Diagnostic Tracing Identifies Suspicious Pointer Values
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Solution Overview
Problem
Diagnostic tracing of executing applications faces challenges in identifying erroneous values at memory addresses, which are crucial for debugging and performance analysis, as existing methods lack efficient mechanisms to track changes and highlight suspicious pointers in trace data.
Innovation Solution
The solution involves a method that uses delta core data to identify changes in memory content over time, allowing for the determination of erroneous values and highlighting suspicious pointers in trace entries, by comparing actual values against declared data types and ranges, and utilizing delta core data to track changes in memory content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional diagnostic tracing methods are used to identify erroneous values in memory, then comprehensive memory analysis can be performed, but the process is time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by capturing base core data and generating delta core data at predetermined trace points during application execution. This allows the diagnostic system to have memory snapshots ready in advance, enabling rapid comparison and identification of erroneous values without time-consuming analysis when problems occur.
Solution Approach 2:
The system creates copies of memory data at different points in time (base core data and delta core data). By comparing these copied data sets, the system can efficiently identify changes and erroneous values without analyzing the entire memory space from scratch, significantly improving debugging efficiency.
2Measurement precision
If delta core data is used to track memory changes efficiently, then suspicious pointers can be identified faster, but the complexity of data processing increases
Solution Approach 1:
The diagnostic process is segmented into distinct phases: capturing base core data at trace points, generating delta core data to represent changes, and comparing these data sets to identify erroneous values. This segmentation allows each component to be optimized independently, improving measurement precision while managing processing complexity through modular organization.
Data Source
AI summary
Arrangements described herein relate to performing diagnostic tracing of an executing application. A trace entry in trace data can be identified, the trace entry comprising a pointer that refers to a memory address. Whether a value that is, or has been, stored at the memory address is an erroneous value can be determined. Responsive to determining that the value that is, or has been, stored at the memory address is an erroneous value, the pointer can be indicated as being a suspicious value.