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Software process simulation modelling: A survey of practice

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Journal of Simulation

Abstract

In recent years, simulation modelling of software development processes has attracted considerable interest in software engineering. Despite the growing interest, there is little literature available that reports on the state-of-practice in software process simulation modelling (SPSM). We report results of a survey of simulation in SPSM and relate it to simulation practice in general. The results of this survey indicate that software process simulation (SPS) modellers are generally methodical, work on large complex problems, develop large models, and have a systematic simulation modelling process in place. However, on the other hand, the simulation modelling process and simulation model evaluation have been identified as the most urgent problems to be addressed in SPSM. The results from this investigation are interesting and bring many problems into focus. The paper helps understand the characteristics of the SPSM and SPS modellers, and highlights areas of interest for further in-depth research in the SPSM.

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References

  • Abdel-Hamid TK (1989). The dynamics of software project staffing: A system dynamics based simulation approach. IEEE Trans Softw Eng 15 (2): 109–119.

    Article  Google Scholar 

  • Ahmed R, Hall T, Wernick P and Robinson S (2004a). Simulation modelling practices of ProSim03 modellers: A survey. In: Dietmar P, David R, Ioana R, Paul W (eds). Fifth International Workshop on Software Process Simulation and Modeling, ProSim 2004, Edinburgh, Scotland — Proceedings. Stevenage: IEE Publishing.

  • Ahmed R, Hall T, Wernick P and Robinson S (2004b). Evaluating the quality of software process simulation models. In: Brailsford SC, Oakshott L, Robinson S and Taylor SJE (eds). Proceedings of The OR Society Simulation Workshop (SW2004), Birmingham, UK, 23–24 March. Birmingham: Operational Research Society.

  • Arthur JD et al (1999). Verification and validation (panel session): What impact should project size and complexity have on attendant V&V activities and supporting infrastructure? In: Farrington PA, Nembhard HB, Sturrock DT and Evans GW (eds). Proceedings of the 31st Winter Simulation Conference, Piscataway, NJ: IEE, pp 148–155.

    Google Scholar 

  • Chwif L, Barretto MRP and Paul RJ (2000). On simulation model complexity. In: Joines JA, Barton RR, Kang K and Fishwick PA (eds). Proceedings of the 32nd Winter Simulation Conference archive, 10–13 December, Piscataway, NJ: IEEE, pp 449–455.

    Google Scholar 

  • Cochran JK, Mckulak GT and Savory PA (1995). Simulation project characteristics in industrial settings. INTERFACES 25 (4): 104–113.

    Article  Google Scholar 

  • Foss BA, Lohmann B and Marquardt W (1998). A field study of the industrial modeling process. J Process Control 8 (5/6): 325–338.

    Article  Google Scholar 

  • Gass SI (1987). Managing the modelling process: A personal reflection. Eur J Oper Res 31 (11): 1–8.

    Article  Google Scholar 

  • Henderson P and Howard Y (2000). Simulating a process strategy for large scale software development using systems dynamics. Softw Process Improv Pract 5 (2–3): 121–131.

    Article  Google Scholar 

  • Highsmith J and Cockburn A (2001). Agile software development: The business of innovation. IEEE Comput 34 (9): 120–127.

    Article  Google Scholar 

  • Hlupic V (1999). Simulation software: What users want? Simulation 73 (6): 362–370.

    Article  Google Scholar 

  • Hollocks BW (2001). Discrete-event simulation: An inquiry into user practice. Simul Pract Theory 8 (6–7): 451–471.

    Article  Google Scholar 

  • Huff KE (1996). Process measurement through process modeling and simulation. Proceedings of the 10th International Software Process Workshop, Washington, DC, USA: IEEE Computer Society.

  • Kellner IM, Madachy R and Raffo D (1999). Software process simulation modelling: Why? What? How? J Syst Softw 46 (2–3): 91–105.

    Article  Google Scholar 

  • Kleijnen JPC (2005). Supply chain simulation tools and techniques: A survey. Int J Simul Process Model 1 (1–2): 2–89.

    Google Scholar 

  • Law DR (1998). Scalable means more than more: A unifying definition of simulation scalability. In: Medeiros DJ, Watson EF, Manivannan M, Carson J. (eds). Proceedings of the 30th Winter Simulation Conference, Piscataway, NJ: IEEE, pp 781–788.

    Google Scholar 

  • Lehman MM and Ramil JF (1999). Modeling process dynamics in software evolution processes—some issues. In: Garlan D and Karmer J (eds). International Conference on Software Engineering, Workshop on Software Change and Evolution, Los Angeles, Piscataway, NJ: IEEE, May.

    Google Scholar 

  • Likert R (1932). A technique for the measurement of attitudes. Arch Psychol 22 (140): 44–53.

    Google Scholar 

  • Madachy R (1994). A software project dynamics model for process cost, schedule and risk assessment. PhD Dissertation, Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA.

  • Martin RH and Raffo D (2000). A model of software development process using both continuous and discrete models. Softw Process Improv Pract, Wiley Inter Science 5 (2): 147–157.

    Article  Google Scholar 

  • Melão N and Pidd M (2003). Use of business process simulation: A survey of practitioners. J Opns Res Soc 54 (1): 2–10.

