Calling-context profiles and dynamic metrics at the bytecode level are important for profiling, workload characterization, program comprehension, and reverse engineering. Prevailing tools for collecting calling-context profiles or dynamic bytecode metrics often provide only incomplete information or suffer from limited compatibility with standard JVMs. However, completeness and accuracy of the profiles is essential for tasks such as workload characterization, and compatibility with standard JVMs is important to ensure that complex workloads can be executed. In this paper, we present the design and implementation of JP2, a new tool that profiles both the inter- and intra-procedural control flow of workloads on standard JVMs. JP2 produces calling-context profiles preserving callsite information, as well as execution statistics at the level of individual basic blocks of code. JP2 is complemented with scripts that compute various dynamic bytecode metrics from the profiles. As a case-study and tutorial on the use of JP2, we use it for crossprofiling for an embedded Java processor.
|Title of host publication||Proceedings of the 9th International Conference on the Principles and Practice of Programming in Java (PPPJ 2011)|
|Publication status||Published - 2011|
|Event||9th International Conference on the Principles and Practice of Programming in Java - Kongens Lyngby, Denmark|
Duration: 24 Aug 2011 → 26 Aug 2011
Conference number: 9
|Conference||9th International Conference on the Principles and Practice of Programming in Java|
|Period||24/08/2011 → 26/08/2011|
Bibliographical note© ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in PPPJ 2011.
- Java Virtual Machine
- Bytecode instrumentation
- Calling Context Tree