Executable Code Abnormality Detection via Automated Test Replay
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Solution Overview
Problem
Manual monkey tests for executable code are time-consuming and labor-intensive, making it difficult to reproduce specific combinations of actions that result in abnormalities, as traditional approaches rely on screen recorder tools that are inefficient and hard to distinguish by video.
Innovation Solution
An automated system for generating test code that detects user-activatable control elements, generates first and second test codes based on these elements, and saves instructions to recreate abnormalities, allowing for efficient identification of issues in executable code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monkey tests are performed by users, then the executable code can be tested for abnormalities, but the testing process becomes time-consuming and labor-intensive
Solution Approach 1:
The system enables self-service testing by automatically generating and executing test codes that simulate user operations. The test code generator creates automated test sequences based on control element detection, eliminating the need for manual user intervention while maintaining comprehensive abnormality detection capabilities.
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational processes. Instead of manual user interactions, the system uses computer-generated test codes that automatically navigate control elements, click buttons, and execute operations to detect abnormalities in the executable code.
2Loss of information
If traditional screen recorder tools are used to capture test actions, then the testing process can be recorded, but the reproduction of specific action combinations becomes difficult and time-consuming
Solution Approach 1:
The system performs preliminary action by pre-generating and storing test codes that capture the sequence of operations. When an abnormality is detected, the corresponding pre-recorded test code can be immediately replayed to reproduce the scenario, eliminating the need to review lengthy screen recordings from scratch.
Solution Approach 2:
The patent creates a digital copy of the test action sequence in the form of executable test codes. These codes serve as precise replicas of the operations that led to abnormalities, allowing for exact reproduction and analysis without manually reviewing the original test session recordings.
3Reliability
If manual testing is performed, then the user can operate controls randomly to find abnormalities, but it becomes difficult to distinguish and analyze specific action combinations
Solution Approach 1:
The system segments the complex testing process into discrete, identifiable units by detecting and categorizing individual control elements. Each control element (buttons, fields, menus) is separately identified and tracked, allowing the system to segment and analyze specific action combinations that lead to abnormalities in a structured manner.
Solution Approach 2:
The patent implements feedback mechanisms that track and record the state of control elements during testing. When abnormalities occur, the system provides feedback by recording the specific sequence of actions that preceded them, enabling detailed analysis of which control element combinations triggered the abnormal behavior.
Data Source
AI summary
Executable code abnormality detection can include detecting user-activatable control elements of an executable code to be tested, generating a first test code based on the detected user-activatable control elements, and generating a second test code based on a script for the executable code to be tested, wherein the first and the second test codes containing instructions executable by a test application to test the executable code. Further, executable code abnormality detection can include executing the first test code and the second test code using the test application, and in response to the test application detecting an abnormality, saving instructions from the executed first test code and the executed second test code into a persistent file to allow replay of the abnormality.