Empirical and theoretical validation of a use case diagram complexity metric

Автор: Sangeeta Sabharwal, Preeti Kaur, Ritu Sibal

Журнал: International Journal of Information Technology and Computer Science @ijitcs

Статья в выпуске: 11 Vol. 9, 2017 года.

Бесплатный доступ

A key artifact produced during object oriented requirements analysis is Use Case Diagram. Functional requirements of the system under development and relationship of the system and the external world are displayed with the help of Use Case Diagram. Therefore, the quality aspect of the artifact Use Case Diagram must be assured in order to build good quality software. Use Case Diagram quality is assessed by metrics that have been proposed in the past by researchers, based on Use Case Diagram countable features such as the number of actors, number of scenarios per Use Case etc., but they have not considered Use Case dependency relations for metric calculation. In our previous paper, we had proposed a complexity metric. This metric was defined considering association relationships and dependency prevailing in the Use Case Diagram. The key objective in this paper is to validate this complexity metric theoretically by using Briand’s Framework and empirically by performing a Controlled experiment. The results show that we are able to perform the theoretical and empirical validation successfully.

Еще

Use Case Diagram, Complexity metric, Empirical validation

Короткий адрес: https://sciup.org/15016207

IDR: 15016207   |   DOI: 10.5815/ijitcs.2017.11.04

Список литературы Empirical and theoretical validation of a use case diagram complexity metric

