Attacks, Google Play Attacks, and Defenses

Characterizing Smartphone Usage Patterns from Millions of Android Users

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