Using abduction and induction for operational requirements elaboration

作     者：Alrajeh, D. Ray, O. Russo, A. Uchitel, S. 

作者机构：Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England Univ Bristol Dept Comp Sci Bristol BS8 1UB Avon England Univ Buenos Aires Dept Computac RA-2160 Buenos Aires DF Argentina 

出 版 物：《JOURNAL OF APPLIED LOGIC》 (应用逻辑学杂志)

年 卷 期：2009年第7卷第3期

页      面：275-288页

核心收录：

学科分类：01[哲学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Saudi Arabian Ministry of Higher Education Seventh Framework Programme, FP7, (204853) Engineering and Physical Sciences Research Council, EPSRC, (PBM C541133/1, UBACyT X020) Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET Agencia Nacional de Promoción Científica y Tecnológica, ANPCyT, (11738, 32440) 

主　　题：Inductive logic programming Abductive reasoning Goal-oriented requirements engineering Scenario-based specification Linear temporal logic Event Calculus 

摘      要：Requirements Engineering involves the elicitation of high-level stakeholder goals and their refinement into operational system requirements. A key difficulty is that stakeholders typically convey their goals indirectly through intuitive narrative-style scenarios of desirable and undesirable system behaviour, whereas goal refinement methods usually require goals to be expressed declaratively using, for instance, a temporal logic. In actual software engineering practice, the extraction of formal requirements from scenario-based descriptions is a tedious and error-prone process that would benefit from automated tool support. This paper presents an Inductive Logic Programming method for inferring operational requirements from a set of example scenarios and an initial but incomplete requirements specification. The approach is based on translating the specification and the scenarios into an event-based logic programming formalism and using a non-monotonic reasoning system, called eXtended Hybrid Abductive Inductive Learning, to automatically infer a set of event pre-conditions and trigger-conditions that cover all desirable scenarios and reject all undesirable ones. This learning task is a novel application of logic programming to requirements engineering that also demonstrates the utility of non-monotonic learning capturing pre-conditions and trigger-conditions. (C) 2008 Elsevier B.V. All rights reserved.