Skip to main content
SpringerLink
Log in

Creating a Framework for Quality Decisions in Software Projects

  • Conference paper
Computational Science and Its Applications – ICCSA 2014 (ICCSA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8583))

Included in the following conference series:

  • 3595 Accesses

Abstract

This work analyzes the challenges that quality decisions represent to software project managers. Projects’ goals are normally determined by the paradigm of the Iron Triangle of project management. Managers need to know which are the effects of a quality assurance (QA) decision on the three axis: which effects in quality they can get but at what cost and which effects may appear in terms of schedule. This decision problem is clearly related to existing disciplines like SBSE, multi-objective optimization and methods for ROI calculation and value-based software engineering. This survey paper critically reviews the contributions of these disciplines to support QA decisions together with basic information from a pilot survey carried out as part of the developments of the Iceberg project funded by EU Programme Marie Curie.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aleti, A., Buhnova, B., Grunske, L., Koziolek, A., Meedeniya, I.: Software Architecture Optimization Methods: A Systematic Literature Review. IEEE Transactions on Software Engineering 39(5), 658–683 (2013)

    Article  Google Scholar 

  2. APM. A History of the Association for Project Management 1972-2010. In: Association for Project Management, Buckinghamshire (2010)

    Google Scholar 

  3. Balsamo, S., Marco, A.D., Inverardi, P., Simeoni, M.: Model-Based Performance Prediction in Software Development: A Survey. IEEE Trans. Soft. Eng. 30(5), 295–310 (2004)

    Article  Google Scholar 

  4. Berman, O., Cutler, M.: Resource allocation during tests for optimally reliable software. Computers & OR 31(11), 1847–1865 (2004)

    Article  MATH  Google Scholar 

  5. Bertolino, A., Inverardi, P., Muccini, H.: Software architecture-based analysis and testing: a look into achievements and future challenges. Computing 95(8), 633–648 (2013)

    Article  Google Scholar 

  6. Buzdalov, M., Buzdalova, A., Petrova, I.: Generation of tests for programming challenge tasks using multi-objective optimization. In: Blum, C., Alba, E. (eds.) GECCO (Companion), pp. 1655–1658. ACM (2013)

    Google Scholar 

  7. Camara, J., Correia, P., de Lemos, R., Garlan, D., Gomes, P., Schmerl, B., Ventura, R.: Evolving an adaptive industrial software system to use architecture-based self-adaptation. In: 2013 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 13–22 (May 2013)

    Google Scholar 

  8. Canfora, G., Lucia, A.D., Penta, M.D., Oliveto, R., Panichella, A., Panichella, S.: Multiobjective Cross-Project Defect Prediction. In: ICST, pp. 252–261. IEEE (2013)

    Google Scholar 

  9. Clements, P., Bachmann, F., Bass, L., Garlan, D., Ivers, J., Little, R., Merson, P., Nord, R., Stafford, J.: Documenting Software Architectures: Views and Beyond, 2nd edn. Addison Wesley (2011)

    Google Scholar 

  10. CMMi Team, CMMI® for Development, Version 1.2 CMMI-DEV, V1.2, CMU/SEI-2006-TR-008, ESC-TR-2006-008, Software Engineering Institute (2006)

    Google Scholar 

  11. Corazza, A., Martino, S.D., Ferrucci, F., Gravino, C., Sarro, F., Mendes, E.: Using tabu search to configure support vector regression for effort estimation. Empirical Software Engineering 18(3), 506–546 (2013)

    Article  Google Scholar 

  12. Cortellessa, V., Marinelli, F., Mirandola, R., Potena, P.: Quantifying the influence of failure repair/mitigation costs on service-based systems. In: 24th International Symposium on Software Reliability Engineering, ISSRE 2013 (2013) (to appear)

    Google Scholar 

  13. Cortellessa, V., Marinelli, F., Potena, P.: An optimization framework for “build-or-buy” decisions in software architecture. Computers & OR 35(10), 3090–3106 (2008)

    Article  MATH  Google Scholar 

  14. Cotroneo, D., Pietrantuono, R., Russo, S.: Combining operational and debug testing for improving reliability. IEEE Transactions on Reliability 62(2), 408–423 (2013)

