rules represent a simplified means of programming, congruent with our understanding of human brain constructs. With the advent of business rules management systems, it has been possible to introduce rule-based program...
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ISBN:
(数字)9783642400377
ISBN:
(纸本)9783642400377;9783642400384
rules represent a simplified means of programming, congruent with our understanding of human brain constructs. With the advent of business rules management systems, it has been possible to introduce rule-based programming to nonprogrammers, allowing them to map expert intent into code in applications such as fraud detection, financial transactions, healthcare, retail, and marketing. However, a remaining concern is the quality, safety, and reliability of the resulting programs. This book is on business rules programs, that is, rule programs as handled in business rules management systems. Its conceptual contribution is to present the foundation for treating business rules as a topic of scientific investigation in semantics and program verification, while its technical contribution is to present an approach to the formal verification of business rules programs. The author proposes a method for proving correctness properties for a business rules program in a compositional way, meaning that the proof of a correctness property for a program is built up from correctness properties for the individual rulesthus bridging a gap between the intuitive understanding of rules and the formal semantics of rule programs. With this approach the author enables rule authors and tool developers to understand, express formally, and prove properties of the execution behavior of business rules programs. This work will be of interest to practitioners and researchers in the areas ofprogram verification,enterprise computing, database management, and artificial intelligence.
The modeling language ML-rules allows specifying and simulating complex systems biology models at multiple levels of organization. The development of such simulation models involves a wide variety of simulation experi...
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The modeling language ML-rules allows specifying and simulating complex systems biology models at multiple levels of organization. The development of such simulation models involves a wide variety of simulation experiments and the replicability of generated simulation results requires suitable means for documenting simulation experiments. Embedded domain-specific languages, such as SESSL, cater to both requirements. With SESSL, the user can integrate diverse simulation experimentation methods and third-party software components into an executable, readable simulation experiment specification. A newly developed SESSL binding for ML-rules exploits these features of SESSL, opening up new possibilities for executing and documenting simulation experiments with ML-rules models.
rule-based programming experiences renaissance due to its applications in areas such as Business rules, Semantic Web, Computational Biology, Verification and Security. Executable rules are used in declarative programm...
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ISBN:
(纸本)9781595933881
rule-based programming experiences renaissance due to its applications in areas such as Business rules, Semantic Web, Computational Biology, Verification and Security. Executable rules are used in declarative programming languages, in program transformation and analysis, and for reasoning in artificial intelligence *** Handling rules (CHR) [6, 8, 11] is a concurrent committed-choice constraint logic programming language consisting of guarded rules that transform multi-sets of atomic formulas (constraints) into simpler ones until exhaustion. CHR was initially developed for solving constraints, but has matured into a general-purpose concurrent constraint language over the last decade, because it can embed many rule-based formalisms and describe algorithms in a declarative way. The clean semantics of CHR facilitates non-trivial program analysis and transformation
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