Skip to main content

COMET-OCEP: A Software Process for Research and Development

  • Conference paper
  • First Online:
New Perspectives in Software Engineering (CIMPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1297))

Included in the following conference series:

  • 432 Accesses

Abstract

Research and development (R&D) activities are employed to find new theories commonly derived in software products; but the gap between the proof-of-concept software and the final implementation is commonly hard to narrow. In a previous work, a combination of the COMET (collaborative object modeling and architectural design method) and OCEP (Open Community engagement model) methodologies was successfully applied to the development of a person re-identification system. In this paper, the COMET-OCEP software process is conceptually related to other processes, and its guidelines are detailed. Additionally, the advantages of the COMET-OCEP process are highlighted through the analysis of a test case.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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

Similar content being viewed by others

Notes

  1. 1.

    Artifacts from the design phase are available at https://drive.google.com/drive/folders/1Qkz-5eyJ7MoUzrtzx5IFF3VoagZGVMwL?usp=sharing.

  2. 2.

    The perception software is currently being registered, and will be available at the same address as documents from design phase.

References

  1. Kenton, W.: Research and Development (R&D), Investorpedia, 05 July 2020. https://www.investopedia.com/terms/r/randd.asp. Accessed 04 Aug 2020

  2. Kellogg, L., Bangerth, W., Hwang, L.J., Heister, T., Gassmoller, R.: The role of scientific communities in creating reusable software: lessons from geophysics. Comput. Sci. Eng. 21, 25–35 2018

    Google Scholar 

  3. Ahalt, S., et al.: Water science software institute: agile and open source scientific software development. Comput. Sci. Eng. 16(3), 18–26 (2014)

    Article  Google Scholar 

  4. Kelly, D.F.: A software chasm: software engineering and scientific computing. IEEE Softw. 24(6), 119–120 (2007)

    Article  Google Scholar 

  5. Storer, T.: Bridging the chasm: a survey of software engineering practice in scientific programming. ACM Comput. Surv. 50(4), 1–32 (2017)

    Article  Google Scholar 

  6. Sarkar, D., Raghav, B., Tushar, S.: The Python machine learning ecosystem. In: Sarkar, D., Raghav, B., Tushar, S. (eds.) Practical Machine Learning with Python, pp. 67–118. Apress, Berkeley (2018)

    Google Scholar 

  7. do Nascimento, G.S., de Oliveira, A.A.: An agile knowledge discovery in databases software process. In: Data and Knowledge Engineering. Springer, Heidelberg (2012)

    Google Scholar 

  8. Alnoukari, M., Alzoabi, Z., Hanna, S.: Applying adaptive software development (ASD) agile modeling on predictive data mining applications: ASD-DM methodology. In: 2008 International Symposium on Information Technology (2008)

    Google Scholar 

  9. Fonseca Bustos, J., De la Torre Gómora, M.Á., Álvarez, S.C.: Software engineering process for developing a person re-identification framework. In: 7th International Conference on Software Process improvement (CIMPS), Guadalajara, Jalisco (2018)

    Google Scholar 

  10. Thangavelu, S., Jyotishi, A.: Influence of R&D and IPR Regulations on the performance of IT firms in India: an empirical analysis using Tobin’s Q approach. In: Proceedings of the 2017 ACM SIGMIS Conference on Computers and People Research, Bangalore, India (2017)

    Google Scholar 

  11. Morris, C., Segal, J.: Lessons learned from a scientific software development project. IEEE Softw. 29(4), 9–12 (2012)

    Article  Google Scholar 

  12. Hannay, J.E., MacLeod, C., Singer, J., Langtangen, H.P., Pfahl, D., Wilson, G.: How do scientists develop and use scientific software?. In: ICSE Workshop on Software Engineering for Computational Science and Engineering (2009)

    Google Scholar 

  13. Marban, O., Segovia, J., Menasalvas, E., Fernandez-Baizan, C.: Toward data mining engineering: A software engineering approach. Inf. Syst. 34(1), 87–107 (2009)

    Article  Google Scholar 

  14. VMEdu: A Guide to the scrum body of knowledge (SBOK Guide), S. Study, Ed., VMEdu (2016)

    Google Scholar 

  15. CollabNet: The 13th annual state of agile report 2019. https://www.stateofagile.com/\#ufh-i-521251909-13th-annual-state-of-agile-report/473508. Accessed 05 Dec 2019

  16. Yamashita, A.: Integration of SE research and industry: reflections, theories and illustrative example. In: IEEE/ACM 2nd International Workshop on Software Engineering Research and Industrial Practice, Florence, Italy (2015)