    Article  Google Scholar 

  15. Cotroneo, D., Pietrantuono, R., Russo, S.: Testing techniques selection based on ODC fault types and software metrics. Journal of Systems and Software 86(6), 1613–1637 (2013)

    Article  Google Scholar 

  16. D’Ambros, M., Lanza, M., Robbes, R.: An extensive comparison of bug prediction approaches. In: 7th IEEE Working Conference on Mining Software Repositories (MSR), pp. 31–41

    Google Scholar 

  17. Damian, D., Zowghi, D., Vaidyanathasamy, L., Pal, Y.: An Industrial Case Study of Immediate Benefits of Requirements Engineering Process Improvement at the Australian Center for Unisys Software. Empirical Software Engineering 9(1-2), 45–75 (2004)

    Article  Google Scholar 

  18. Dolado, J.J.: A Validation of the Component-Based Method for Software Size Estimation. IEEE Trans. Software Eng. 26(10), 1006–1021 (2000)

    Article  Google Scholar 

  19. Doloi, H.K.: Understanding stakeholders’ perspective of cost estimation in project management. International Journal of Project Management 29(5), 622–636 (2011)

    Article  Google Scholar 

  20. Dorn, C., Taylor, R.N.: Coupling Software Architecture and Human Architecture for Collaboration-aware System Adaptation. In: Proceedings of the International Conference on Software Engineering, ICSE 2013, pp. 53–62. IEEE Press (2013)

    Google Scholar 

  21. Fernández-Sanz, L., Villalba, M.T., Hilera, J.R., Lacuesta, R.: Factors with negative influence on software testing practice in spain: A survey. In: O’Connor, R.V., Baddoo, N., Cuadrago Gallego, J., Rejas Muslera, R., Smolander, K., Messnarz, R. (eds.) EuroSPI 2009. CCIS, vol. 42, pp. 1–12. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  22. Ferrucci, F., Harman, M., Ren, J., Sarro, F.: Not going to take this anymore: multi-objective overtime planning for software engineering projects. In: ICSE, pp. 462–471. IEEE / ACM (2013)

    Google Scholar 

  23. Ferrucci, F., Harman, M., Sarro, F.: Search-Based Software Project Management. Software Project Management in a Changing World. Springer (to appear, 2014)

    Google Scholar 

  24. Firat, M., Hurkens, C.A.J.: An improved MIP-based approach for a multi-skill workforce scheduling problem. J. Scheduling 15(3), 363–380 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  25. Futrell, R.T., Shafer, L.I., Shafer, D.F.: Quality Software Project Management. Prentice Hall PTR, Upper Saddle River (2001)

    Google Scholar 

  26. Goseva-Popstojanova, K., Singh, A.D., Mazimdar, S., Li, F.: Empirical Characterization of Session-Based Workload and Reliability for Web Servers. Empirical Software Engineering 11(1), 71–117 (2006)

    Article  Google Scholar 

  27. Gueorguiev, S., Harman, M., Antoniol, G.: Software Project Planning for Robustness and Completion Time in the Presence of Uncertainty Using Multi Objective Search Based Software Engineering. In: Proceedings of Conference on Genetic and Evolutionary Computation, GECCO 2009, pp. 1673–1680. ACM (2009)

    Google Scholar 

  28. Güldali, B., Funke, H., Sauer, S., Engels, G.: TORC: test plan optimization by requirements clustering. Software Quality Journal 19(4), 771–799 (2011)

    Article  Google Scholar 

  29. Gyimothy, T., Ferenc, R., Siket, I.: Empirical validation of object-oriented metrics on open source software for fault prediction. IEEE Transactions on Software Engineering 31(10), 897–910 (2005)

    Article  Google Scholar 

  30. Hall, T., Beecham, S., Bowes, D., Gray, D., Counsell, S.: A Systematic Literature Review on Fault Prediction Performance in Software Engineering. IEEE Trans. Software Eng. 38(6), 1276–1304 (2012)

