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Estimating the Implementation Risk of Requirements in Agile Software Development Projects with Traceability Metrics

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9013))

Abstract

[Context and Motivation] Agile developments follow an iterative procedure with alternating requirements planning and implementation phases boxed into sprints. For every sprint, requirements from the product backlog are selected and appropriate test measures are chosen. [Question/problem] Both activities should carefully consider the implementation risk of each requirement. In favor of a successful project, risky requirements should either be deferred or extra test effort should be dedicated on them. Currently, estimating the implementation risk of requirements is mainly based on gut decisions. [Principal ideas/results] The complexity of the graph spanned by dependency and decomposition relations across requirements can be an indicator of implementation risk. In this paper, we propose three metrics to assess and quantify requirement relations. We conducted a study with five industry-scale agile projects and found that the proposed metrics are in fact suitable for estimating implementation risk of requirements. [Contribution] Our study of heterogeneous, industrial development projects delivers for the first time evidence that the complexity of a requirements traceability graph is correlated with the error-proneness of the implementing source code. The proposed traceability metrics provide an indicator for requirements’ implementation risks. This indicator supports product owners and developers in requirement prioritization and test measure selection.

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References

  1. Bansiya, J., Davis, C.G.: A hierarchical model for object-oriented design quality assessment. IEEE Transactions on Software Engineering 28(1), 4–17 (2002)

    Article  Google Scholar 

  2. Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., et al.: The agile manifesto (2001)

    Google Scholar 

  3. Boehm, B., Basili, V.R.: Software defect reduction top 10 list. Computer 34(1), 135–137 (2001)

    Article  Google Scholar 

  4. Boehm, B., Turner, R.: Using risk to balance agile and plan-driven methods. Computer 36(6), 57–66 (2003)

    Article  Google Scholar 

  5. Breusch, T.S., Pagan, A.R.: A simple test for heteroscedasticity and random coefficient variation. Econometrica: Journal of the Econometric Society, 1287–1294 (1979)

    Google Scholar 

  6. Briand, L.C., Wüst, J., Daly, J.W., Victor Porter, D.: Exploring the relationships between design measures and software quality in object-oriented systems. Journal of Systems and Software 51(3), 245–273 (2000)

    Article  Google Scholar 

  7. Burnham, K.P., Anderson, D.R., Huyvaert, K.P.: Aic model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behavioral Ecology and Sociobiology 65(1), 23–35 (2011)

    Article  Google Scholar 

  8. Cao, L., Ramesh, B.: Agile requirements engineering practices: An empirical study. IEEE Software 25(1), 60–67 (2008)

    Article  Google Scholar 

  9. Cohn, M.: Agile estimating and planning. Pearson Education (2006)

    Google Scholar 

  10. Costello, R.J., Liu, D.B.: Metrics for requirements engineering. Journal of Systems and Software 29(1), 39–63 (1995)

    Article  Google Scholar 

  11. Dick, J.: Rich traceability. In: Proc. of the 1st Int. Workshop on Traceability in Emerging Forms of Software Engineering, Edinburgh, Scotland, pp. 18–23 (2002)

    Google Scholar 

  12. Fenton, N.E., Pfleeger, S.L.: Software metrics: a rigorous and practical approach. PWS Publishing Co. (1998)

    Google Scholar 

  13. Git. http://git-scm.com/

  14. Graves, T.L., Karr, A.F., Marron, J.S., Siy, H.: Predicting fault incidence using software change history. IEEE TSE 26(7), 653–661 (2000)

    Google Scholar 

  15. Hull, E., Jackson, K., Dick, J.: Requirements engineering. Springer, London (2011)

    Book  MATH  Google Scholar 

  16. Jaber, K., Sharif, B., Liu, C.: A study on the effect of traceability links in software maintenance. IEEE Access 1, 726–741 (2013)

