Debug Session Tree Recorder for Software Root Cause Analysis
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Solution Overview
Problem
Software debugging processes are inefficient and time-consuming, as they often rely on manual exploration of log files and key traces, lacking automation and reuse of debugging knowledge across sessions.
Innovation Solution
A method that records debug actions and metadata from initial sessions, generates a generic decision tree, and automatically applies these steps to identify root causes in subsequent sessions, leveraging log file accesses and key traces to create a reusable playbook for debugging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual debugging processes are used to explore log files and key traces, then debugging can be performed with simple tools, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by recording debug actions, results, and metadata during initial debugging sessions to create a generic decision tree. This pre-computed knowledge structure enables automated playback and root cause identification in subsequent sessions, eliminating the need for manual exploration and significantly reducing debugging time while maintaining high efficiency.
2Adaptability or versatility
If experienced developers perform manual debugging, then complex problems can be solved, but the process cannot be easily replicated by less skilled analysts
Solution Approach 1:
The system copies the debugging knowledge and decision-making process of experienced developers into a generic decision tree structure. By recording and genericizing debug actions, results, and metadata from expert sessions, the system creates a reusable playbook that can be automatically played back for similar problems, enabling less skilled analysts to achieve expert-level debugging results without manual skill transfer.
3Reliability
If debugging knowledge is captured from each session, then future debugging can be improved, but the complexity of managing and reusing this knowledge increases
Solution Approach 1:
The system creates a universal generic decision tree that serves multiple debugging scenarios. By genericizing debug actions and results into a standardized tree structure with nodes representing files and branches representing debug paths, the system enables one decision tree to handle multiple similar debugging problems across different sessions. This universal structure simplifies knowledge management while maintaining high reliability in root cause identification.
Data Source
AI summary
Specific example debugging sessions are used to generate a generic decision tree (flow diagram) for use in future debugging sessions. Debug metadata is recorded for each debugging session. The debug metadata includes log file accesses and key traces. A generic decision tree is generated for use in future debugging sessions. Each file accessed by a developer during debug sessions creates a node in the generic decision tree. Branches of the decision tree are created between the nodes by aggregating the plurality of debug sessions together based on similarities and differences among the file accesses and results for the various debug sessions. The recorded metadata is genericized by identifying specific actions taken by developers and specific results thereof. The actions and results are abstracted to create more general types of actions and results such that the generic decision tree is applicable to a wider variety of problems in the software program.