Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105476
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dc.contributorDepartment of Computing-
dc.creatorTang, Y-
dc.creatorWang, H-
dc.creatorZhan, X-
dc.creatorLuo, X-
dc.creatorZhou, Y-
dc.creatorZhou, H-
dc.creatorYan, Q-
dc.creatorSui, Y-
dc.creatorKeung, J-
dc.date.accessioned2024-04-15T07:34:35Z-
dc.date.available2024-04-15T07:34:35Z-
dc.identifier.issn0098-5589-
dc.identifier.urihttp://hdl.handle.net/10397/105476-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Y. Tang et al., "A Systematical Study on Application Performance Management Libraries for Apps," in IEEE Transactions on Software Engineering, vol. 48, no. 8, pp. 3044-3065, 1 Aug. 2022 is available at https://doi.org/10.1109/TSE.2021.3077654.en_US
dc.subjectAndroiden_US
dc.subjectApplication performance managementen_US
dc.subjectEmpirical studyen_US
dc.titleA systematical study on application performance management libraries for appsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage3044-
dc.identifier.epage3065-
dc.identifier.volume48-
dc.identifier.issue8-
dc.identifier.doi10.1109/TSE.2021.3077654-
dcterms.abstractBeing able to automatically detect the performance issues in apps can significantly improve apps’ quality as well as having a positive influence on user satisfaction. A pplication P erformance M anagement (APM) libraries are used to locate the apps’ performance bottleneck, monitor their behaviors at runtime, and identify potential security risks. Although app developers have been exploiting application performance management (APM) tools to capture these potential performance issues, most of them do not fully understand the internals of these APM tools and the effect on their apps. To fill this gap, in this paper, we conduct the first systematic study on APMs for apps by scrutinizing 25 widely-used APMs for Android apps and develop a framework named APMHunter for exploring the usage of APMs in Android apps. Using APMHunter, we conduct a large-scale empirical study on 500,000 Android apps to explore the usage patterns of APMs and discover the potential misuses of APMs. We obtain two major findings: 1) some APMs still employ deprecated permissions and approaches, which makes APMs fail to perform as expected; 2) inappropriate use of APMs can cause privacy leaks. Thus, our study suggests that both APM vendors and developers should design and use APMs scrupulously.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on software engineering, Aug. 2022, v. 48, no. 8, p. 3044-3065-
dcterms.isPartOfIEEE transactions on software engineering-
dcterms.issued2021-
dc.identifier.scopus2-s2.0-85105889105-
dc.identifier.eissn1939-3520-
dc.description.validate202402 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCOMP-0118en_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextShanghaiTech Start-up Research; CityU; National Natural Science Foundation of China; Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang; Central Universitiesen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS53487470en_US
dc.description.oaCategoryGreen (AAM)en_US
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