A model-based diagnostics toolset that given a set of inconsistent rules (policies) finds the minimal inconsistent subset(s) of it. There are two example cases in the current repository:
- Case1.py: Input: a set of integers; Diagnostic Function: a set of integers with no common factor is inconsistent
- Case2.py: Input: a provenance graph, a set of integrity rules for a valid graph, a set of customization rules for sanitizing the graph stated as a set of DLV rules. Diagnostic Function: a set of customization rules violating one (or more) integrity rule is inconsistent.
Usage: diagFunc.py -d [diagnostics function] -i [input file]
- example case1. python diagFunc.py -d gcd.has_common_prime
- example case 2. python diagFunc.py -d prob.diag -i ur.dlv