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| Content Provider | ACM Digital Library |
|---|---|
| Author | Zhang, Xiangyu Sumner, William N. Xin, Bin |
| Abstract | Execution indexing uniquely identifies a point in an execution. Desirable execution indices reveal correlations between points in an execution and establish correspondence between points across multiple executions. Therefore, execution indexing is essential for a wide variety of dynamic program analyses, for example, it can be used to organize program profiles; it can precisely identify the point in a re-execution that corresponds to a given point in an original execution and thus facilitate debugging or dynamic instrumentation. In this paper, we formally define the concept of execution index and propose an indexing scheme based on execution structure and program state. We present a highly optimized online implementation of the technique. We also perform a client study, which targets producing a failure inducing schedule for a data race by verifying the two alternative happens-before orderings of a racing pair. Indexing is used to precisely locate corresponding points across multiple executions in the presence of non-determinism so that no heavyweight tracing/replay system is needed. |
| Starting Page | 238 |
| Ending Page | 248 |
| Page Count | 11 |
| File Format | |
| ISSN | 03621340 15581160 |
| DOI | 10.1145/1379022.1375611 |
| Journal | ACM SIGPLAN Notices (SIGP) |
| Volume Number | 43 |
| Issue Number | 6 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1983-05-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Execution alignment Control dependence Execution indexing Data race Structural indexing Semantic augmentation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Graphics and Computer-Aided Design Software |
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