Memory Leak Detection via Same-Sized Chunk Statistics
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Solution Overview
Problem
Dynamic memory allocation systems face challenges in detecting memory leaks, particularly in long-running systems where allocated memory is not released, leading to resource wastage and potential system instability.
Innovation Solution
A method and system that generate and monitor statistical information about allocated memory chunks, intercepting standard memory allocation and deallocation calls to identify potential memory leaks by tracking chunk counts over time and generating alerts when predetermined thresholds are exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If memory allocation is performed without monitoring, then memory resources are distributed efficiently, but memory leaks cannot be detected leading to resource wastage and system instability
Solution Approach 1:
The system performs preliminary actions by generating statistical information about memory chunk allocations before memory leaks cause system instability. The monitoring mechanism proactively tracks allocation patterns and identifies potential leaks early, preventing resource wastage and maintaining system reliability without requiring complex post-mortem analysis
Solution Approach 2:
The invention implements feedback by continuously monitoring statistical information about memory chunk allocations and comparing it against thresholds. When allocation patterns deviate from expected behavior, the system generates alerts that provide feedback to administrators, enabling timely intervention to maintain system stability while using a relatively simple monitoring architecture
2Measurement precision
If statistical monitoring of all memory chunks is implemented, then memory leaks are detected accurately, but system overhead and processing time increase
Solution Approach 1:
The system segments the memory monitoring task by focusing statistical analysis on same-sized memory chunks rather than tracking every individual allocation. This segmentation approach maintains detection accuracy for memory leaks while significantly reducing the computational overhead and processing time required to analyze memory allocation patterns
Solution Approach 2:
The invention applies partial monitoring by generating statistical information only for same-sized memory chunks rather than comprehensively tracking all memory allocations. This partial action approach provides sufficient precision to detect memory leaks while minimizing system overhead and processing time requirements
3Reliability
If alert thresholds are set low for sensitive detection, then memory leaks are identified early, but false alerts increase reducing system reliability
Solution Approach 1:
The system employs dynamic threshold management by adjusting alert thresholds based on the specific characteristics of memory chunk allocations and observed patterns. This dynamic approach allows the system to maintain high sensitivity for detecting genuine memory leaks while adapting to normal allocation variations, thereby reducing false alerts and preserving detection reliability
Solution Approach 2:
The invention changes parameters by adjusting alert thresholds based on statistical analysis of memory chunk allocation patterns. Rather than using fixed low thresholds that generate false alerts, the system dynamically modifies threshold parameters according to observed allocation behavior, enabling early detection of memory leaks while minimizing false positive rates
Data Source
AI summary
A method to detect memory leaks during dynamic memory allocation comprises generating statistical information regarding allocated chunks in a memory heap during a dynamic memory allocation process, with the statistical information including same-sized chunk information related to the number of allocated chunks being identical in size. The statistical information is monitored to identify a potential memory leak based at least in part on the same-sized chunk information, in response to which an alert signal is generated.