    Article  Google Scholar 

  17. JIRA. https://www.atlassian.com/software/jira

  18. Leffingwell, D.: Agile software requirements: lean requirements practices for teams, programs, and the enterprise. Addison-Wesley Professional (2010)

    Google Scholar 

  19. Mäder, P., Egyed, A.: Do developers benefit from requirements traceability when evolving and maintaining a software system? EmpSE, pp. 1–29 (2014)

    Google Scholar 

  20. Mäder, P., Gotel, O., Philippow, I.: Getting back to basics: promoting the use of a traceability information model in practice. In: ICSE Workshop on Traceability in Emerging Forms of Software Engineering, TEFSE, pp. 21–25. IEEE (2009)

    Google Scholar 

  21. Mäder, P., Gotel, O., Philippow, I.: Motivation matters in the traceability trenches. In: Proc. of the 17th IEEE RE conference, pp. 143–148. IEEE (2009)

    Google Scholar 

  22. Marinescu, R.: Measurement and quality in object-oriented design. In: Proc. of the 21st IEEE Int. Conference on Software Maintenance, pp. 701–704. IEEE (2005)

    Google Scholar 

  23. Murgia, A., Concas, G., Tonelli, R., Turnu, I.: Empirical study of software quality evolution in open source projects using agile practices. In: Proc. of the 1st International Symposium on Emerging Trends in Software Metrics, p. 11 (2009)

    Google Scholar 

  24. Nagappan, N., Ball, T., Zeller, A.: Mining metrics to predict component failures. In: Proc. of the 28th Int. Conf. on Software Engineering, pp. 452–461. ACM (2006)

    Google Scholar 

  25. Pfleeger, S.L., Bohner, S.A.: A framework for software maintenance metrics. In: Proc. of Software Maintenance conference, pp. 320–327. IEEE (1990)

    Google Scholar 

  26. Rempel, P., Mäder, P., Kuschke, T.: An empirical study on project-specific traceability strategies. In: Proceedings of the 21st IEEE International Requirements Engineering Conference (RE), pp. 195–204. IEEE (2013)

    Google Scholar 

  27. Rempel, P., Mäder, P., Kuschke, T., Cleland-Huang, J.: Mind the gap: assessing the conformance of software traceability to relevant guidelines. In: Proc. of the 36th International Conference on Software Engineering (ICSE), India (2014)

    Google Scholar 

  28. Rempel, P., Mäder, P., Kuschke, T., Philippow, I.: Requirements traceability across organizational boundaries - a survey and taxonomy. In: Doerr, J., Opdahl, A.L. (eds.) REFSQ 2013. LNCS, vol. 7830, pp. 125–140. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  29. Sedigh-Ali, S., Ghafoor, A., Paul, R.A.: Software engineering metrics for cots-based systems. Computer 34(5), 44–50 (2001)

    Article  Google Scholar 

  30. Sillitti, A., Ceschi, M., Russo, B., Succi, G.: Managing uncertainty in requirements: a survey in documentation-driven and agile companies. In: 11th IEEE International Symposium on Software Metrics, p. 10. IEEE (2005)

    Google Scholar 

  31. Subramanyam, R., Krishnan, M.S.: Empirical analysis of ck metrics for object-oriented design complexity: Implications for software defects. IEEE Transactions on Software Engineering 29(4), 297–310 (2003)

    Article  Google Scholar 

  32. Washizaki, H., Yamamoto, H., Fukazawa, Y.: A metrics suite for measuring reusability of software components. In: Proceedings of the Ninth International of Software Metrics Symposium, pp. 211–223. IEEE (2003)

    Google Scholar 

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Rempel, P., Mäder, P. (2015). Estimating the Implementation Risk of Requirements in Agile Software Development Projects with Traceability Metrics. In: Fricker, S., Schneider, K. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2015. Lecture Notes in Computer Science(), vol 9013. Springer, Cham. https://doi.org/10.1007/978-3-319-16101-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-16101-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16100-6

  • Online ISBN: 978-3-319-16101-3

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