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Improving software product line using an ontological approach

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Abstract

Software product line (SPL) is an emergent strategy for generating software products. The variability and commonality of SPL is illustrated by feature models (FMs). The quality of software products relies on the correctness of SPL. The overall benefits of software product line engineering (SPLE) are reduced by various kinds of defects such as dead features and false optional features in an FM. These defects can be inherited in the software products built from a defective product line model (PLM). In this paper, the problem of enhancing the quality of software products derived from SPLE is handled. An ontological based approach is proposed following first-order logic (FOL) rules to identify defects namely dead features and false optional features. The classification of cases for these defects in FMs that represent variability of SPL is defined. The presented approach has been explained with the help of an FM derived from the standard case in product line (PL) community. The initial empirical evaluation of the proposed approach analyses 35 FMs with different sizes. The results obtained exhibit that the proposed approach is accurate, effective, scalable up to 200 features and therefore improves SPL.

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References

  1. Clements P and Northrop L 2001 Software product lines: practices and pattern, Addison-Wesley Professional

  2. Bosch J 2002 Maturity and evolution in software product lines: approaches, artefacts and organization. In: Software Product Lines, Lecture Notes in Computer Science, Springer. 257–271. doi:10.1007/3-540-45652-X_16

  3. Kang K C, Cohen S G, Hess J A, Novak W E and Peterson A S 1990 Feature-oriented domain analysis (FODA) feasibility study. Technical Report CMU/SEI-90-TR-21, ESD-90-TR-222, SEI

  4. Elfaki A O, Fong S, Aik K and Johar M M D 2013 Towards detecting redundancy in domain engineering process using first order logic rules. Int. J. Knowl. Eng. Soft Data Paradigms 4(1): 1–20. doi:10.1504/IJKESDP.2013.052716

  5. Elfaki A O, Fong S L, Vijayaprasad P, Johar M G M and Fadhil M S 2014 Using a rule based method for detecting anomalies in software product line. Res. J. Appl. Sci. Eng. Technol. 7(2): 275–281

    Google Scholar 

  6. Elfaki A O, Phon-Amnuaisuk S and Ho C K 2009 Using first order logic to validate feature model. In: Proceedings of the 3rd International Workshop on Variability Modeling of Software-Intensive Systems (VaMoS). pp. 169–172

  7. Elfaki A O 2016 A rule-based approach to detect and prevent inconsistency in the domain-engineering process. Expert Syst. 33(1): 3–13. doi:10.1111/exsy.12116

    Article  Google Scholar 

  8. Mannion M 2002 Using first-order logic for product line model validation. In: Proceedings of the 2nd International Conference on Software Product Line Conference (SPLC2), Springer: Verlag. pp. 176–187. doi:10.1007/3-540-45652-X_11

  9. Rincón L F, Giraldo G L, Mazo R and Salinesi C 2014 An ontological rule-based approach for analyzing dead and false optional features in feature models. Electron. Notes Theoret. Comput. Sci. 302: 111–132. doi:http://dx.doi.org/10.1016/j.entcs.2014.01.023

    Article  Google Scholar 

  10. Wielemaker J 2007 SWI-Prolog (Version 5.6.36), free software, Amsterdam, University of Amsterdam

  11. Salinesi C, Mazo R and Diaz D 2010 Criteria for the verification of feature models. In: Proceedings of the 28th INFORSID (INFormatique Des ORganisations et Syst`emes d’Information et de Décision). pp. 293–308

  12. Von Der Massen T and Lichter H 2004 Deficiencies in feature models. In: Proceedings of the Workshop on Software Variability Management for Product DerivationTowards Tool Support. pp. 59–62

  13. Lopez-Herrejon R and Batory D 2001 A standard problem for evaluating product-line methodologies. In: Proceedings of the 3rd International Conference on Generative and Component-Based Software Engineering, Springer: Berlin Heidelberg. pp. 10–24. doi:10.1007/3-540-44800-4_2

  14. Salinesi C and Mazo R 2012 Defects in product line models and how to identify them. Software product line – advanced topic, InTech. 97–122. doi:10.5772/35662

    Google Scholar 

  15. Segura S 2008 Automated analysis of feature models using atomic sets. In: Proceedings of the 1st Workshop on Analyses of Software Product Lines (ASPL 2008), SPLC’08. pp. 201–207

