Use Case Based Approach to Analyze Software Change Impact and Its Regression Test Effort Estimation

  • Avinash Gupta
  • Aprna Tripathi
  • Dharmendra Singh Kuswaha
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 315)


Software needs to be maintained and changed to satisfy the new requirement and existing faults. Without analyzed changes, change implemented to software often cause unexpected ripple effects. To avoid this and diminish the risk of performing undesirable changes, an impact analysis of the change is done. Software Change Impact Analysis (SCIA) needs to be computed at every change request for software systems, to access the impact information for several critical software engineering tasks such as risk analysis, effort estimation, and regression testing. The use of UML analysis/design models on large projects lead to a large number of interdependent UML diagrams. Paper proposes a UML model based approach strictly to use use-case diagram for impact analysis that is applicable in early decision making and change planning. Later, by using the impact set we estimate the regression test effort required for the effected change in the software. The reduction in test effort observed ranges from 47 to 95 %, saving significant software testing cost.


Impact analysis Use-case Test case Regression testing SCIA 


  1. 1.
    Arnold, R., Bohner, S.: Impact analysis-towards a framework for comparison. In Software Maintenance,1993. CSM-93, Proceedings., Conference on, pp. 292–301, (1993)Google Scholar
  2. 2.
    Lehnert, S.: A taxonomy for software change impact analysis. In Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th annual ERCIM Workshop on Software Evolution, IWPSE-EVOL’11, ACM, pp. 41–50, New York, NY, USA, (2011)Google Scholar
  3. 3.
    Visual paradigm: [Online; accessed 03-June- 2013]
  4. 4.
    Antoniol, G., Canfora, G., Casazza, G., De Lucia, A., Merlo, E.: Recovering traceability links between code and documentation. Soft. Eng. IEEE Trans. 28(10), 970–983 (2002)CrossRefGoogle Scholar
  5. 5.
    Corley, C.S., Kraft, N.A., Etzkorn, L.H., Lukins, S.K.: Recovering traceability links between source code and fixed bugs via patch analysis. In Proceedings of the 6th International Workshop on Traceability in Emerging Forms of Software Engineering, pp. 31–37. ACM, (2011)Google Scholar
  6. 6.
    Bohner, S.A.: A graph traceability approach for software change impact analysis. Ph.D. Thesis, Fairfax, VA, USA, UMI Order No. GAX95-42995 (1995)Google Scholar
  7. 7.
    Khalil, A., Dingel, J.: Supporting the evolution of UML models in model driven software developmeny: A Survey, Technical Report, School of Computing. Queens University, Canada (2013)Google Scholar
  8. 8.
    Breivold, H.P., Crnkovic, I., Larsson, M.: A systematic review of software architecture evolution research. Inf. Softw. Technol. 54(1), 16–40 (2012)CrossRefGoogle Scholar
  9. 9.
    Tip, F.: A Survey of Program Slicing Techniques. Technical Report. CWI, Amsterdam, The Netherlands (1994)Google Scholar
  10. 10.
    Göknil, A., Kurtev, I., van den Berg, K.G.: Change impact analysis based on formalization of trace relations for requirements. In: ECMDA Traceability Workshop (ECMDA-TW), pp. 59–75. Berlin, Germany (2008)Google Scholar
  11. 11.
    Fowler, M.: UML Distilled: A Brief Guide to the Standard Object Modeling Language, 3rd edn. Addison-Wesley Longman Publishing Co., Inc, Boston (2003)Google Scholar
  12. 12.
    Briand, L.C., Labiche, Y., O’Sullivan, L.: Impact analysis and change management of uml models. In Proceedings of the International Conference on Software Maintenance, ICSM’03, IEEE Computer Society, pp. 256–,Washington, DC, USA, (2003)Google Scholar
  13. 13.
    Li, Y., Li, J., Yang, Y., Li, M.: Requirement-centric traceability for change impact analysis: a case study. In: Wang, Q., Pfahl, D., Raffo, D. (eds.) Making Globally Distributed Software Development a Success Story. Lecture Notes in Computer Science, vol. 5007, pp. 100–111. Springer, Berlin Heidelberg (2008)CrossRefGoogle Scholar
  14. 14.
    Marcus, Sergeyev, A., Rajlich, V., Maletic, J.I.: An information retrieval approach to concept location in source code. In: Reverse Engineering, 2004. Proceedings. 11th Working Conference on, pp. 214–223. IEEE, (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Avinash Gupta
    • 1
  • Aprna Tripathi
    • 1
  • Dharmendra Singh Kuswaha
    • 1
  1. 1.MNNIT AllahabadAllahabadIndia

Personalised recommendations