    Google Scholar 

  17. Gorton, I.: Cyberinfrastructures: bridging the divide between scientific research and software engineering. Computer 47(8), 48–55 (2014)

    Article  Google Scholar 

  18. Dowling, P.: Successfully transitioning a research project to a commercial spin-out using an agile software process. J. Softw. Evol. Process 26(5), 468–475 (2014)

    Article  Google Scholar 

  19. Borges, P., Monteiro, P., Machado, R.J.: Tailoring RUP to small software development teams. In: 37th EUROMICRO Conference on Software Engineering and Advanced Applications, Oulu, Finland (2011)

    Google Scholar 

  20. Monteiro, P., Borges, P., Machado, R.J., Ribeiro, P.: A reduced set of {RUP} roles to small software development teams. In: International Conference on Software and System Process (ICSSP), Zurich, Switzerland (2012)

    Google Scholar 

  21. Septian, W., Gata, W.: Software development framework on small team using agile framework for small projects (AFSP) with neural network estimation. In: 11th International Conference on Information Communication Technology and System (ICTS), Surabaya (2017)

    Google Scholar 

  22. Nascimento, L.M.A., Horta Travassos, G.: Software knowledge registration practices at software innovation startups: results of an exploratory study. In: Proceedings of the 31st Brazilian Symposium on Software Engineering, Fortaleza, CE, Brazil (2017)

    Google Scholar 

  23. Shlomo, M., Yotam, L.: Customized project charter for computational scientific software products. J. Comput. Methods Sci. Eng. 18(1), 165–176 (2018)

    Google Scholar 

  24. Johanson, A., Hasselbring, W.: Software engineering for computational science: past, present, future. Comput. Sci. Eng. 20(2), 90–109 (2018)

    Article  Google Scholar 

  25. Bonaretti, S., Gold, G.E., Beaupre, G.S.: pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage. PLoS ONE 15(1), 1–19 (2020)

    Article  Google Scholar 

  26. Riesch, M., Nguyen, T.D., Jirauschek, C.: Bertha: project skeleton for scientific software. PLoS ONE 15(3), 1–12 (2020)

    Article  Google Scholar 

  27. Badia, S., Martín, A.F., Principe, J.: FEMPAR: an object-oriented parallel finite element framework. Archives Comput Methods Eng 25(2), 195–271 (2018)

    Article  MathSciNet  Google Scholar 

  28. Netto, M.A.S., Calheiros, R.N., Rodrigues, E.R., Cunha, R.L.F., Buyya, R.: HPC cloud for scientific and business applications: taxonomy, vision, and research challenges. ACM Computing Surveys, 51(1), 8:1–8:29 (2018)

    Google Scholar 

  29. López-Fernández, H., Reboiro-Jato, M., Glez-Peña, D., Laza, R., Pavón, R., Fdez-Riverola, F.: GC4S: a bioinformatics-oriented Java software library of reusable graphical user interface components. PLoS ONE 13(9), 1–19 (2018)

    Article  Google Scholar 

  30. Nanthaamornphong, A., Carver, J.C.: Test-driven development in HPC science: a case study. Comput. Sci. Eng. 20(5), 98–113 (2018)

    Article  Google Scholar 

  31. Rashid, N., Khan, S.U.: Using agile methods for the development of green and sustainable software: success factors for GSD vendors. Journal of Software: Evol. Process 30(8), e1927 (2018)

    Google Scholar 

  32. Gomaa, H.: Software Modeling and Design: UML, Use Cases, Patterns, and Software Architectures. Cambridge University Press, Cambridge (2011)

    Book  Google Scholar 

  33. Gonzalez, R., Woods, R.E.: Digital Image Processing. Pearson, New York (2018)

    Google Scholar 

  34. Pisano, F.M.: Applying use case driven UML-based comet method for autonomous flight management on IMA platform. In: IEEE/AIAA 34th Digital Avionics Systems Conference (DASC) (2015)

    Google Scholar 

  35. Oktaba, H., Alquicira Esquivel, C., Su Ramos, A., Martínez Martínez, A., Quintanilla Osorio, G., Ruvalcaba López, M., López Lira Hinojo, F., Rivera López, M.E., Orozco Mendoza, M.J., Fernández Ordóñez, Y., Flores Lemus, M.Á.: Modelo de Procesos para la Industria de Software: MoProSoft, Ver. 1.3, UNAM, Mexico (2005)

    Google Scholar 

  36. Mikulskiene, B.: Research and Development Project Management. Mykolas Romeris University, Lithuania (2014)

    Google Scholar 

  37. