Characterizing Failures in Mobile OSes: A Case Study with Android and Symbian

Maji, Amiya K.; Hao, Kangli; Sultana, Salmin; Bagchi, Saurabh

doi:10.1109/issre.2010.45

Cited by 63 publications

(30 citation statements)

References 7 publications

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“…This finding confirms that of Kumar Maji et al's [38], who observed a similar distribution of defects in their smaller scale study. In fact, our findings also vindicate our position about the relevance of studying issues in all of the OS's layers, as against a subset of issues [31].…”

Section: Software Architecture (Rq1) (A) How Android Architecture Isssupporting

confidence: 92%

“…1 reveals that far fewer issues were raised in regard to the libraries and Android runtime layers (only 4.8% and 0.3% respectively). These results confirm the findings of the smaller scale study of Kumar Maji et al [38], and justify the need for further investigation of issues as evident in the Android OS application layer.…”

Section: Architecture Issues (Rq1)supporting

confidence: 87%

“…We observed that none of the issues had a Close date, suggesting that, although issues were addressed, developers did not invest effort in updating this field. This pattern was also noted in Kumar Maji et al [38], whose study of 758 Android OS bugs revealed that some fields were not updated regularly. In fact, we observed that only 2,816 issues had the version field updated (out of the total 21,547 issues), while the others were left blank.…”

Section: Research Settingsupporting

confidence: 65%

“…In this work the archival data studied were not originally prepared for the purpose of research, and thus, there were many missing values in the issues studied (refer to Section 3). This issue was observed by previous research that considered subsets of the same data source [38]. Nevertheless, we did not observe any missing text in the description summary field of any of the 21,547 issues that were examined, which formed the core of our analysis.…”

Section: Limitationssupporting

confidence: 56%

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Exploring the Prevalence and Evolution of Android Concerns: A Community Viewpoint

Licorish¹

2016

JSW

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Abstract:In line with growing awareness of the need for systems to adapt quickly to change, there has been increasing interest in the evolution of software systems. Research has particularly considered developer-led activities change over time. Comparatively less consideration has been given to the study of software evolution as driven by the wider community of stakeholders. Although, a project's wider community is central to the feedback system and project success. We have contributed to such efforts and studied the evolution of architecture issues and non-functional requirements in the Android project, as identified by the wider Android community 1 . We mined the Android issues tracker, employing n-gram analysis in our examination of 21,547 issues. We observe that most architecture-related issues were located in Android application layer, and these issues increased with time. Additionally, usability-related concerns were reported most when they were held to be given greatest attention. Outcomes suggests that Android's open model and shared ownership have positively impacted Google's success, which could provide a useful lesson for other similar projects.

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Section: Software Architecture (Rq1) (A) How Android Architecture Isssupporting

confidence: 92%

Section: Architecture Issues (Rq1)supporting

confidence: 87%

Section: Research Settingsupporting

confidence: 65%

Section: Limitationssupporting

confidence: 56%

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Exploring the Prevalence and Evolution of Android Concerns: A Community Viewpoint

Licorish¹

2016

JSW

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“…• Reliability: is a set of attributes which affect the application's ability to maintain its level of performance under stated conditions for a stated period of time [34].…”

Section: Completion Of Systematic Reviewmentioning

confidence: 99%

Estimating the Effort of Mobile Application Development

Souza¹,

Aquino²

2014

Computer Science &Amp; Information Technology ( CS &Amp; IT )

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Charting the API minefield using software telemetry data

2014

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Programs draw significant parts of their functionality through the use of Application Programming Interfaces (APIs). Apart from the way developers incorporate APIs in their software, the stability of these programs depends on the design and implementation of the APIs. In this work, we report how we used software telemetry data to analyze the causes of API failures in Android applications. Specifically, we got 4.9 GB worth of crash data that thousands of applications sent to a centralized crash report management service. We processed that data to extract approximately a million stack traces, stitching together parts of chained exceptions, and established heuristic rules to draw the border between applications and the API calls. We examined a set of more than a half million stack traces associated with risky API calls to map the space of the most common application failure reasons. Our findings show that the top ones can be attributed to memory exhaustion, race conditions or deadlocks, and missing or corrupt resources. Given the classes of the crash causes we identified, we recommend API design and implementation choices, such as specific exceptions, default resources, and non-blocking algorithms, that can eliminate common failures. In addition, we argue that development tools like memory analyzers, thread debuggers, and static analyzers can prevent crashes through early code testing and analysis. Finally, some execution platform and framework designs for process and memory management can also eliminate some application crashes.

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Characterizing Failures in Mobile OSes: A Case Study with Android and Symbian

Cited by 63 publications

References 7 publications

Exploring the Prevalence and Evolution of Android Concerns: A Community Viewpoint

Exploring the Prevalence and Evolution of Android Concerns: A Community Viewpoint

Estimating the Effort of Mobile Application Development

Charting the API minefield using software telemetry data

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