Abstract: Approaches presented herein enable optimizing a hierarchical rule-based decision policy. An initial domain of values for each decision of a ruleset is extracted. Using the initial domain of values and a hierarchical structure of the ruleset, a reduced domain of values for each decision is computed starting from the lowest level decision. Each of the reduced domain of values upwards in the hierarchical structure is propagated upwards. A completeness and consistency analysis for each decision is then performed based on the propagation to identify any missing and/or arbitration rules for the policy.

Abstract: A method for domain specific language design includes, with a physical computing system, receiving from a user, a number of annotations for at least one of a set of statements within a problem domain, the annotations identifying a set of elements within the statement. The method further includes forming a set of grammar rules for the problem domain based on the annotations, and parsing the set of statements using the set of grammar rules.

Abstract: A computing system includes a processor; and a memory communicatively coupled to the processor. The processor is configured to: receive from a user, a number of annotations for at least one of a set of statements within a problem domain, the annotations identifying a set of elements within the statement; form a set of grammar rules for the problem domain based on the annotations; and parse the set of statements using the set of grammar rules.

Abstract: Embodiments relate to managing and executing interpreted language code. An aspect includes a parser configured to parse controlled language code against both a language grammar and for building an execution model comprising parsed known concepts. Another aspect includes a pattern matching engine configured to match patterns in the controlled language code with a patterns for a new concept. Yet another aspect includes a concept engine configured to create a new concept from the matched pattern and controlled language code and for saving the new concept into an object model and into a language grammar so that current and future parsing errors will not occur when recognizing the new concept.

Abstract: Embodiments relate to validating logical statements in code for domain specific languages. An aspect includes parsing logical statements and annotating constraint type logical statements with specific constraint annotations from the logical grammar of the domain specific language. A non-contradiction graph is built using specific constraint annotations constrained to represent cases satisfying the logical statements and is solved to find a case that satisfies the logical statement or prove that no such case exists, thus locating a contradiction. The non-contradiction graph is negated to form a non-tautology graph constrained to represent cases violating the logical statements and the non-tautology graph is solved to find a case that violates the logical statement or prove that no such case exists, thus locating a tautology. A report is provided regarding at least one case satisfying the logical statement and at least one case violating the logical statement whereby the logical statement is validated.

Abstract: Embodiments relate to managing and executing interpreted language code. An aspect includes a parser configured to parse controlled language code against both a language grammar and for building an execution model comprising parsed known concepts. Another aspect includes a pattern matching engine configured to match patterns in the controlled language code with a patterns for a new concept. Yet another aspect includes a concept engine configured to create a new concept from the matched pattern and controlled language code and for saving the new concept into an object model and into a language grammar so that current and future parsing errors will not occur when recognizing the new concept.

Abstract: Embodiments relate to validating logical statements in code for domain specific languages. An aspect includes parsing logical statements and annotating constraint type logical statements with specific constraint annotations from the logical grammar of the domain specific language. A non-contradiction graph is built using specific constraint annotations constrained to represent cases satisfying the logical statements and is solved to find a case that satisfies the logical statement or prove that no such case exists, thus locating a contradiction. The non-contradiction graph is negated to form a non-tautology graph constrained to represent cases violating the logical statements and the non-tautology graph is solved to find a case that violates the logical statement or prove that no such case exists, thus locating a tautology. A report is provided regarding at least one case satisfying the logical statement and at least one case violating the logical statement whereby the logical statement is validated.

Abstract: A computing system includes a processor; and a memory communicatively coupled to the processor. The processor is configured to: receive from a user, a number of annotations for at least one of a set of statements within a problem domain, the annotations identifying a set of elements within the statement; form a set of grammar rules for the problem domain based on the annotations; and parse the set of statements using the set of grammar rules.

Abstract: A method for domain specific language design includes, with a physical computing system, receiving from a user, a number of annotations for at least one of a set of statements within a problem domain, the annotations identifying a set of elements within the statement. The method further includes forming a set of grammar rules for the problem domain based on the annotations, and parsing the set of statements using the set of grammar rules.