    Article  Google Scholar 

  • Misic VB, Gevaert H and Rennie R (2004). Extreme dynamics: Towards a system dynamics model of the extreme programming software development process. 5th International Workshop on Software Process Simulation and Modeling (ProSim 2004)” W1 1L Workshop — 26th International Conference on Software Engineering (2004/911), pp. 237–242. Edinburgh, Scotland, UK, 24–25 May 2004.

  • Münch J and Pfahl D (2006). Guest Editorials. Special Issues on ProSim 2005. Softw Process Improv Pract 11 (4): 339–343.

    Article  Google Scholar 

  • Murphy SP and Perera TD (2001). General applications: Simulation practice: Key enablers in the development of simulation. In: Peters BA, Smith JS, Medeiros DJ and Evans GW (eds). Proceedings of the 33rd Winter Simulation Conference, Piscataway, NJ: IEEE, pp 1429–1437.

    Google Scholar 

  • Navarro EO and Hoek A (2005). Software process modeling for an educational software engineering simulation game. Softw Process Improv Pract 10 (3): 311–325.

    Article  Google Scholar 

  • Oppenheim AN (1992). Questionnaire Design, Interviewing and Attitude Measurement. Continuum: London.

    Google Scholar 

  • Page EH et al (1999). Panel: Strategic directions in simulation research. In: Farrington PA, Nembhard HB, Sturrock DT and Evans GW (eds). Proceedings of 31st Winter Simulation Conference, Piscataway, NJ: IEEE, pp 1509–1520.

    Google Scholar 

  • Paulk MC, Goldenson DR and White DM (2000). The 1999 survey of high maturity organizations. Software Engineering Institute, CMU, Pittsburgh CMU/SEI-2000-SR-002, February.

  • Paul RJ and Taylor SJE (1997). Simulation modelling methodology and education. Informatica 21 (4): 579–586.

    Google Scholar 

  • Pollacia FL (2004). A survey of discrete event simulation and stateo-the-art discrete event languages. ACM SIGSIM Simulation Digest 2004 20 (3): 8–25.

    Article  Google Scholar 

  • Raffo M (1998). Software process simulation modeling. (ProSim'98): Workshop Report, Empirical Software Engineering, pp 407–412.

  • Robinson S (2002). Modes of simulation practice: Approaches to business and military simulation. Simul Model Pract Theory 10 (8): 513–523.

    Article  Google Scholar 

  • Robinson S et al (2004). Simulation model reuse: Definitions, benefits and obstacles. Simul Model Pract Theory 12 (7–8): 479–494.

    Article  Google Scholar 

  • Roehling ST, Collofell JS, Herman BG and Smith DE (2000). System dynamics modeling applied to software outsourcing decision support. Softw Proc Improv Pract 5 (2–3): 169–182.

    Article  Google Scholar 

  • Rus I, Neu H and Munch J (2003). A systematic methodology for developing discrete event simulation models of software development processes. Proceedings of the International Workshop on Software Process Simulation and Modelling (ProSim 2003), Portland, Oregon, USA, 3–4 May, 2003.

  • Scacchi W (2000). Understanding software process redesign using modeling, analysis and simulation. Softw Proc Improv Pract 5 (2–3): 183–195.

    Article  Google Scholar 

  • Shannon RE (1975). Systems Simulation: The Art and Science. Prentice-Hall: NJ.

    Google Scholar 

  • Spiegel M, Reynolds PF and Brogan DC (2006). Grand challenge case studies in a simulation curriculum. In: Perrone LF, Wieland FP, Liu J, Lawson BG, Nicol DM and Fujimoto RM (eds). Proceedings Winter Simulation Conference, Monterey, CA, Piscataway, NJ: IEEE, pp 2242–2249.

    Google Scholar 

  • Standridge CR, Centeno MA and Johansson B (2005). Introducing simulation across the disciplines. In: Kuh ME, Steiger NM, Armstrong FB and Joines JA (eds). Proceedings Winter Simulation Conference, Orlando, FL, Piscataway, NJ: IEEE, pp 2274–2279.

    Google Scholar 

  • Taylor SJE and Robinson S (2006). So where to next? A survey of the future for discrete-event simulation. J Simul 1 (1): 1–6.

    Article  Google Scholar 

  • Terzi S and Cavalieri S (2004). Simulation in the supply chain context: A survey. Comput Ind 53 (1): 3–16.

    Article  Google Scholar 

  • Waisel LB, Wallace WA and Willemain TR (1999). Visualizing modelling heuristics: An exploratory study. In: De P and De Gross JI (eds), Association for Information Systems.

  • Willemain TR (1994). Insights on modelling from a Dozen experts. Opns Res 42 (2): 213–222.

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Teesside, Middlesbrough, UK

    R Ahmed

  2. University of Hertfordshire, Hatfield, UK

    T Hall & P Wernick

  3. University of Warwick, Warwick Business School, Coventry, UK

    S Robinson

  4. Cranfield University, Cranfield School of Management, Bedford, UK

    M Shah

Authors
  1. R Ahmed
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  2. T Hall
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  3. P Wernick
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  4. S Robinson
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  5. M Shah
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Correspondence to R Ahmed.

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Ahmed, R., Hall, T., Wernick, P. et al. Software process simulation modelling: A survey of practice. J Simulation 2, 91–102 (2008). https://doi.org/10.1057/jos.2008.1

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