    Article  Google Scholar 

  31. Harman, M., Langdon, W.B., Jia, Y., White, D.R., Arcuri, A., Clark, J.A.: The GISMOE Challenge: Constructing the Pareto Program Surface Using Genetic Programming to Find Better Programs (Keynote Paper). In: Proceedings of the IEEE/ACM International Conference on Automated Software Engineering, ASE 2012, pp. 1–14 (2012)

    Google Scholar 

  32. Harman, M., Mansouri, S.A., Zhang, Y.: Search-based Software Engineering: Trends, Techniques and Applications. ACM Comput. Surv. 45(1), 11:1–11:61 (2012)

    Google Scholar 

  33. Heimerl, C., Kolisch, R.: Scheduling and staffing multiple projects with a multi-skilled workforce. OR Spectrum 32(2), 343–368 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  34. Helander, M.E., Zhao, M., Ohlsson, N.: Planning models for software reliability and cost. IEEE Trans. Software Eng. 24(6), 420–434 (1998)

    Article  Google Scholar 

  35. Hoover, C., Rosso-Llopart, M., Taran, G.: Evaluating Project Decisions: Case Studies in Software Engineering. Addison-Wesley Professional (2009)

    Google Scholar 

  36. Iceberg consortium. Project proposal. How to estimate costs of poor quality in a Software QA project: a novel approach to support management decisions (2012)

    Google Scholar 

  37. Janevski, N., Goseva-Popstojanova, K.: Session Reliability of Web Systems Under Heavy-TailedWorkloads: An Approach based on Design and Analysis of Experiments. IEEE Transactions on Software Engineering 99(preprints), 1 (2013)

    Google Scholar 

  38. Jia, Y., Harman, M.: An Analysis and Survey of the Development of Mutation Testing. IEEE Transactions on Software Engineering 37(5), 649–678 (2011)

    Article  Google Scholar 

  39. Jørgensen, M.: The influence of selection bias on effort overruns in software development projects. Information & Software Technology 55(9), 1640–1650 (2013)

    Article  Google Scholar 

  40. Kazman, R., Asundi, J., Klein, M.: Quantifying the costs and benefits of architectural decisions. In: Proceedings of the 23rd International Conference on Software Engineering, ICSE 2001, pp. 297–306 (May 2001)

    Google Scholar 

  41. Kazman, R., Klein, M., Barbacci, M., Longstaff, T., Lipson, H., Carriere, J.: The architecture tradeoff analysis method. In: Proceedings of the Fourth IEEE Intern. Conference on Engineering of Complex Computer Systems, ICECCS 1998, pp. 68–78 (August 1998)

    Google Scholar 

  42. Kifetew, F.M., Panichella, A., De Lucia, A., Oliveto, R., Tonella, P.: Orthogonal Exploration of the Search Space in Evolutionary Test Case Generation. In: Proceedings of the Intern. Symposium on Software Testing and Analysis, ISSTA 2013, pp. 257–267. ACM (2013)

    Google Scholar 

  43. Kiper, J.D., Feather, M.S., Richardson, J.: Optimizing the V& V Process for Critical Systems. In: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, GECCO 2007, pp. 1139–1139. ACM, New York (2007)

    Google Scholar 

  44. Kitchenham, B.: Procedures for Performing Systematic Reviews (TR/SE-0401). Technical report, Keele University (2004)

    Google Scholar 

  45. Kpodjedo, S., Ricca, F., Galinier, P., Guéhéneuc, Y.-G., Antoniol, G.: Design evolution metrics for defect prediction in object oriented systems. Empirical Software Engineering 16(1), 141–175 (2011)

    Article  Google Scholar 

  46. Lakhotia, K., Harman, M., Gross, H.: Austin: An open source tool for search based software testing of c programs. Information and Software Technology 55(1), 112–125 (2013)

    Article  Google Scholar 

  47. Li, H., Womer, K.: Scheduling projects with multi-skilled personnel by a hybrid MILP/CP benders decomposition algorithm. J. Scheduling 12(3), 281–298 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  48. Malek, S., Medvidovic, N., Mikic-Rakic, M.: An Extensible Framework for Improving a Distributed Software System’s Deployment Architecture. IEEE Transactions on Software Engineering 38(1), 73–100 (2012)

