Memory Leak Detection via Heap Segmentation and Isolation
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Solution Overview
Problem
Current methods for analyzing memory leaks in production systems are inadequate, as they often require expensive tools, alter application behavior, consume memory, or necessitate server restarts, making it difficult to detect and isolate memory leaks in ongoing execution.
Innovation Solution
A method and service that recursively divide memory sections experiencing abnormal conditions into smaller logical sections, isolate the source of the issue, and reallocate memory, allowing for remote monitoring and management without affecting system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If memory leak analysis tools are used in production systems, then memory leaks can be detected, but system performance degrades and operations are disrupted
Solution Approach 1:
The patent segments the heap memory into multiple isolated sections, each monitored independently. This allows the system to detect memory leaks in specific sections without requiring full-system analysis tools that would degrade overall performance. The segmentation enables localized monitoring that maintains productivity while achieving detection accuracy.
Solution Approach 2:
The patent introduces memory isolation sections as intermediary structures between the application and the monitoring system. These isolation sections act as mediators that capture memory allocation data without requiring direct instrumentation of the application code, thus avoiding performance degradation while maintaining detection capability.
2Measurement precision
If expensive memory analysis tools are used, then memory leaks can be detected, but costs increase
Solution Approach 1:
The patent implements a self-service monitoring mechanism where the system automatically tracks memory allocation within isolated sections using lightweight metadata. This eliminates the need for expensive external analysis tools by providing built-in detection capability that achieves accuracy without high costs.
Solution Approach 2:
The patent uses lightweight, disposable metadata structures to track memory allocation in each isolation section. These cheap tracking structures are created and discarded as needed, providing effective memory leak detection without requiring expensive persistent analysis tools.
3Measurement precision
If memory analysis alters application behavior, then memory leaks can be detected, but the application's original behavior changes
Solution Approach 1:
The patent extracts memory monitoring functionality from the application code itself by using operating system-level memory isolation features. This extraction allows detection of memory leaks without inserting instrumentation code that would alter application behavior, maintaining behavioral consistency while achieving detection accuracy.
4Measurement precision
If server restarts are performed to analyze memory leaks, then the source can be identified, but operations are disrupted
Solution Approach 1:
The patent enables continuous memory monitoring within isolated heap sections during production operation. By maintaining monitoring continuity without requiring system restarts, the system can identify memory leak sources while operations continue uninterrupted, eliminating operational downtime while achieving source identification.
Data Source
AI summary
A computerized method, program product, and a service that allocates and isolates leaky memory during the execution of an application in a data processing system. A memory controller having several components first identifies a leaky section of memory and delegates to an allocation component to allocate more memory if possible. If, however, the problematic memory section should not be allocated more memory, an isolator component can isolate the memory section and further divide the memory section into subsections and so on. Each section and each subsection may then be tested to determine if more memory can be allocated, tested to determine if memory resources are strained so as to identify the application or its component causing the strain and then binding the memory. Each section and subsection and further divided and isolated until the leaky portion of memory is identified, and as a result, the software component causing the leak can also be identified. The software component associated with the leaky memory section or subsection can also be taken out-of-service.