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On mobile phones, users and developers use apps official marketplaces servingas repositories of apps. The Google Play Store and Apple Store are the officialmarketplaces of Android and Apple products which offer more than a millionapps. Although both repositories offer description of apps, informationconcerning performance is not available. Due to the constrained hardware ofmobile devices, users and developers have to meticulously manage the resourcesavailable and they should be given access to performance information aboutapps. Even if this information was available, the selection of apps would stilldepend on user preferences and it would require a huge cognitive effort to makeoptimal decisions. Considering this fact we propose APOA, a recommendationsystem which can be implemented in any marketplace for helping users anddevelopers to compare apps in terms of performance.  APOA uses as input metric values of apps and a set of metrics to optimize. Itsolves an optimization problem and it generates optimal sets of apps fordifferent user's context. We show how APOA works over an Android case study.Out of 140 apps, we define typical usage scenarios and we collect measurementsof power, CPU, memory, and network usages to demonstrate the benefit of usingAPOA.

An App Performance Optimization Advisor for Mobile Device App Marketplaces