  • B. Anda, D. Sjoberg, M. Jorgensen. 2001 Quality and Understandability of Use Case Models. In Proceedings of ECOOP 2001 European Conference, Springer-Verlag, London, 402-428. DOI: 10.1007/3-540-45337-7_21
  • B. Anda, H. Dreiem, D. Sjoberg, M. Jorgensen. 2001. Estimating Software development Effort based on Use Cases-Experiences from Industry. The Unified Modeling Language. Modeling Languages, Concepts, and Tools. Lecture Notes in Computer Science Vol. 2185, 487-502. DOI: 10.1007/3-540-45441-1_35
  • A. Albrecht. Measuring Application Development Productivity. 1979. In Proceedings of Proceedings of IBM Application Development Symposium.
  • V.R. Basili, L. Briand, W. Melo. 1996. Validation of Object-Oriented Design Metrics as Quality Indicators.IEEE Transactions on Software Engineering, Vol. 22, No. 10, 751-761. DOI: 10.1109/32.544352
  • V.R. Basili.2007. Role of Controlled Experiments in Software Engineering Research. Empirical Software Engineering Issues, LNCS 4336, Springer-Verlag, Berlin, 33-37. DOI: 10.1007/978-3-540-71301-2_10
  • G. Booch, I. Jacobson, J.Rumbaugh. 2001. The Unified Modeling Language User Guide. Addison Wesley. ISBN:978-0321267979
  • L. Briand, S. Morasca, V. Basili. 1996. Property Based Software Engineering Measurement. IEEE Transactions on Software Engineering. Vol. 22, issue 1, 68-86. DOI: 10.1109/32.481535
  • L. Briand, S. Morasca, V. Basili. 1997. Response to: Property Based Software Engineering Measurement: Refining additive Properties. IEEE Transactions on Software Engineering. Vol. 23, issue 3,196-197. DOI: 10.1109/TSE.1997.585509
  • L. Briand, J. Wust, S. IkoNomovski, H. Lounis. 1999. Investigating Quality Factors in Object-Oriented Designs: an Industrial Case Study. In Proceedings of 21st International Conference on Software Engineering, CA, 345-354. DOI: 10.1145/302405.302654
  • L. Briand, J. Wust. 2002. Empirical Studies of Quality Models in Object-Oriented Systems. Advances in Computers, Vol. 59, Academic Press, 97-166. DOI: 10.1016/S0065-2458(02)80005-5
  • R. Brito, F. Carapuça. 1994. Object-Oriented Software Engineering: Measuring and controlling the development process. In Proceedings 4th Interntional Conference on Software Quality, US, 1-8.
  • D. N. Card, W. W. Agresti. 1988. Measuring Software Design Complexity. The Journal of Systems and Software. Elsevier Science Inc, 185-197.
  • S. Cherfi, J. Akoka, I. Wattiau. 2006. Use Case Modeling and Refinement: A Quality-Based Approach. In Proceedings 25th International Conference on Conceptual Modeling, 84-97. DOI: 10.1007/11901181_8
  • J.K Chhabra, K. K. Aggrawal, Y. Singh.2003 Code and Data Spatial Complexity: Two Important Software. Information and Software Technology, Elsevier Science, Vol. 45, 539-546. DOI: 10.1016/S0950-5849(03)00033-8
  • S. Chidamber, C.Kemerer. 1994. A Metric Suite for Object Oriented Design. IEEE Transactions on Software Engineering, Vol. 20, No. 6, 476-493. DOI: 10.1109/32.295895
  • B. Douglass.2004 Computing Model Complexity. Borland: White Paper, I-Logix.
  • N. Fenton, M. Neil. 2000. Software Metrics: Roadmap. In Proceedings of International Conference on Software Engineering. Ireland, 357-370. DOI: 10.1145/336512.336588
  • M. Georgiades, S. Andreou.2012. Formalizing and Automating Use Case Model Development. The Open Software Engineering Journal, Vol. 6, 21-40. DOI: 10.2174/1874107X01206010021
  • M. Genero, G. Poels, M. Piattini. 2007. Defining and Validating Metrics for Assessing the Understandability of Entity-Relationship Diagrams. Data and Knowledge Engineering Elsevier Journal, Vol. 64, 534-557. DOI 10.1016/j.datak.2007.09.011
  • M. Halstead.1977. Elements of Software Science. Elsevier- Science Inc. New York, USA. ISBN:0444002057
  • B. Henderson-Sellers, D. Zowghi, T. Klemola, S. Parasuram. 2002 Sizing Use Cases: How to Create a Standard Metrical Approach. In Proceedings of 8th International Conference on Object-Oriented. Information Systems. 409-421. DOI: 10.1007/3-540-46102-7_43
  • S. Henry, D. Kafura. 1981. Software Structure Metrics Based on Information Flow. IEEE Transactions. Software Engineering, Vol. 7, 510-518. DOI: 10.1109/TSE.1981.231113
  • C. Kaner and W. Bond. 2004. Software Engineering Metrics: What Do They Measure and How Do We Know? In Proceedings of 10th International Software Metrics Symposium, METRICS, 1-12.
  • D. Kang, B. Xu, J. Lu, W. Chu. 2004. Complexity Measure for Ontology Based on UML. In Proceedings of IEEE, Workshop on Future Trends of Distributed Computing, 222-228. DOI: 10.1109/FTDCS.2004.1316620
  • N. Khanahmadliravi, H. R. Khataee. 2012. Estimating Quality of an Object Oriented Software System Using Graph Algorithm. International Journal of Computer and Electrical Engineering, Vol. 4, No. 4, 467-470.
  • M. Lorenz, J. Kidd. 1994. Object-Oriented Software Metrics: A Practical Guide. Englewood Cliffs, New Jersey - USA. 1994. ISBN-13: 978-0131792920