  16. Gruber T R 1993 A translation approach to portable ontology specifications. Knowl. Acquisit. 5(2): 199–220. doi:10.1006/knac.1993.1008

    Article  Google Scholar 

  17. Czarnecki K, Kim C H P and Kalleberg K T 2006 Feature models are views on ontologies. In: Proceedings of the 10th International on Software Product Line Conference, IEEE Computer Society. pp. 41–51

  18. De Bruijn J and Heymans S 2006 Translating ontologies from predicate-based to frame-based languages. In: Proceedings of the 2nd International Conference on Rules and Rule Markup Languages for the Semantic Web, IEEE. pp. 7–16. doi:10.1109/RULEML.2006.23

  19. Mazo R, Lopez-Herrejon R, Salinesi C, Diaz D and Egyed A 2011 Conformance checking with constraint logic programming: the case of feature models. In: Proceedings of the 35th Annual International Computer Software and Applications Conference (COMPSAC), IEEE Press. pp. 456–465

  20. Zaid L A, Houben G, De Troyer O and Kleinermann F 2008 An OWL-based approach for integration in collaborative feature modelling. In: Proceedings of the 4th Workshop on Semantic Web Enabled Software Engineering (SWESE2008). pp. 93–100

  21. Noorian M, Ensan A, Bagheri E, Boley H and Biletskiy Y 2011 Feature model debugging based on description logic reasoning. In: Proceedings of the 17th International Conference on Distributed Multimedia Systems (DMS’11). pp. 158–164

  22. Goldstein R C and Storey V C 1991 Database and expert systems applications. In: Proceedings of the International Conference in Berlin, Federal Republic of Germany, Springer: Vienna Wien Gmb. pp. 124–129. doi:10.1007/978-3-7091-7555-2_21

  23. Pohl K, Bockle G and Van Der Linden F 2005 Software product line engineering foundations principles and techniques. Springer: Verlag New York, ISBN: 3540243720

    Book  MATH  Google Scholar 

  24. Johansen M F, Fleurey F, Acher M, Collet P and Lahire P 2010 Exploring the synergies between feature models and ontologies. In: SPLC Workshops. pp. 163–171

  25. Kim C H P 2006 On the relationship between feature models and ontologies. University of Waterloo, Master’s Thesis. (Available at http: //gsd.uwaterloo.ca/2006/05/11/peter-kims-masc-thesis/.14)

  26. Lee S, Kim J, Song C and Baik D 2007 An approach to analyzing commonality and variability of features using ontology in a software product line engineering. In: Proceedings of the 5th International Conference on Software Engineering Research, Management and Applications. pp. 727–734

  27. Sirin E, Parsia B, Grau BC, Kalyanpur A and Katz Y 2007 Pellet: a practical OWL-DL reasoner. Web Semant. Sci., Services Agents World Wide Web. 5: 51–53. doi:10.1016/j.websem.2007.03.004

    Article  Google Scholar 

  28. Wang H, Li Y F, Sun J, Zhang H and Pan J 2005 A semantic web approach to feature modeling and verification. In: Proceedings of the Workshop on Semantic Web Enabled Software Engineering (SWESE’05). Galway, Ireland

  29. Wang H H, Li Y F, Sun J, Zhang H and Pan J 2007 Verifying feature models using OWL. Web Semant. Sci., Services Agents World Wide Web. 5: 117–129. doi:http://dx.doi.org/10.1016/j.websem.2006.11.006

    Article  Google Scholar 

  30. Matcha V B, Reddy P V G D P, Hari C V M K, Srinivas G, Rao N S, Jayachand B, Kumar J N V R S, SriRamGanesh G, Krishna N V R V V, Pradeep I K and Ramesh C 2009 Software reuse: ontological approach to feature modeling. Int. J. Comput. Sci. Netw. Security 9(8): 262–268

    Google Scholar 

  31. Zaid L A, Kleinermann F and Troyer O D 2009 Applying semantic web technology to feature modeling. In: Proceedings of the 2009 ACM symposium on Applied Computing (SAC ‘09). ACM, New York, NY, USA. pp. 1252–1256. doi:http://doi.acm.org/10.1145/1529282.1529563

  32. Mazo R, Salinesi C and Diaz D 2012 VariaMos: a tool for product line driven systems engineering with a constraint based approach. In: Proceedings of the 24th International Conference on Advanced Information Systems Engineering (CAiSE Forum ’12). Springer Press, Gdansk-Poland. pp. 25–29

