Detecting system use cases and validations from documents

Identifying system use cases and corresponding validations involves analyzing large requirement documents to understand the descriptions of business processes, rules and policies. This consumes a significant amount of effort and time. We discuss an approach to automate the detection of system use cases and corresponding validations from documents. We have devised a representation that allows for capturing the essence of rule statements as a composition of atomic `Rule intents' and key phrases associated with the intents. Rule intents that co-occur frequently constitute `Rule acts' analogous to the Speech acts in Linguistics. Our approach is based on NLP techniques designed around this Rule Model. We employ syntactic and semantic NL analyses around the model to identify and classify rules and annotate them with Rule acts. We map the Rule acts to business process steps and highlight the combinations as potential system use cases and validations for human supervision.

[1]  Jane Cleland-Huang,et al.  Automated classification of non-functional requirements , 2007, Requirements Engineering.

[2]  Gerhard Knolmayer,et al.  The specification of business rules: A comparison of selected methodologies , 1994, Methods and Associated Tools for the Information Systems Life Cycle.

[3]  S. Ali,et al.  Rule extraction methodology by using XML for business rules documentation , 2005, INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics, 2005..

[4]  Annie I. Antón,et al.  Mining rule semantics to understand legislative compliance , 2005, WPES '05.

[5]  Daniela Rosca,et al.  A decision making methodology in support of the business rules lifecycle , 1997, Proceedings of ISRE '97: 3rd IEEE International Symposium on Requirements Engineering.

[6]  Hafedh Mili,et al.  Agile Business Rule Development , 2011 .

[7]  Richard C. Waters,et al.  Challenges to the field of reverse engineering , 1993, [1993] Proceedings Working Conference on Reverse Engineering.

[8]  Tao Xie,et al.  Inferring method specifications from natural language API descriptions , 2012, 2012 34th International Conference on Software Engineering (ICSE).

[9]  Stefano Ceri,et al.  Designing Database Applications with Objects and Rules: The IDEA Methodology , 1997 .

[10]  Tao Xie,et al.  Automated extraction of security policies from natural-language software documents , 2012, SIGSOFT FSE.

[11]  Ellen Gottesdiener.  Business RULES Show Power, Promise , 1997 .

[12]  Steffen Staab,et al.  Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text , 2004, ECAI.

[13]  Nirav Ajmeri,et al.  A semantic and collaborative platform for agile requirements evolution , 2010, 2010 Third International Workshop on Managing Requirements Knowledge.

[14]  Martijn Zoet,et al.  European Conference on Information Systems ( ECIS ) 10-6-2011 ALIGNMENT OF BUSINESS PROCESS MANAGEMENT AND BUSINESS RULES , 2011 .

[15]  Alistair Cockburn,et al.  Writing Effective Use Cases , 2000 .

[16]  Hafedh Mili,et al.  Agile Business Rule Development - Process, Architecture, and JRules Examples , 2011 .

[17]  Marc Moens,et al.  Sentence extraction and rhetorical classification for flexible abstracts , 1998 .

[18]  Ronald G. Ross,et al.  The Business Rule Book: Classifying, Defining and Modeling Rules , 1997 .

[19]  Soumya Ghosh,et al.  Decision Making Methodology , 2013 .

[20]  Fawzy A. Torkey,et al.  A Text Mining Technique Using Association Rules Extraction , 2008 .

[21]  Eric SanJuan,et al.  Annotation of Scientific Summaries for Information Retrieval , 2011, ESAIR 2011.