Fuzzy Evaluation of Domain Knowledge

Software engineering utilizes selected knowledge sources from which the fundamental concepts for the software solution can be extracted. The quality of the adopted knowledge sources intrinsically defines the quality of the software solution. This quality of knowledge sources is, on the one hand, determined by its objectivity value, and on the other hand, by its relevance value for the given problem. Since the relevance and objectivity values may change due to newly generated knowledge or evolving requirements, crisp decisions in accepting or rejecting the knowledge sources will result in an inappropriate evaluation. We propose to apply fuzzy reasoning in which knowledge sources are assigned fuzzy linguistic quality values to express the quality degrees. This provides a more precise evaluation and can better cope with the evolution of the knowledge sources and the corresponding software requirements. We describe the validation of our proposal with an experimental case study on the evaluation of domain knowledge for the design of transaction systems.

[1]  Bedir Tekinerdogan,et al.  Design of an object-oriented framework for atomic transactions , 2001 .

[2]  Dimitar P. Filev,et al.  Fuzzy SETS AND FUZZY LOGIC , 1996 .

[3]  Robert L. Glass,et al.  Contemporary Application-Domain Taxonomies , 1995, IEEE Softw..

[4]  A SimosMark.  Organization domain modeling (ODM) , 1995 .

[5]  E. B. Moss,et al.  Nested Transactions: An Approach to Reliable Distributed Computing , 1985 .

[6]  Bedir Tekinerdogan,et al.  Synthesis - Based Software Architecture Design , 2001 .

[7]  Siegfried Gottwald,et al.  Fuzzy Sets and Fuzzy Logic , 1993 .

[8]  Steven Wartik,et al.  Criteria for Comparing Domain Analysis Approaches Version 01.00.00 , 1991 .

[9]  Walter H. Kohler,et al.  A Survey of Techniques for Synchronization and Recovery in Decentralized Computer Systems , 1981, CSUR.

[10]  Guillermo Arango,et al.  Domain Analysis and Software Systems Modeling , 1991 .

[11]  Alain Abran,et al.  The Guide to the Software Engineering Body of Knowledge , 1999, IEEE Softw..

[12]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[13]  Stéphane Bressan,et al.  Introduction to Database Systems , 2005 .

[14]  Robert J. Stroud,et al.  The design and implementation of a distributed transaction system based on atomic data types , 1995, Distributed Syst. Eng..

[15]  Philip A. Bernstein,et al.  Principles of Transaction Processing , 1996 .

[16]  Francesco Marcelloni,et al.  Deferring elimination of design alternatives in object‐oriented methods , 2001, Concurr. Comput. Pract. Exp..

[17]  Ruben Prieto-Diaz,et al.  Criteria for Comparing Reuse-Oriented Domain Analysis Approaches , 1992, Int. J. Softw. Eng. Knowl. Eng..

[18]  Gail E. Kaiser,et al.  Concurrency control in advanced database applications , 1991, CSUR.

[19]  J CareyMichael,et al.  Concurrency control performance modeling: alternatives and implications , 1987 .

[20]  Butler W. Lampson,et al.  Atomic Transactions , 1980, Advanced Course: Distributed Systems.

[21]  M. Stella Atkins,et al.  Adaptable concurrency control for atomic data types , 1992, TOCS.

[22]  Krzysztof Czarnecki,et al.  Generative Programming , 2001, ECOOP Workshops.