Skip to main content
SpringerLink
Log in

Measuring Flexibility in Software Project Schedules

  • Research Article - Computer Engineering and Computer Science
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

The complexity of software projects is growing with the increasing complexity of software systems. The pressure to fit schedules within shorter periods of time leads to initial project schedules with a complex logic. These schedules are often highly susceptible to any subsequent delays in project activities. Thus, techniques need to be developed to determine the quality of a software project schedule. Most of the existing measures of schedule quality define the goodness of a schedule in terms of its network complexity. However, these measures fail to estimate the flexibility of a schedule, that is, the extent to which a schedule can withstand delays without requiring extensive changes. The relatively few schedule flexibility measures that exist in literature suffer from several drawbacks such as lack of a theoretical foundation, not having a definite scale and not being able to distinguish between schedules with similar network topologies. In this paper, we address these issues by defining two flexibility measures for software project schedules, namely path shift and value shift, which, respectively, predict the impact of changes in activity durations on the critical paths and the critical value of a schedule. Inspired by the notion of betweenness centrality, these measures are theoretically sound, have a well-defined scale, and require little computational effort. Furthermore, by several examples and two real-life software project case studies, we demonstrate that these measures outperform the existing flexibility measures in clearly discriminating between the flexibility of software project schedules having very similar topologies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Mahmood S., Lai R., Kim Y.S., Kim J.H., Park S.C., Oh H.S.: A survey of component based system quality assurance and assessment. Inf. Softw. Technol. 47(10), 693–707 (2005)

    Article  Google Scholar 

  2. Mahmood S., Lai R., Kim Y.S.: Survey of component based software development. IET Softw. 1(2), 57–66 (2007)

    Article  Google Scholar 

  3. Khan M.A., Mahmood S.: A graph based requirements clustering approach for component selection. Adv. Eng. Softw. 54, 1–6 (2012)

    Article  Google Scholar 

  4. Alshayeb M.: The impact of refactoring to patterns in software quality attributes. Arab. J. Sci. Eng. 36, 1241–1251 (2011)

    Article  Google Scholar 

  5. Verner, J.; Brereton, O.; Kitchenham, B.; Turner, M.; Niazi, M.: Systematic literature reviews in global software development: a tertiary study. In: 16th International Conference on Evaluation and Assessment in Software Engineering (EASE 2012), pp. 2–11 (2012)

  6. Niazi, M.; Mahmood, S.; Alshayeb, M.; Riaz, M.R.; Faisal, K.; Cerpa, N.: Challenges of project management in global software development: initial results. In: Proceedings of Science and Information Conference (SAI 2013), pp. 202–206 (2013)

  7. Fitzgerald B.: The transformation of open source software. MIS Q. 30(3), 587–598 (2006)

    Google Scholar 

  8. Hericko A.Z.M., Rozman I.: An approach to optimizing software development team size. Inf. Process. Lett. 108(3), 101–106 (2008)

    Article  MathSciNet  Google Scholar 

  9. Nan N., Harter D.E.: Impact of budget and schedule pressure on software development cycle time and effort. IEEE Trans. Softw. Eng. 35(5), 624–637 (2009)

    Article  Google Scholar 

  10. CHAOS Report 2009. The Standish Group (2009)

  11. Smith S.F.: Is Scheduling a Solved Problem? Multidisciplinary Scheduling: Theory and Applications. Springer, Berlin (2005)

    Google Scholar 

  12. Schwalbe, K.: Information Technology Project Management, 6th edn. Course Technology, Boston (2014)

  13. Sandru, M.; Olaru, M.: Critical path method applied to the multi project management environment. In: Proceedings of the European Conference on Management Leadership, 440 pp (2013)

  14. Nassar K., Hegab M.Y.: Developing a complexity measure for project schedules. J. Constr. Eng. Manag. 132, 554–561 (2006)

    Article  Google Scholar 

  15. Kiamann R.A.: Coefficient of network complexity. Manag. Sci. 21(2), 172–177 (1974)

    Article  Google Scholar 

  16. Reyck B., Herroelen W.: On the use of the complexity index as a measure of complexity in activity networks. Eur. J. Oper. Res. 91, 347–366 (1996)

    Article  MATH  Google Scholar 

  17. Badiru A., Pulat P.S.: Comprehensive Project Management: Integrating Optimization Models, Management Principles, and Computers. Prentice Hall, Englewood Cliffs (1995)

    Google Scholar 

  18. Davies, E.M.: An experimental investigation of resource allocation in multiactivity projects with resource restraints. Technical report, University of Birmingham, Environmental Modelling and Survey Unit, Birmingham, UK (2001)

  19. Latva-Koivisto, A.M.: Finding a complexity measure for business process models. Technical report, Helsinki University of Technology (2001)

  20. Whitty S.J., Maylor H.: And then came complex project management. Int. J. Proj. Manag. 27(3), 304–310 (2009)

    Article  Google Scholar 

  21. Vidal L.-A., Marle F., Bocquet J.-C.: Measuring project complexity using the analytic hierarchy process. Int. J. Proj. Manag. 29, 718–727 (2011)

    Article  Google Scholar 

  22. Duggan J., Byrne H., Lyons G.: A task allocation optimizer for software construction. IEEE Softw. 21(3), 76–82 (2004)

