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| Content Provider | ACM Digital Library |
|---|---|
| Author | McDaniel, Patrick Jha, Somesh Octeau, Damien |
| Abstract | The Android OS has emerged as the leading platform for SmartPhone applications. However, because Android applications are compiled from Java source into platform-specific Dalvik bytecode, existing program analysis tools cannot be used to evaluate their behavior. This paper develops and evaluates algorithms for retargeting Android applications received from markets to Java class files. The resulting Dare tool uses a new intermediate representation to enable fast and accurate retargeting. Dare further applies strong constraint solving to infer typing information and translates the 257 DVM opcodes using only 9 translation rules. It also handles cases where the input Dalvik bytecode is unverifiable. We evaluate Dare on 1,100 of the top applications found in the free section of the Android market and successfully retarget 99.99% of the 262,110 associated classes. Further, whereas existing tools can only fully retarget about half of these applications, Dare can recover over 99% of them. In this way, we open the door to users, developers and markets to use the vast array of program analysis tools to ensure the correct operation of Android applications. |
| Starting Page | 1 |
| Ending Page | 11 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781450316149 |
| DOI | 10.1145/2393596.2393600 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-11-11 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Dalvik bytecode Dalvik retargeting Android |
| Content Type | Text |
| Resource Type | Article |
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