  • M. Marchesi. 1998. OOA Metrics for the Unified Modeling Language. In Proceedings of Euromicro Conference on Software Maintenance and Reengineering, 67-73. DOI: 10.1109/CSMR.1998.665739
  • T. J. McCabe. 1976. A Complexity Measure. IEEE Transactions on Software Engineering, Vol. 2, 308-320. DOI :10.1109/TSE.1976.233837
  • C. L. McClure. 1978. A Model for Program Complexity Analysis. In Proceedings of 3rd international conference on Software Engineering, 149-157.
  • H. Nelson, G. Poels, M. Genero. 2012. A Conceptual Modeling Quality Framework. Software Quality Journal, Vol. 20, 201-228. DOI: 10.1007/s11219-011-9136-9
  • S. Singh, S. Sabharwal, J. Gupta.2009. Events-An Alternative to Use Case as starting point in Object- Oriented Analysis. In Proceedings of 2nd International Conference on Emerging Trends in Engineering & Technology, USA, 1004-1010. DOI: 10.1109/ICETET.2009.94
  • S. Singh, S. Sabharwal, J. Gupta. 2011. Deriving System Complexity Metric from Events and its Validation. International Journal of Software Engineering and Knowledge Engineering, Vol. 21, No. 8, 1097-1121. DOI: 10.1142/S021819401100561X
  • S. Sabharwal, R. Sibal, P. Kaur P.2014. Deriving Complexity Metric Based on Use Case Diagram and its Validation. In Proceedings of IEEE ISSPIT. DOI: 10.1109/ISSPIT.2014.7300571
  • E. J. Weyuker.1998. Evaluating Software Complexity Measures. IEEE Transactions on Software Engineering, Vol. 14, No. 9. 1357 – 1365. DOI: 10.1109/32.6178
  • Y. Yavari, M. Afsharchi, M. Karami. 2011. Software Complexity Level Determination Using Software Effort Estimation Use Case Points Metrics. In Proceedings of 5th Malaysian Conference in Software Engineering, 257-262. DOI: 10.1109/MySEC.2011.6140680
  • B. H Yin, J. W. Winchester. 1978. The Establishment and Use of Measures to Evaluate the Quality of Software Designs. In Proceedings of Software Quality Assurance Workshop on Functional and Performance, New York – USA. 45-52. DOI: 10.1145/800283.811099
  • Z. Yuming, X. Baowen. 2003. Measuring Structural Complexity of UML Class Diagrams. Journal of Electronics. Vol. 20. No.3, 227-231. DOI: 10.1007/BF02687710
  • Y. Zhou, B. Xu. 2005. Measuring Structural Complexity for Class Diagram: An Information Theory Approach. In Proceedings of 5th ACM Symposium on Applied Computing, USA, 1679-1683. 10.1145/1066677.1067057
  • R. Hurlbut. 1997. A Survey of Approaches for Describing and Formalizing Use Cases. Technical Report: XPT-TR-97-03, Expertech Ltd.
  • B. Anda, D. Sjoberg, M. Jorgensen. 2002. Towards an Inspection Technique for Use Case Models. In Proceedings of SEKE 2002, 127-134. 10.1145/568760.568785
  • A. Sellami. and H. Ben-Abdallah. 2009. Functional Size of Use Case Diagrams: A Fine –Grain Measurement. In Proceedings of 4th International Conference on Software Engineering Advances, 282-28, 2009. DOI: 10.1109/ICSEA.2009.96
  • M. Genero. 2001. Using Metrics to Predict OO Information Systems Maintainability. Lecture Notes in Computer Science vol. 2068, 388-401. ISBN:3-540-42215-3
  • G. Krishna, R. Mall. 2010. Model- Based Software Reliability Prediction. Information Systems, Technology and Management Communications in Computer and Information Science, Vol. 54, 145-155. DOI: 10.1007/978-3-642-12035-0_15
  • V. R. Basili and H. D. Rombach. 1988. The TAME Project: Towards Improvement-Oriented Software Environments. IEEE Transactions on Software Engineering, Vol. 14, No. 6, 758-773, DOI: 10.1109/32.6156
  • J. Chhabra, V. Gupta. 2009. Evaluation of Code and Data Spatial Complexity Measures. In Proceedings of Contemporary Computing. IC3 2009. Communications in Computer and Information Science, Springer, Berlin, Heidelberg Vol. 40. 604-614. DOI: 10.1007/978-3-642-03547-0_57
  • G. Karner. 1993. Metrics for Objectory. Diploma Thesis, University of Linkoping, Sweden.
  • Mohammad D. Aljohani, M. Rizwan J. Qureshi. 2016. Management of Changes in Software Requirements during Development Phases. International Journal of Education and Management Engineering(IJEME), Vol.6, No.6, pp.12-26, 2016.DOI: 10.5815/ijeme.2016.06.02
  • S. Koussoube, A. Ayimdji, L.P. Fotso. An Ontology-Based Approach for Multi-Agent Systems Engineering.2013. International Journal of Education and Computer Science, Vol. 1, 42-55 DOI: 10.5815/ijmecs.2013.01.06
  • A. Abran. 2003. COSMIC Measurement Manual-Version 3.0. The COSMIC Implementation Guide for ISO/IEC 19761. Retrieved from www.cosmicon.com/portal/public/mm4.pdf
  • Lauretta O. Osho, Muhammad B. Abdullahi, Oluwafemi Osho. 2016. Framework for an E-Voting System Applicable in Developing Economies. International Journal of Information Engineering and Electronic Business (IJIEEB), Vol.8, No.6, pp.9-21, 2016. DOI: 10.5815/ijieeb.2016.06.02
  • B. W. Boehm, J. R. Brown, and M. Lipow. 1976. Quantitative Evaluation of Software Quality. In Proceedings of 2n International Conference on Software Engineering, San Francisco, California, United States. 592–605.
Еще
Статья научная