For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Improving Natural Language Requirements Quality Using Workflow Patterns
Ye WANG Xiaohu YANG Cheng CHANG Alexander J. KAVS
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2013/09/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Software Engineering
requirements analysis, correctness, consistency, workflow patterns, pattern matching,
Full Text: PDF(4.1MB)
>>Buy this Article
Natural language (NL) requirements are usually human-centric and therefore error-prone and inaccurate. In order to improve the 3Cs of natural language requirements, namely Consistency, Correctness and Completeness, in this paper we propose a systematic pattern matching approach supporting both NL requirements modeling and inconsistency, incorrectness and incompleteness analysis among requirements. We first use business process modeling language to model NL requirements and then develop a formal language — Workflow Patterns-based Process Language (WPPL) — to formalize NL requirements. We leverage workflow patterns to perform two-level 3Cs checking on the formal representation based on a coherent set of checking rules. Our approach is illustrated through a real world financial service example — Global Equity Trading System (GETS).