Abstract: A technology is disclosed for estimating the impact that heap memory allocations have on the behavior of garbage collection activities. A sampling mechanism randomly and unbiased selects a subset of allocations for detailed analysis. A detailed analysis is performed for the selected allocation activities. Allocation monitoring data, including type and size of the allocated object and data describing the code location on which the allocation was performed are gathered. Further, the point in time, when the allocated object is later reclaimed by garbage collection is recorded. Gathered object allocation and reclaim data are used to estimate for individual allocation sites or types of allocated objects, the number of bytes that are allocated, and the number of bytes that survived a garbage collection run. Allocation activity causing frequently garbage collection runs is identified using allocation size data and the survived byte counts are used to identify allocation activity causing long garbage collection runs.

Abstract: A system and method for the efficient monitoring of memory allocations performed during the executing code is presented. The proposed approach analyzes the code to build a control flow graph that describes all possible execution sequences of the code. Individual execution paths are identified by an analysis of the control path and memory allocation counters representing the memory allocations of each execution path are placed in the code. The memory allocation counters provide next to data describing memory allocations also execution frequency data of execution paths. The execution frequency data is used to identify the path with the highest execution frequency. The position of the memory allocation counters is further adapted with the optimization goal that the path with the highest execution frequency triggers the least number of memory allocation counter increments.

Abstract: A system and method for the efficient monitoring of memory allocations performed during the executing code is presented. The proposed approach analyzes the code to build a control flow graph that describes all possible execution sequences of the code. Individual execution paths are identified by an analysis of the control path and memory allocation counters representing the memory allocations of each execution path are placed in the code. The memory allocation counters provide next to data describing memory allocations also execution frequency data of execution paths. The execution frequency data is used to identify the path with the highest execution frequency. The position of the memory allocation counters is further adapted with the optimization goal that the path with the highest execution frequency triggers the least number of memory allocation counter increments.