Advertisement

Research in Engineering Design

, Volume 25, Issue 2, pp 139–156 | Cite as

Comparative analysis of requirements change prediction models: manual, linguistic, and neural network

  • Beshoy Morkos
  • James Mathieson
  • Joshua D. SummersEmail author
Original Paper

Abstract

Requirement change propagation, if not managed, may lead to monetary losses or project failure. The a posteriori tracking of requirement dependencies is a well-established practice in project and change management. The identification of these dependencies often requires manual input by one or more individuals with intimate knowledge of the project. Moreover, the definition of these dependencies that help to predict requirement change is not currently found in the literature. This paper presents two industry case studies of predicting system requirement change propagation through three approaches: manually, linguistically, and bag-of-words. Dependencies are manually and automatically developed between requirements from textual data and computationally processed to develop surrogate models to predict change. Two types of relationship generation, manual keyword selection and part-of-speech tagging, are compared. Artificial neural networks are used to create surrogate models to predict change. These approaches are evaluated on three connectedness metrics: shortest path, path count, and maximum flow rate. The results are given in terms of search depth needed within a requirements document to identify the subsequent changes. The semi-automated approach yielded the most accurate results, requiring a search depth of 11 %, but sacrifices on automation. The fully automated approach is able to predict requirement change within a search depth of 15 % and offers the benefits of full minimal human input.

Keywords

Requirement change Change propagation Engineering change Dependency modelling Complex system design 

