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| Content Provider | ACM Digital Library |
|---|---|
| Author | Verbrugge, Clark Dufour, Bruno Driesen, Karel Hendren, Laurie |
| Abstract | In order to perform meaningful experiments in optimizing compilation and run-time system design, researchers usually rely on a suite of benchmark programs of interest to the optimization technique under consideration. Programs are described as numeric, memory-intensive, concurrent, or object-oriented, based on a qualitative appraisal, in some cases with little justification. We believe it is beneficial to quantify the behaviour of programs with a concise and precisely defined set of metrics, in order to make these intuitive notions of program behaviour more concrete and subject to experimental validation. We therefore define and measure a set of unambiguous, dynamic, robust and architecture-independent metrics that can be used to categorize programs according to their dynamic behaviour in five areas: size, data structure, memory use, concurrency, and polymorphism. A framework computing some of these metrics for Java programs is presented along with specific results demonstrating how to use metric data to understand a program's behaviour, and both guide and evaluate compiler optimizations. |
| Starting Page | 149 |
| Ending Page | 168 |
| Page Count | 20 |
| File Format | |
| ISSN | 03621340 15581160 |
| DOI | 10.1145/949343.949320 |
| Journal | ACM SIGPLAN Notices (SIGP) |
| Volume Number | 38 |
| Issue Number | 11 |
| 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 | Java Profiling Software metrics Execution traces Program analysis Optimization Dynamic metrics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Graphics and Computer-Aided Design Software |
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