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Handling non-canonical software requirements based on Annotated Predicate Calculus

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Abstract

Eliciting requirements for a proposed system inevitably involves the problem of handling undesirable information about customer's needs, including inconsistency, vagueness, redundancy, or incompleteness. We term the requirements statements involved in the undesirable information non-canonical software requirements. In this paper, we propose an approach to handling non-canonical software requirements based on Annotated Predicate Calculus (APC). Informally, by defining a special belief lattice appropriate for representing the stakeholder's belief in requirements statements, we construct a new form of APC to formalize requirements specifications. We then show how the APC can be employed to characterize non-canonical requirements. Finally, we show how the approach can be used to handle non-canonical requirements through a case study.

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Authors and Affiliations

  1. School of Mathematical Sciences, Peking University, Beijing, 100871, P.R. China

    Kedian Mu & Yan Peng

  2. Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, 100080, P.R. China

    Zhi Jin & Ruqian Lu

Authors
  1. Kedian Mu
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  2. Zhi Jin
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  3. Ruqian Lu
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  4. Yan Peng
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Corresponding author

Correspondence to Kedian Mu.

Additional information

Kedian Mu received B.Sc. degree in applied mathematics from Beijing Institute of Technology, Beijing, China, in 1997, M.Sc. degree in probability and mathematical statistics from Beijing Institute of Technology, Beijing, China, in 2000, and Ph.D. in applied mathematics from Peking University, Beijing, China, in 2003. From 2003 to 2005, he was a postdoctoral researcher at Institute of Computing Technology, Chinese Academy of Sciences, China. He is currently an assistant professor at School of Mathematical Sciences, Peking University, Beijing, China. His research interests include uncertain reasoning in artificial intelligence, knowledge engineering and science, and requirements engineering.

Zhi Jin was awarded B.Sc. in computer science from Zhejiang University, Hangzhou, China, in 1984, and studied for her M.Sc. in computer science (expert system) and her Ph.D. in computer science (artificial intelligence) at National Defence University of Technology, Changsha, China. She was awarded Ph.D. in 1992. She is a senior member of China Computer Federation. She is currently a professor at Academy of Mathematics and System Sciences, Chinese Academy of Science. Her research interests include knowledge-based systems, artificial intelligence, requirements engineering, ontology engineering, etc. Her current research focuses on ontology-based requirements elicitation and analysis. She has got about 60 papers published, including co-authoring one book.

Ruqian Lu is a professor of computer science of the Institute of Mathematics, Chinese Academy of Sciences. His research interests include artificial intelligence, knowledge engineering and knowledge based software engineering. He designed the “Tian Ma” software systems that have been widely applied in more than 20 fields, including the national defense and the economy. He has won two first class awards from Chinese Academy of Sciences and a National second class prize from the Ministry of Science and Technology. He has also won the sixth Hua Lookeng Prize for Mathematics.

Yan Peng received B.Sc. degree in software from Jilin University, Changchun, China, in 1992. From June 2002 to December 2005, he studied for his M.E. in software engineering at College of Software Engineering, Graduate School of Chinese Academy of Sciences, Beijing, China. He was awarded M.E degree in 2006. He is currently responsible for CRM (customer relationship management) and BI (business intelligence) project in the BONG. His research interests include customer relationship management, business intelligence, data ming, software engineering and requirements engineering.

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Mu, K., Jin, Z., Lu, R. et al. Handling non-canonical software requirements based on Annotated Predicate Calculus. Knowl Inf Syst 11, 85–104 (2007). https://doi.org/10.1007/s10115-006-0021-y

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  • DOI: https://doi.org/10.1007/s10115-006-0021-y

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