References

  1. Aldous D (1985) Exchangeability and related topics. École d’Été de Probabilités de Saint-Flour XIII Lecture Notes Math 1117:1–198MathSciNetGoogle Scholar
  2. Almefelt L et al (2006) Requirements management in practice: findings from an empirical study in the automotive industry. Res Eng Design 17(3):113–134CrossRefGoogle Scholar
  3. Andreou AS, Zographos AC, Papadopoulos GA (2003) A three-dimensional requirements elicitation and management decision-making scheme for the development of new software components. In Proceedings of the fifth international conference on enterprise information systems (ICEIS). Angers, France, pp 3–13Google Scholar
  4. Bader GD, Hogue CWV (2003) An automated method for finding molecular complexes in large interaction network. BMC Bioinfo 4(2)Google Scholar
  5. Berge C (1976) Graphs and hypergraphs. North-Holland Publishing Company, New YorkzbMATHGoogle Scholar
  6. Chen ZY (2006) Classification of product requirements based on product environment. Concurr Eng 14(3):219–230CrossRefGoogle Scholar
  7. Chen YM, Shir WS, Shen CY (2002) Distributed engineering change management for allied concurrent engineering. Int J Comput Integr Manuf 15(2):127–151CrossRefGoogle Scholar
  8. Chen ZY et al (2007) Formalisation of product requirements: from natural language descriptions to formal specifications. Int J Manuf Res 2(3):362–387CrossRefGoogle Scholar
  9. Clarkson PJ, Simons C, Eckert C (2004) Predicting change propagation in complex design. J Mech Des 126(5):788–797CrossRefGoogle Scholar
  10. Cohen T, Navathe SB, Fulton RE (2000) C-FAR, change favorable representation. Comput Aided Des 32(5):321–338CrossRefGoogle Scholar
  11. Deerwester S et al (1990) Indexing by latent semantic analysis. J Am Soc Inf Sci 41(6):391–407CrossRefGoogle Scholar
  12. Dym CL, Little P (1999) Engineering design: a project-based introduction. Wiley, New YorkGoogle Scholar
  13. Eckert C, Clarkson PJ, Zanker W (2004) Change and customisation in complex engineering domains. Res Eng Design 15(1):1–21CrossRefGoogle Scholar
  14. Freeman L (1977) A set of measures of centrality based on betweenness. Sociometry 40(1):35–41CrossRefGoogle Scholar
  15. Giffin M et al (2009) Change propagation analysis in complex technical systems. J Mech Des 131(8):081001CrossRefMathSciNetGoogle Scholar
  16. Goldberg AV, Tarjan RE (1986) A new approach to the maximum flow problem. In: Annual ACM symposium on theory of computing. ACM, New York, NY, pp 136–146Google Scholar
  17. Goldberg AV, Tarjan RE (1988) A new approach to the maximum flow problem. J ACM 35(4):921–940CrossRefzbMATHMathSciNetGoogle Scholar
  18. Harker SDP, Eason KD, Dobson JE (1993) The change and evolution of requirements as a challenge to the practice of software engineering. In: Proceedings of IEEE international symposium on requirements engineering. IEEE, San Diego, CA, pp 266–272Google Scholar
  19. Hofmann T (2001) Unsupervised learning by probabilistic latent semantic analysis. Mach Learn 42(1):177–196CrossRefzbMATHGoogle Scholar
  20. Jarratt TAW et al (2011) Engineering change: an overview and perspective on the literature. Res Eng Design 22(2):103–124CrossRefGoogle Scholar
  21. Kannapan SM, Marshek KM (1992) A schema for negotiation between intelligent design agents in concurrent engineering. In: Intelligent computer aided design. Elsevier Science Publishers, North Holland, pp 1–25Google Scholar
  22. Kobayashi A, Maekawa M (2001) Need-based requirements change management. In: Proceedings of eighth annual IEEE international conference and workshop on the engineering of computer based systems. IEEE, Washington, DC, pp 171–178Google Scholar
  23. Kotonya G, Sommerville I (1992) Viewpoints for requirements definition. Softw Eng J 7(6):375–387CrossRefGoogle Scholar
  24. Lamar C, Mocko G (2010) Linguistic analysis of natural language engineering requirement statements. In: Tools and methods for competitive engineering. Ancona, ItalyGoogle Scholar
  25. Lee HJ et al (2006) Capturing and reusing knowledge in engineering change management: a case of automobile development. Inf Syst Frontiers 8(5):375–394CrossRefGoogle Scholar
  26. Mathieson JL, Summers JD (2010) Complexity metrics for directional node-link system representations: theory and applications. In: Proceedings of the ASME international design engineering technical conferences, Montreal, QC, pp 13–24Google Scholar
  27. Morkos B (2012) Computational representation and reasoning support for requirements change management in complex system design. Ph.D. Dissertation, Clemson UniversityGoogle Scholar
  28. Morkos B et al. (2010) Requirements and data content evaluation of industry in-house data management system. In: Proceedings of the ASME international design engineering technical conferences, Montreal, QC, pp 493–503Google Scholar
  29. Morkos B, Summers JD (2010) Requirement change propagation prediction approach results from an industry case study. In ASME international design engineering technical conferences, Montreal, QC, pp 111–121Google Scholar
  30. Morkos B, Shankar P, Summers JD (2012) Predicting requirement change propagation, using higher order design structure matrices: an industry case study. J Eng Des 23(12):905–926CrossRefGoogle Scholar
  31. Nurmuliani N, Zowghi D, Williams SP (2006) Requirements volatility and its impact on change effort: evidence-based research in software development projects. In: Australian workshop on requirements engineering. Adelaide, AustraliaGoogle Scholar
  32. Ollinger GA, Stahovich TF (2004) RedesignIT—a model-based tool for managing design changes. J Mech Des 126(2):208–216CrossRefGoogle Scholar
  33. Ottosson S (1996) Dynamic product development: findings from participating action research in a fast new product development process. J Eng Design 7(2):151–169CrossRefGoogle Scholar
  34. Ottosson S, Björk E (2004) Research on dynamic systems—some considerations. Technovation 24(11):863–869CrossRefGoogle Scholar
  35. Pramanick I, Ali H (1994) Analysis and experiments for a parallel solution to the all pairs shortest path problem. In: IEEE international symposium on circuits and systems. New York, NY, pp 479–482Google Scholar
  36. Rajlich V (2000) Modeling software evolution by evolving interoperation graphs. Ann Softw Eng 9(1):235–248CrossRefGoogle Scholar
  37. Ramzan S, Ikram N (2005) Making decision in requirement change management. In: International conference on information and communication technologies. IEEE, Karachi, pp 309–312Google Scholar
  38. Schach SR, Tomer A (2000) A maintenance-oriented approach to software construction. J Softw Maint Res Pract 12(1):25–45CrossRefGoogle Scholar
  39. Shankar P, Morkos B, Summers JD (2010) A hierarchical modeling scheme with non functional requirements. In: ASME design engineering technical conferences. ASME, Montreal, QC, pp 283–296Google Scholar
  40. Shankar P, Morkos B, Summers JD (2012) Reasons for change propagation: a case study in an automotive OEM. Res Eng Design 23(4):291–303CrossRefGoogle Scholar
  41. Spitas C (2011) Analysis of systematic engineering design paradigms in industrial practice: a survey. J Eng Des 22(6):427–445CrossRefGoogle Scholar
  42. Sugden RC, Strens MR (1996) Strategies, tactics and methods for handling change. In: IEEE symposium and workshop on engineering of computer-based systems, Friedrichshafen, Germany, pp 457–463Google Scholar
  43. Teegavarapu S, Summers JD, Mocko G (2008) Case study method for design research: a justification. In: ASME international design engineering technical conferences. Brooklyn, NY, pp 495–503Google Scholar
  44. Toutanova K, Manning CD (2000) Enriching the knowledge sources used in a maximum entropy part-of-speech tagger. In SIGDAT conference on empirical methods in natural language processing and very large corpora. Association for Computational Linguistics, Hong Kong, pp 63–70Google Scholar
  45. Vajna S et al (2005) The autogenetic design theory: an evolutionary view of the design process. J Eng Des 16(4):423–440CrossRefGoogle Scholar
  46. Watts DJ, Strogatz S (1998) Collective dynamics of “small-world” networks. Nature 393(6):440–442CrossRefGoogle Scholar
  47. Yin R (2003) Case study research: design and methods. Sage, Thousand OaksGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • Beshoy Morkos
    • 1
  • James Mathieson
    • 2
  • Joshua D. Summers
    • 3
    Email author
  1. 1.Department of Mechanical and Aerospace EngineeringFlorida Institute of TechnologyMelbourneUSA
  2. 2.Department of Mechanical EngineeringClemson UniversityClemsonUSA
  3. 3.Department of Mechanical EngineeringClemson UniversityClemsonUSA

Personalised recommendations