    Article  Google Scholar 

  23. Chen W., Zhang J.: Ant colony optimization for software project scheduling and staffing with an event-based scheduler. IEEE Trans. Softw. Eng. 39(1), 1–17 (2013)

    Article  Google Scholar 

  24. Abdel-Hamid K., Sengupta K., Ronan D.: Software project control: an experimental investigation of judgment with fallible information. IEEE Trans. Softw. Eng. 19(6), 603–612 (1993)

    Article  Google Scholar 

  25. Abdel-Hamid K., Sengupta K., Swett C.: The impact of goals on software project management: an experimental investigation. MIS Q. 23(4), 531–555 (1999)

    Article  Google Scholar 

  26. Ding, R.G.; Jing, X.H.: Five principles of project management in software companies. Proj. Manag. Technol. 1 (2003)

  27. Kitchenham B.: Empirical studies of assumptions that underlie software cost-estimation models. Inf. Softw. Technol. 34(4), 211–219 (1992)

    Article  Google Scholar 

  28. Ruhe G., Saliu M.O.: The art and science of software release planning. IEEE Softw. 22(6), 47–53 (2005)

    Article  Google Scholar 

  29. Austin R.: The effects of time pressure on quality in software development: an agency model. Inf. Syst. Res. 12(2), 195–207 (2001)

    Article  MathSciNet  Google Scholar 

  30. Cesta, A.O.A.; Smith, S.F.: Profile based algorithms to solve multiple capacitated metric scheduling problems. In: Proceedings of the 4th International Conference on Artificial Intelligence Planning Systems (AIPS 98), pp. 214–223 (1998)

  31. Policella, A.C.N.; Smith, S.F.; Oddi, A.: Generating robust schedules through temporal flexibility. In: Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS 2004), pp. 209–218 (2004)

  32. Aloulou, M.; Portmann, M.: An efficient proactive reactive scheduling approach to hedge against shop floor disturbances. In: Proceedings of the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications 2003 (2003)

  33. Klimek M., Lebkowski P.: Resource allocation for robust project scheduling. Bull. Polish Acad. Sci. Tech. Sci. 59, 51–55 (2011)

    MATH  Google Scholar 

  34. Hevner A.R., Ram S., March S.T., Park J.: Design science in information systems research. MIS Q. 28(1), 75–105 (2004)

    Google Scholar 

  35. Mahmood, S.; Khan, M.A.: A degree centrality-based approach to prioritize interactions of component-based systems. In: Proceedings of 2012 International Conference on Computer and Information Science (ICCIS) 2, 863–867 (2012)

  36. Borgatti S.P., Everett M.G.: A graph-theoretic perspective on centrality. Soc. Netw. 28, 466–484 (2005)

    Article  Google Scholar 

  37. Kwak Y.H., Ingall L.: Exploring monte carlo simulation applications for project management. Risk Manag. 9, 44–57 (2007)

    Article  Google Scholar 

  38. McCabe, B.: Monte carlo simulations for schedule risks. In: Chick, S., Sánchez, P.J., Ferrin, D., Morrice, D.J. (eds.) Proceedings of the 2003 Winter Simulation Conference. pp. 1561–1565 (2003)

  39. Mckay M.D., Beckman R.J., Conover W.J.: A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 42(1), 55–61 (2000)

    Article  Google Scholar 

  40. Can F., Polat T., Polat F.: State of the Art Applications of Social Network Analysis. Lecture Notes in Social Networks. Springer, Berlin (2014)

    Book  Google Scholar 

  41. Brucker P., Drexl A., Mohring K., Neumnn K., Pesch E.: Resource-constrained project scheduling: notation, classification, models and methods. Eur. J. Oper. Res. 112, 3–41 (1999)

    Article  MATH  Google Scholar 

  42. Qi J.-J., Liu Y.-J., Lei H.-T., Guo B.: Solving the multi-mode resource availability cost problem in project scheduling based on modified particle swarm optimization. Arab. J. Sci. Eng. 39, 5279–5288 (2014)

    Article  Google Scholar 

  43. Sadeghi H., Mousakhani M., Yazdani M., Delavari M.: Evaluating project managers by an interval decision-making method based on a new project manager competency model. Arab. J. Sci. Eng. 39, 1417–1430 (2014)

    Article  Google Scholar 

  44. Lakhoua M.N.: Systemic analysis of an industrial system: case study of a grain silo. Arab. J. Sci. Eng. 38, 1243–1254 (2013)

    Article  Google Scholar 

  45. Lin J.T., Wang F.-K., Wu C.: A comparison study of replenishment strategies in vendor-managed inventory. Arab. J. Sci. Eng. 39, 5253–5264 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, University of Calgary, 2500 Campus Drive NW, Calgary, AB, T2N 1N4, Canada

    Muhammad Ali Khan

  2. Information and Computer Science Department, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    Sajjad Mahmood

Authors
  1. Muhammad Ali Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sajjad Mahmood
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Muhammad Ali Khan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khan, M.A., Mahmood, S. Measuring Flexibility in Software Project Schedules. Arab J Sci Eng 40, 1343–1358 (2015). https://doi.org/10.1007/s13369-015-1597-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-015-1597-x

Keywords

Search

Navigation