Fault Localization in Declarative Specification Languages
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Solution Overview
Problem
Existing fault localization techniques for declarative specification languages are slow and inaccurate, limiting confidence and feasibility in analyzing large complex models.
Innovation Solution
A method using a partial max satisfiability solver to find a satisfying instance close to a counterexample, analyzing differences between the counterexample and the satisfying instance to compute suspicion scores for expressions in the model, and presenting these scores for fault localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing fault localization techniques (unit tests, mutation testing, statistical debugging) are used for declarative specification languages, then fault localization can be performed, but the process becomes slow and inaccurate
Solution Approach 1:
The patent replaces traditional mechanical debugging approaches (unit tests, mutation testing, statistical debugging) with a satisfaction-based analytical system that uses logical solvers to automatically identify faults in declarative specifications, achieving both speed and accuracy improvements
Solution Approach 2:
The system changes the fundamental parameter of fault localization from trial-based testing to satisfaction-based logical analysis, transforming the approach from iterative experimental methods to direct computational solving that simultaneously improves accuracy and reduces time
2Reliability
If traditional fault localization techniques are applied to large complex models in declarative specification languages, then analysis can be performed, but confidence in results and feasibility are limited
Solution Approach 1:
The patent replaces unreliable traditional testing mechanisms with a rigorous satisfaction-based logical analysis system that provides deterministic results even for large complex models, thereby increasing confidence and feasibility
Solution Approach 2:
The system performs preliminary satisfaction checking and counterexample generation before full analysis, allowing early identification of issues in complex models and building confidence progressively through systematic verification steps
Data Source
AI summary
In accordance with some embodiments, systems, methods, and media for fault localization in declarative specification languages are provided. In some embodiments, a method comprises: receiving a model in a declarative specification language; querying an automated analysis of the declarative specification language for a counterexample, wherein the counterexample is an instance of the model that does not satisfy a property; using a partial max satisfiability solver to find an instance that satisfies the property; determining one or more differences in an expression from the model between the counterexample and the satisfying instance; analyzing the differences between the counterexample and the satisfying instance; determining a suspicion score for the expression in the model; and causing the suspicion score to be presented.


