Writing effective business rules :
Witt, Graham C.
Writing effective business rules : a practical method / Graham Witt. - Waltham, Mass. : Morgan Kaufmann/Elsevier, 2012. - xx, 340 p. : ill. ; 23 cm.
Includes bibliographical references (p. 303-304) and index.
The world of rules -- How rules work -- A brief history of rules -- Types of rules -- The building blocks of natural language rule statements -- Fact models -- How to write quality natural language rule statements -- An end-to-end rule management methodology -- Rule statement templates and subtemplates.
Writing Effective Business Rules moves beyond the fundamental dilemma of system design: defining business rules either in natural language, intelligible but often ambiguous, or program code (or rule engine instructions), unambiguous but unintelligible to stakeholders. Designed to meet the needs of business analysts, this book provides an exhaustive analysis of rule types and a set of syntactic templates from which unambiguous natural language rule statements of each type can be generated. A user guide to the SBVR [Semantics of Business Vocabulary and Business Rules] specification, it explains how to develop an appropriate business vocabulary and generate quality rule statements using the appropriate templates and terms from the vocabulary. The resulting rule statements can be reviewed by business stakeholders for relevance and correctness, providing for a high level of confidence in their successful implementation. A complete set of standard templates for rule statements and their component syntactic elements A rigorous approach to rule statement construction to avoid ambiguity and ensure consistency. A clear explanation of the way in which a fact model provides and constrains the rule statement vocabulary A practical reader-friendly user guide to the those parts of the SBVR specification that are relevant to rule authoring--
9780123850515
2011277627
015959177 Uk
Semantic computing.
Rule-based programming.
Data structures (Computer science)
Natural language processing (Computer science)
Electronic data processing.
QA 76.5913 / .W58 2012
Writing effective business rules : a practical method / Graham Witt. - Waltham, Mass. : Morgan Kaufmann/Elsevier, 2012. - xx, 340 p. : ill. ; 23 cm.
Includes bibliographical references (p. 303-304) and index.
The world of rules -- How rules work -- A brief history of rules -- Types of rules -- The building blocks of natural language rule statements -- Fact models -- How to write quality natural language rule statements -- An end-to-end rule management methodology -- Rule statement templates and subtemplates.
Writing Effective Business Rules moves beyond the fundamental dilemma of system design: defining business rules either in natural language, intelligible but often ambiguous, or program code (or rule engine instructions), unambiguous but unintelligible to stakeholders. Designed to meet the needs of business analysts, this book provides an exhaustive analysis of rule types and a set of syntactic templates from which unambiguous natural language rule statements of each type can be generated. A user guide to the SBVR [Semantics of Business Vocabulary and Business Rules] specification, it explains how to develop an appropriate business vocabulary and generate quality rule statements using the appropriate templates and terms from the vocabulary. The resulting rule statements can be reviewed by business stakeholders for relevance and correctness, providing for a high level of confidence in their successful implementation. A complete set of standard templates for rule statements and their component syntactic elements A rigorous approach to rule statement construction to avoid ambiguity and ensure consistency. A clear explanation of the way in which a fact model provides and constrains the rule statement vocabulary A practical reader-friendly user guide to the those parts of the SBVR specification that are relevant to rule authoring--
9780123850515
2011277627
015959177 Uk
Semantic computing.
Rule-based programming.
Data structures (Computer science)
Natural language processing (Computer science)
Electronic data processing.
QA 76.5913 / .W58 2012