Epigenetic Test Case Constraint Control for Software Failure Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional software test case generation methods focus on improving coverage but fail to consider various constraints such as timing, scheduling, hardware environment, and external interference, limiting their effectiveness in detecting software failures under actual operating conditions.
Innovation Solution
A test case constraint control technology based on epigenetics, utilizing a genetic modification mechanism similar to methylation and acetylation for constraint regulation, including on/off, enhancement/attenuation, and genetic/non-genetic operations, to dynamically and reversibly control constraints, thereby generating test cases that better reflect actual software operation conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional test case generation methods are used to improve coverage, then the coverage of test cases is improved, but the ability to detect software failures under actual operating constraints deteriorates
Solution Approach 1:
The patent applies dynamics by making test case constraints adjustable and reversible through epigenetic mechanisms. Constraints can be dynamically added, removed, enhanced, or attenuated during test case generation, allowing the system to adapt to different operating conditions rather than using fixed constraints throughout the testing process
Solution Approach 2:
The patent changes parameters by introducing epigenetic markers that modify constraint parameters without altering the underlying program code. These markers enable continuous adjustment of constraint strength and applicability, transforming static test constraints into dynamically可调 parameters that reflect real-world operating variations
2Productivity
If test automation is implemented to reduce costs and time, then productivity is improved, but the ability to handle complex constraints deteriorates
Solution Approach 1:
The patent introduces epigenetic markers as intermediary elements between the test case generation system and constraints. These markers act as mediators that automatically manage constraint application, allowing the automated system to handle complex constraints without manual intervention while maintaining adaptability through the marker-based control mechanism
Solution Approach 2:
The system performs self-service by automatically generating and managing epigenetic markers that control constraint application. The test case generation process autonomously adjusts constraints based on epigenetic information without requiring external manual configuration, maintaining both automation efficiency and constraint adaptability
Data Source
AI summary
A construction method of a test case constraint control technology based on epigenetics includes steps of: 1: defining a fitness function, a genetic coding method, and a constraint control rule; 2: initializing parameters: setting a population size, an evolution number, and a termination fitness function value; 3: initializing a population: randomly generating an initial population; 4: performing evolution termination judgment; 5. performing constraint regulation based on the epigenetics: performing constraint methylation and constraint acetylation according to the constraint control rule; 6: selecting individuals; 7: completing epigenetic evolution of the population; and 8: outputting a test case set; wherein through the above steps, construction of an epigenetic test case constraint control technology is completed, so as to design test cases that are more in line with the actual operation conditions of the software, find more potential software failures, and improve the quality of software testing.