Reverse Debugging Source Code Causal Analysis
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Solution Overview
Problem
Software developers face challenges in determining the execution path of source code that leads to a bug, as current debugging methods rely on manual trace statements and stack traces, which do not provide a complete execution path.
Innovation Solution
A method and apparatus for reverse debugging source code using causal analysis, where byte-code execution data is collected and analyzed to determine the execution path, with a graphical user interface for displaying execution data and allowing users to step back through the code to identify errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual trace statements are used to track execution path, then debugging information can be obtained, but the debugging process requires considerable time and manual effort
Solution Approach 1:
The system performs preliminary actions by automatically inserting trace statements into source code before the debugging session begins. These trace statements are pre-positioned at strategic locations to capture execution path information, variable states, and control flow data without requiring manual intervention during the actual debugging process.
Solution Approach 2:
The debugging system performs self-service by automatically generating, inserting, and analyzing trace statements without continuous manual input. The system autonomously executes the program, collects execution data, reconstructs the control flow graph, and presents debugging information, thereby eliminating the need for developers to manually place and interpret trace statements.
2Loss of information
If stack traces are used to retrieve execution information, then currently executing routine information can be obtained, but the complete execution path from the beginning of program execution cannot be revealed
Solution Approach 1:
The system transitions from the traditional single-dimension stack trace (which only shows current call stack) to a multi-dimensional execution path reconstruction. It creates a control flow graph that spans multiple dimensions: temporal (execution sequence), spatial (code locations), and contextual (variable states), thereby revealing the complete execution path from program start to the current breakpoint.
Solution Approach 2:
The system introduces an intermediary component - the control flow graph reconstruction module - that bridges the gap between limited stack trace information and complete execution path knowledge. This intermediary collects data from multiple sources (stack frames, trace statements, program counter), processes it through causal analysis, and synthesizes a comprehensive execution history that includes both current and past execution states.
3Measurement precision
If developers manually determine the actual path of execution, then debugging accuracy can be maintained, but the process requires considerable time and effort
Solution Approach 1:
The system implements feedback mechanisms where execution data is continuously collected and analyzed, then fed back to update the control flow graph and provide debugging information. The trace statements provide feedback about actual execution paths, variable modifications, and control flow decisions, allowing the system to accurately reconstruct the execution history and present precise debugging information to the developer.
Solution Approach 2:
The system replaces the mechanical manual process of tracing execution paths with an automated computational system. Instead of developers manually following code paths and tracking variable changes, the system uses automated program analysis, control flow graph construction, and causal reasoning algorithms to determine execution paths and present debugging information, thereby maintaining accuracy while dramatically improving efficiency.
Data Source
AI summary
A method and apparatus for reverse debugging source code using causal analysis is disclosed. The method comprises executing byte-code created from a plurality of lines of source code, wherein the plurality of lines of source code comprise at least one breakpoint; storing execution data after execution of each line of source code in the plurality of lines of source code until execution reaches the at least one breakpoint; performing a code execution analysis using the execution data and the plurality of lines of source code; receiving an input via a graphical user interface (GUI), wherein the input requests specific execution details based on the code execution analysis; and responding via the GUI to the input.