Name
Abstract | ||
|---|---|---|
We aim to detect and diagnose code misbehavior that wastes energy, which we call energy bugs. This paper describes a method and implementation, called Carat, for performing such diagnosis on mobile devices. Carat takes a collaborative, black-box approach. A non-invasive client app sends intermittent, coarse-grained measurements to a server, which identifies correlations between higher expected energy use and client properties like the running apps, device model, and operating system. Carat successfully detected all energy bugs in a controlled experiment and, during a deployment to 883 users, identified 5434 instances of apps exhibiting buggy behavior in the wild. |
Year | Venue | Keywords |
|---|---|---|
2012 | HotDep | controlled experiment,device model,black-box approach,coarse-grained measurement,client property,mobile device,energy bug,non-invasive client app,diagnose code misbehavior,buggy behavior,higher expected energy use,collaborative energy |
Field | DocType | Citations |
Carat,Software deployment,Computer science,Mobile device,Controlled experiment,Operating system,Embedded system,Debugging | Conference | 19 |
PageRank | References | Authors |
1.10 | 23 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adam J. Oliner | 1 | 715 | 51.10 |
| Anand Iyer | 2 | 108 | 6.67 |
| Eemil Lagerspetz | 3 | 427 | 29.56 |
| Sasu Tarkoma | 4 | 1312 | 125.76 |
| I. Stoica | 5 | 21406 | 1710.11 |