Domain Specific Model Validation via Logic Programming
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Solution Overview
Problem
Model-driven engineering approaches face challenges in balancing the usability of modeling languages with their verifiability, as languages easy for subject matter experts to use are less formal and harder to verify, while formal languages are difficult for experts to interpret.
Innovation Solution
A processor-implemented method and system that translates domain-specific models into machine-interpretable rules and vocabularies, generating logic programming representations to validate models using solution scenarios, with inconsistency checking and conflict resolution, leveraging the Semantics of Business Vocabulary and Business Rules (SBVR) standard and Answer Set Programming (ASP) paradigm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If formal modeling languages are used to improve verifiability, then model correctness can be verified, but usability for subject matter experts deteriorates
Solution Approach 1:
The patent introduces an intermediate modeling layer that translates between informal SME-friendly models and formal verification models. This intermediary translation mechanism allows SMEs to work with intuitive, informal models while automated solvers verify the translated formal representations, resolving the contradiction between usability and verifiability.
Solution Approach 2:
The verification process is segmented into distinct components: an informal model creation phase for SMEs, a translation phase to formal logic, and a verification phase using automated solvers. This segmentation allows each component to be optimized independently - usability in the informal phase and rigor in the verification phase.
2Ease of operation
If informal modeling languages are used to improve usability, then SMEs can easily use the language, but model verifiability deteriorates
Solution Approach 1:
The informal model serves as an intermediary representation that SMEs can create easily, which is then translated into a formal verification model. This intermediary informal model preserves usability while the translation step ensures verifiability is not compromised.
Solution Approach 2:
The system creates a formal copy or translation of the informal model that can be verified automatically. The informal model is copied into a formal representation that maintains the semantic meaning but enables automated verification through logic programming solvers.
Data Source
AI summary
Model driven engineering (MDE) approaches necessitate verification and validation (V&V) of the models used. Balancing usability of modeling languages with verifiability of the specification presents several challenges. Conventional modeling languages have automated solvers but are hard to interpret and use. Implementations of present disclosure provide systems and methods for validating domain specific models wherein rules and vocabularies in domain specific model are translated to machine interpretable rules (MIR) and machine interpretable vocabularies (MIV) which are processed (via logic programming technique) to generate a logic programming representation (LPR) of the MIR and MIV based on which solution scenarios are generated for validating the domain specific model. Validation of the model involves verifying LPR using a set of ground facts. During validation of solution scenarios of model, system also checks for inconsistences in rules, if any. These rules are corrected and solution scenarios are re-generated to obtain anomaly free solution scenarios.