Studying the characteristics of logging practices in mobile apps: a case study on F-Droid.
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| Title: | Studying the characteristics of logging practices in mobile apps: a case study on F-Droid. |
|---|---|
| Authors: | Zeng, Yi1 ze_yi@encs.concordia.ca, Chen, Jinfu1, Shang, Weiyi1, Chen, Tse-Hsun (Peter)1 |
| Source: | Empirical Software Engineering. Dec2019, Vol. 24 Issue 6, p3394-3434. 41p. |
| Subjects: | Application logging (Computer science), Mobile apps, Computer software, Information retrieval, Software engineering |
| Abstract: | Logging is a common practice in software engineering. Prior research has investigated the characteristics of logging practices in system software (e.g., web servers or databases) as well as desktop applications. However, despite the popularity of mobile apps, little is known about their logging practices. In this paper, we sought to study logging practices in mobile apps. In particular, we conduct a case study on 1,444 open source Android apps in the F-Droid repository. Through a quantitative study, we find that although mobile app logging is less pervasive than server and desktop applications, logging is leveraged in almost all studied apps. However, we find that there exist considerable differences between the logging practices of mobile apps and the logging practices in server and desktop applications observed by prior studies. In order to further understand such differences, we conduct a firehouse email interview and a qualitative annotation on the rationale of using logs in mobile app development. By comparing the logging level of each logging statement with developers' rationale of using the logs, we find that all too often (35.4%), the chosen logging level and the rationale are inconsistent. Such inconsistency may prevent the useful runtime information to be recorded or may generate unnecessary logs that may cause performance overhead. Finally, to understand the magnitude of such performance overhead, we conduct a performance evaluation between generating all the logs and not generating any logs in eight mobile apps. In general, we observe a statistically significant performance overhead based on various performance metrics (response time, CPU and battery consumption). In addition, we find that if the performance overhead of logging is significantly observed in an app, disabling the unnecessary logs indeed provides a statistically significant performance improvement. Our results show the need for a systematic guidance and automated tool support to assist in mobile logging practices. [ABSTRACT FROM AUTHOR] |
| Copyright of Empirical Software Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 140205786 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Studying the characteristics of logging practices in mobile apps: a case study on F-Droid. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zeng%2C+Yi%22">Zeng, Yi</searchLink><relatesTo>1</relatesTo><i> ze_yi@encs.concordia.ca</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Jinfu%22">Chen, Jinfu</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shang%2C+Weiyi%22">Shang, Weiyi</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Tse-Hsun+%28Peter%29%22">Chen, Tse-Hsun (Peter)</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Empirical+Software+Engineering%22">Empirical Software Engineering</searchLink>. Dec2019, Vol. 24 Issue 6, p3394-3434. 41p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Application+logging+%28Computer+science%29%22">Application logging (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+apps%22">Mobile apps</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Logging is a common practice in software engineering. Prior research has investigated the characteristics of logging practices in system software (e.g., web servers or databases) as well as desktop applications. However, despite the popularity of mobile apps, little is known about their logging practices. In this paper, we sought to study logging practices in mobile apps. In particular, we conduct a case study on 1,444 open source Android apps in the F-Droid repository. Through a quantitative study, we find that although mobile app logging is less pervasive than server and desktop applications, logging is leveraged in almost all studied apps. However, we find that there exist considerable differences between the logging practices of mobile apps and the logging practices in server and desktop applications observed by prior studies. In order to further understand such differences, we conduct a firehouse email interview and a qualitative annotation on the rationale of using logs in mobile app development. By comparing the logging level of each logging statement with developers' rationale of using the logs, we find that all too often (35.4%), the chosen logging level and the rationale are inconsistent. Such inconsistency may prevent the useful runtime information to be recorded or may generate unnecessary logs that may cause performance overhead. Finally, to understand the magnitude of such performance overhead, we conduct a performance evaluation between generating all the logs and not generating any logs in eight mobile apps. In general, we observe a statistically significant performance overhead based on various performance metrics (response time, CPU and battery consumption). In addition, we find that if the performance overhead of logging is significantly observed in an app, disabling the unnecessary logs indeed provides a statistically significant performance improvement. Our results show the need for a systematic guidance and automated tool support to assist in mobile logging practices. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Empirical Software Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10664-019-09687-9 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 41 StartPage: 3394 Subjects: – SubjectFull: Application logging (Computer science) Type: general – SubjectFull: Mobile apps Type: general – SubjectFull: Computer software Type: general – SubjectFull: Information retrieval Type: general – SubjectFull: Software engineering Type: general Titles: – TitleFull: Studying the characteristics of logging practices in mobile apps: a case study on F-Droid. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zeng, Yi – PersonEntity: Name: NameFull: Chen, Jinfu – PersonEntity: Name: NameFull: Shang, Weiyi – PersonEntity: Name: NameFull: Chen, Tse-Hsun (Peter) IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 13823256 Numbering: – Type: volume Value: 24 – Type: issue Value: 6 Titles: – TitleFull: Empirical Software Engineering Type: main |
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