| Title: |
SPARSE: A Symptom-based Antipattern Retrieval Knowledge-based System Using Semantic Web Technologies |
| Author(s): |
D. Settas, G. Meditskos, I. Stamelos, N. Bassiliades.
|
| Availability: |
|
| Keywords: |
Antipatterns, Symptom-based retrieval, OWL ontology, Production rules, Objects.
|
| Appeared in: |
Expert Systems with Applications, Elsevier, 38(6), pp. 7633-7646, 2011.
|
| Abstract: |
Antipatterns provide information on commonly occurring solutions to problems that generate negative consequences. The number of software project management antipatterns that appears in the literature and the Web increases to the extent that makes using antipatterns problematic. Furthermore, antipatterns are usually inter-related and rarely appear in isolation. As a result, detecting which antipatterns exist in a software project is a challenging task which requires expert knowledge. This paper proposes SPARSE, an OWL ontology based knowledge-based system that aims to assist software project managers in the antipattern detection process. The antipattern ontology documents antipatterns and how they are related with other antipatterns through their causes, symptoms and consequences. The semantic relationships that derive from the antipattern definitions are determined using the Pellet DL reasoner and they are transformed into the COOL language of the CLIPS production rule engine. The purpose of this transformation is to create a compact representation of the antipattern knowledge, enabling a set of object-oriented CLIPS production rules to run and retrieve antipatterns relevant to some initial symptoms. SPARSE is exemplified through 31 OWL ontology antipattern instances of software development antipatterns that appear on the Web. |
| See also : |
|
This paper has been cited by the following:
| 1 |
Neill, C.J., “Antipatterns in systems engineering: An opening trio”, (2012) 22nd Annual International Symposium of the International Council on Systems Engineering, INCOSE 2012 and the 8th Biennial European Systems Engineering Conference 2012, EuSEC 2012, 2, pp. 1336-1348. |
| 2 |
Naouel Moha, Francis Palma, Mathieu Nayrolles, Benjamin Joyen Conseil, Yann-Gael Gueheneuc, Benoit Baudry, and Jean-Marc Jezequel, “Specification and Detection of SOA Antipatterns”, 10th International Conference on Service Oriented Computing (ICSOC 2012), November 12-16, Shanghai, China, 2012. |
| 3 |
Rabia Bashirm “Anti-patterns in Open Source Software Development”, International Journal of Computer Applications (0975 – 8887) Volume 44– No.3, April 2012, pp. 23-30. |
| 4 |
SHENG Jin-fang. HU Pci-pei, WANG Bin, “Survey of research on anti-pattern detection”, Application Research of Computers, Vol.30 No. 12, Dec. 2013 |
| 5 |
Francis Palma, Mathieu Nayrolles, Naouel Moha, Yann-Gaël Guéhéneuc, Benoit Baudry, Jean-Marc Jézéquel: Soa Antipatterns: an Approach for their Specification and Detection. Int. J. Cooperative Inf. Syst. 22(4) (2013) |
| 6 |
Mathieu Nayrolles, Naouel Moha, Petko Valtchev, "Improving SOA antipatterns detection in Service Based Systems by mining execution traces," 2013 20th Working Conference on Reverse Engineering (WCRE), pp. 321-330, 2013 20th Working Conference on Reverse Engineering (WCRE), 2013. |
| 7 |
Elena Navarro, Carlos E. Cuesta, Dewayne E Perry, and Pasqual Gonzales, "Antipatterns for Architectural Knowledge Management", International Journal of Information Technology & Decision Making, 12:3 (May 2013), pp. 547 - 589. |
| 8 |
Palma, F., Moha, N., Tremblay, G., Guéhéneuc, Y.-G., “Specification and detection of SOA antipatterns in web services”, (2014) Lecture Notes in Computer Science (including subseries Lecture Notes in Artifi-cial Intelligence and Lecture Notes in Bioinformatics), 8627 LNCS, pp. 58-73. |
|
