Dynamic Logger Code Insertion via Confidence Scoring
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Solution Overview
Problem
Developers face challenges in managing logger source code segments in source code development platforms, as unnecessary logger code segments incur execution costs, while failing to insert them when needed can hinder error detection.
Innovation Solution
A computer-implemented method identifies primary code segments, determines a confidence score, and inserts or removes logger code segments based on whether the score exceeds a confidence threshold, using indicators like use frequency, modification frequency, user confidence, and failure response to dynamically determine logger code segment necessity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If logger source code segments are inserted into all code segments, then error detection capability is improved, but execution efficiency deteriorates due to unnecessary logger code segments
Solution Approach 1:
The system dynamically changes the parameter of logger code segment presence based on confidence scores. Code segments are selectively instrumented with logger code only when the confidence score indicates high probability of containing bugs, thereby maintaining error detection capability while reducing unnecessary execution overhead in confident code segments
Solution Approach 2:
The system implements dynamic decision-making for logger code insertion by evaluating confidence scores at runtime or during analysis. This dynamic approach allows the system to adaptively determine which code segments need logging, transitioning from a static all-or-nothing approach to a dynamic selective approach that optimizes both error detection and execution efficiency
2Productivity
If logger source code segments are removed to improve execution efficiency, then error detection capability deteriorates
Solution Approach 1:
The system uses confidence scores as a parameter to determine logger code presence. By changing the parameter state based on confidence thresholds, the system removes logger code from segments with high confidence (low bug probability) while retaining it in segments with low confidence (high bug probability), thus optimizing execution efficiency without sacrificing error detection capability
3Adaptability or versatility
If manual management of logger source code segments is used, then flexibility is improved, but device complexity and user effort increase
Solution Approach 1:
The system enables self-service by automatically analyzing code segments, calculating confidence scores, and making decisions about logger code insertion and removal. This automated self-service approach maintains flexibility in logger management while eliminating the need for manual user intervention, thereby reducing user effort and complexity
Solution Approach 2:
The system implements feedback mechanisms by using confidence scores derived from code analysis to automatically adjust logger code placement. This closed-loop feedback system continuously evaluates code segments and adapts logger instrumentation accordingly, providing flexible and adaptive logger management without requiring complex manual configuration or user effort
Data Source
AI summary
A computer-implemented method includes identifying a primary code segment, determining a confidence score associated with said primary code segment, and determining whether the confidence score exceeds a confidence threshold. The computer-implemented method further includes responsive to the confidence score exceeding the confidence threshold, determining a logger code segment associated with the primary code segment. A corresponding computer program product and computer system are also disclosed.