Efficient heap monitoring tool for memory leak detection and root-cause analysis

Memory leaks are of serious concern in software programs written in languages that do not have a dedicated garbage collector. Memory leaks are the result of prolonged unnecessary usage of the system memory resources. This increases the workload, paging, and lowers the response rate leading to performance degradation of the system or software. Such leaks are difficult to detect due to a software’s development testing span and different working environments.This research paper proposes an algorithm to detect memory leaks based on the growth analysis of the memory blocks. The proposed method captures the allocation made in memory blocks via malloc, calloc, and realloc and stores the captured results onto the files. The files are then analyzed using the leak threshold determined by the developer or tester. Unlike other approaches such as ASAN/LSAN which require multiple snapshots to analyze the leaks, the proposed method works without a snapshot for the summary analysis algorithm and only requires one snapshot, collected at the end of the execution. This approach does not need to be integrated within the application to analyze the software and detect memory leaks. Our method provides more accurate results by visualizing the captured and analyzed data for the developers, making it more convenient to detect the root cause of the leakage.