    Google Scholar 

  33. Thüm T, Kästner C, Benduhn F, Meinicke J, Saake G and Leich T 2014 FeatureIDE: an extensible framework for feature-oriented software development. Sci. Comput. Program. 79: 70–85. doi:http://dx.doi.org/10.1016/j.scico.2012.06.002

    Article  Google Scholar 

  34. Trinidad P, Benavides A and Ruiz-Cortés A 2006 Isolated features detection in feature model. Paper presented at the Advanced Information Systems Engineering (CAiSE), Luxembour. doi:http://www.ceur-ws.org/Vol-231/Paper19.pdf

  35. Trinidad P, Benavides D, Duran A, Ruiz-Cortés A and Toro M 2008a Automated error analysis for the agilization of feature modelling. J. Syst. Softw. 81: 883–896. doi:10.1016/j.jss.2007.10.030

  36. Trinidad P, Benavides D, Ruiz-Cortés A, Segura S and Jimenez A 2008b FAMA framework. In: Proceedings of the 12th International Software Product Line Conference (SPLC’12), IEEE Computer Society. pp. 359. doi:10.1109/SPLC.2008.50

  37. Broek P and Galvão I 2009 Analysis of feature models using generalised feature trees. In: Proceedings of the Third International Workshop on Variability Modeling of Software-intensive Systems (VaMoS’09), University of Sevilla, Spain. pp. 71–76. doi:10.1.1.216.5377

  38. Zhang G, Ye H and Lin Y 2013 An approach for validating feature models in software product lines. J. Softw. Eng. 7(1): 1–29. doi:10.3923/jse.2013.1.29

    Article  MathSciNet  Google Scholar 

  39. Javed M, Naeem M and Wahab H A 2014 Towards the maturity model for feature oriented domain analysis. Comput. Ecol. Softw. 4(3): 170–182

    Google Scholar 

  40. Ripon S, Hossain J and Bhuiyan T 2013 Managing and analysing software product line requirements. Int. J. Softw. Eng. Appl. 4(5): 63–75. doi:10.5121/ijsea.2013.4505

    Google Scholar 

  41. Millo J-V, Ramesh S, Krishna S N and Narwane G K 2013 Compositional verification of software product lines. In: Proceedings of the 10th International Conference on Integrated Formal Methods, Springer, Lecture Notes in Computer Science. vol. 7940, pp. 109–123. doi:10.1007/978-3-642-38613-8_8

  42. Trinidad P and Ruiz-Cortés A 2009 Abductive reasoning and automated analysis of feature models: How are they connected. In: Proceedings of the 3rd International Workshop on Variability Modelling of Software-Intensive Systems. pp. 145–153. doi:10.13140/2.1.4955.0400

  43. Millo J-V, Mohalik S K and Ramesh S 2011 Integrated analysis of software product lines: a constraint based framework for consistency, liveness, and commonness checking. In: Proceedings of the 4th India Software Engineering Conference, ISEC ’11, New York, NY, USA. ACM. pp. 41–50. doi:10.1145/1953355.1953361

  44. Osman A, Amnuaisuk S P and Ho C K 2008 Knowledge based method to validate feature models. In: Proceedings of the 12th International Conference Software Product Lines Conference (SPLC 2008), Limerick, Ireland. pp. 217–225

    Google Scholar 

  45. Giraldo G L, Rincón-Perez L and Mazo R 2013 Identifying dead features and their causes in product line models: an ontological approach. Revista DYNA. 81: 68–77. doi:10.15446/dyna.v81n183.36348

  46. Rincón L, Giraldo G L, Mazo R, Salinesi C and Diaz D 2015 Method to identify corrections of defects on product line models. Electron. Notes Theoret. Comp. Sci. 314: 61–81. doi:10.1016/j.entcs.2015.05.005

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Acknowledgement

One of the authors, Megha, gratefully acknowledges the University Grants Commission (UGC), New Delhi, Government of India, for awarding her the Rajiv Gandhi National Fellowship (Grant No. F117.1/201415/RGNF201415SCJAM66324) to carry out this research work. We would like to thank Vikram Jeet Singh, Research Scholar, Department of Computer Science, Himachal Pradesh University, Shimla, India.

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Correspondence to Megha Bhushan.

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Bhushan, M., Goel, S. Improving software product line using an ontological approach. Sādhanā 41, 1381–1391 (2016). https://doi.org/10.1007/s12046-016-0571-y

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