    Article  Google Scholar 

  49. Mead, N., Allen, J., Conklin, W., Drommi, A., Harrison, J., Ingalsbe, J., Rainey, J., Shoemaker, D.: Making the Business Case for Software Assurance (CMU/SEI-2009-SR-001). Technical report. Software Engineering Institute, Carnegie Mellon University, Pittsburgh (2009), http://resources.sei.cmu.edu/library/assetview.cfm?AssetID=8831

  50. Mirandola, R., Potena, P., Scandurra, P.: Adaptation space exploration for service-oriented applications. Science of Computer Programming 80(Part B), 356–384 (2014)

    Article  Google Scholar 

  51. Moser, T., Biffl, S., Winkler, D.: Process-driven Feature Modeling for Variability Management of Project Environment Configurations. In: Proceedings of International Conference on Product Focused Software, PROFES 2010, pp. 47–50. ACM (2010)

    Google Scholar 

  52. Oster, N., Saglietti, F.: Automatic Test Data Generation by Multi-objective Optimisation. In: Górski, J. (ed.) SAFECOMP 2006. LNCS, vol. 4166, pp. 426–438. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  53. Pierantuono, R., Russo, S., Battipaglia, I., Gaiani, C., Fernandez, L., Rodriguez, D.: Industrial needs collection and state of the art surveys (2013)

    Google Scholar 

  54. Potena, P.: Optimization of adaptation plans for a service-oriented architecture with cost, reliability, availability and performance tradeoff. Journal of Systems and Software 6(3), 624–648 (2013)

    Article  Google Scholar 

  55. Rodriguez, D., Ruiz, M., Riquelme, J.C., Harrison, R.: Multiobjective Simulation Opti misation in Software Project Management. In: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, GECCO 2011, pp. 1883–1890. ACM (2011)

    Google Scholar 

  56. Stylianou, C., Gerasimou, S., Andreou, A.: A Novel Prototype Tool for Intelligent Software Project Scheduling and Staffing Enhanced with Personality Factors. In: IEEE Intern. Conference on Tools with Artificial Intelligence (ICTAI), vol. 1, pp. 277–284 (2012)

    Google Scholar 

  57. Wagner, S.: Towards Software Quality Economics for Defect-Detection Techniques. In: Software Engineering Worksho. 29th Annual IEEE/NASA, pp. 265–274 (April 2005)

    Google Scholar 

  58. Ye, Z., Zhou, X., Bouguettaya, A.: Genetic Algorithm Based QoS-Aware Service Compositions in Cloud Computing. In: Yu, J.X., Kim, M.H., Unland, R. (eds.) DASFAA 2011, Part II. LNCS, vol. 6588, pp. 321–334. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  59. Zeng, H., Rine, D.: Estimation of Software Defects Fix Effort Using Neural Networks. In: COMPSAC Workshops, pp. 20–21. IEEE Computer Society (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, University of Alcalá, 28871, Alcalá de Henares, Madrid, Spain

    Pasqualina Potena, Luis Fernandez-Sanz, Carmen Pages & Teresa Diez

Authors
  1. Pasqualina Potena
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Luis Fernandez-Sanz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Carmen Pages
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Teresa Diez
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Engineering, University of Basilicata, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Sanjay Misra

  3. Department of Production and Systems, University of Minho, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

  4. DICAR, Polytecnico di Bari, 70125, Bari, Italy

    Carmelo Torre

  5. University of Minho, Braga, Portugal

    Jorge Gustavo Rocha  & Maria Irene Falcão  & 

  6. Monash University, 3800,, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, 813-8503, Higashi-ku, Fukuoka, Japan

    Bernady O. Apduhan

  8. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy

    Osvaldo Gervasi

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Potena, P., Fernandez-Sanz, L., Pages, C., Diez, T. (2014). Creating a Framework for Quality Decisions in Software Projects. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8583. Springer, Cham. https://doi.org/10.1007/978-3-319-09156-3_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-09156-3_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09155-6

  • Online ISBN: 978-3-319-09156-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation