Abstract: In one aspect, a computer implemented method for translating and executing rules using a directed acyclic graph is provided. The method includes transforming a ruleset into a directed acyclic graph. The directed acyclic graph includes a plurality of nodes and a plurality of branches. The method further includes identifying similarities across the plurality of branches. The method further includes grouping branches of the directed acyclic graph based on the identified similarities. The method further includes creating a modified directed acyclic graph based on the grouping. The method further includes selecting and using a method of processing a group of the modified directed acyclic graph based on an aspect of the group.

Abstract: In one aspect, a computer implemented method for translating and executing rules using a directed acyclic graph is provided. The method includes transforming a ruleset into a directed acyclic graph. The directed acyclic graph includes a plurality of nodes and a plurality of branches. The method further includes identifying similarities across the plurality of branches. The method further includes grouping branches of the directed acyclic graph based on the identified similarities. The method further includes creating a modified directed acyclic graph based on the grouping. The method further includes selecting and using a method of processing a group of the modified directed acyclic graph based on an aspect of the group.

Abstract: In one aspect, a computer implemented method for efficient value lookup in a set of scalar intervals is provided. The method includes determining, in response to a query for a scalar value, that the scalar value is located in a set of scalar intervals, wherein each of the scalar intervals comprises a left bound and a right bound. The method further includes sorting the scalar intervals based on left bounds. The method further includes comparing, in response to the sorting, a pair of scalar intervals to determine if the pair of scalar intervals overlaps. The method further includes identifying, based on the comparing indicating that the pair overlaps, a method of processing the scalar intervals.

Abstract: In one aspect, a computer implemented method for efficient value lookup in a set of scalar intervals is provided. The method includes determining, in response to a query for a scalar value, that the scalar value is located in a set of scalar intervals, wherein each of the scalar intervals comprises a left bound and a right bound. The method further includes sorting the scalar intervals based on left bounds. The method further includes comparing, in response to the sorting, a pair of scalar intervals to determine if the pair of scalar intervals overlaps. The method further includes identifying, based on the comparing indicating that the pair overlaps, a method of processing the scalar intervals.

Abstract: In one aspect, a computer implemented method for translating and executing rules using a directed acyclic graph is provided. The method includes transforming a ruleset into a directed acyclic graph. The directed acyclic graph includes a plurality of nodes and a plurality of branches. The method further includes identifying similarities across the plurality of branches. The method further includes grouping branches of the directed acyclic graph based on the identified similarities. The method further includes creating a modified directed acyclic graph based on the grouping. The method further includes selecting and using a method of processing a group of the modified directed acyclic graph based on an aspect of the group.

Abstract: Data is received that characterizes a score model. Thereafter, the score model is normalized by transforming it into a directed acyclic graph. The directed acyclic graph is then transformed into a structured rules language program. The structured rules language program is then transformed into a program using a concurrent, class-based, object-oriented computer programming language (e.g., JAVA, C, COBOL, etc.). Related apparatus, systems, techniques and articles are also described.

Abstract: Data is received that characterizes a score model. Thereafter, the score model is normalized by transforming it into a directed acyclic graph. The directed acyclic graph is then transformed into a structured rules language program. The structured rules language program is then transformed into a program using a concurrent, class-based, object-oriented computer programming language (e.g., JAVA, C, COBOL, etc.). Related apparatus, systems, techniques and articles are also described.

Abstract: Data is received that characterizes a score model. Thereafter, the score model is normalized by transforming it into a directed acyclic graph. The directed acyclic graph is then transformed into a structured rules language program. The structured rules language program is then transformed into a program using a concurrent, class-based, object-oriented computer programming language (e.g., JAVA, C, COBOL, etc.). Related apparatus, systems, techniques and articles are also described.

Abstract: Data is received that characterizes a score model. Thereafter, the score model is normalized by transforming it into a directed acyclic graph. The directed acyclic graph is then transformed into a structured rules language program. The structured rules language program is then transformed into a program using a concurrent, class-based, object-oriented computer programming language (e.g., JAVA, C, COBOL, etc.). Related apparatus, systems, techniques and articles are also described.