Fault Localization via Augmented Combinatorial Test Case Generation
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Solution Overview
Problem
Combinatorial Test Design (CTD) methods require additional processing power for test generation and fault localization after a bug is discovered, as tests are generated post-bug detection, leading to inefficiencies in identifying fault-causing attribute-value pairs.
Innovation Solution
A computer-implemented method that generates and augments test cases by locating missing counterparts for attribute-value pairs, modifying test cases to act as counterparts, and adding them to the set, while ensuring compliance with predefined constraints, to identify faults in a system under test.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If test cases are generated after bug discovery using CTD, then fault localization capability is improved, but processing power and time consumption increase
Solution Approach 1:
The patent applies preliminary action by generating counterpart test cases in advance before bug discovery. The system creates a comprehensive test suite including both original and counterpart test cases, so that when a bug is found, the fault localization can immediately utilize the pre-generated counterpart cases without requiring additional processing power for test generation.
2Measurement precision
If additional test cases are generated for fault localization, then fault identification accuracy is improved, but test execution time increases
Solution Approach 1:
The patent applies local quality by selectively generating counterpart test cases only for specific attribute-value pairs that are suspected of causing the bug, rather than generating all possible test cases. This targeted approach improves fault identification accuracy for the specific faulty region while minimizing the overall test execution time by focusing resources locally on the problematic area.
3Reliability
If comprehensive test coverage is achieved through CTD, then bug detection capability is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the test suite into original test cases and counterpart test cases, where each counterpart is specifically designed to isolate and test particular attribute-value pairs. This segmentation allows comprehensive bug detection capability while managing complexity by organizing tests into logical groups with specific purposes, making the overall test suite more structured and maintainable.
Data Source
AI summary
A computer-implemented method, in accordance with one embodiment, includes generating a set of test cases for a system under test (SUT). The set of test cases is augmented by locating a missing counterpart for a first combination of values in a first test case based on identifying a number of instances of the first combination of values in the set of test cases, generating a new test case based on modifying the first test case to act as the missing counterpart, determining whether the new test case violates a constraint from a set of predefined constraints, in response to determining that the new test case violates the constraint, modifying at least one of the values in the new test case, and adding the modified new test case to the set of test cases. A fault for the SUT is identified based on executing the augmented set of test cases.