Correlating Macro and Error Data for Debugging
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Solution Overview
Problem
Reproducing and analyzing error events in application execution is challenging due to the difficulty in recreating specific user actions and contexts that lead to errors, making it hard to debug and test applications effectively.
Innovation Solution
Generating and storing macro data and error data during program execution, including user interface tasks and error events with corresponding timestamps, to correlate and recreate the sequence of events leading to an error, enabling the generation of test cases for debugging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is logged during application execution to reproduce error events, then the ability to analyze error events is improved, but the complexity of data management and correlation increases
Solution Approach 1:
The patent segments error event data into distinct components: macro data (user interface tasks with timestamps), error data (failure entries with timestamps), and relationship data (correlations between them). This segmentation allows each component to be managed independently, reducing overall data management complexity while maintaining comprehensive error analysis capability.
Solution Approach 2:
The patent introduces relationship data as an intermediary element that connects macro data and error data. This intermediary contains timestamp-based correlations that link specific user interface tasks to error events, enabling automated error reproduction without requiring complex manual data correlation processes.
2Measurement precision
If detailed execution data is collected to recreate error scenarios, then debugging accuracy is improved, but the amount of data to be processed and stored increases
Solution Approach 1:
The patent extracts only the essential elements needed for error reproduction: timestamps, user interface task identifiers, and error event identifiers. By taking out only these critical data points rather than logging complete execution states, the system maintains high debugging accuracy while significantly reducing data volume.
Solution Approach 2:
The patent performs preliminary correlation of macro data and error data during application execution, creating relationship data that pre-establishes the connections between user actions and errors. This preliminary action eliminates the need to process and analyze large volumes of raw execution data later, reducing overall data processing requirements.
Data Source
AI summary
A solution for managing a program execution is provided. During execution of a program, macro data and error data can be generated and stored. The macro data includes a set of execution entries, each of which includes data for a user interface task for a user interface object and a time for the user interface task. The error data, if any, includes a set of failure entries, each of which includes data for an error event and a time for the error event. A failure entry can be subsequently correlated with at least one execution entry based on the corresponding times. Further, relationship data and/or the like can be used to generate a test case, which can enable the user interface tasks that led up to the error event to be recreated.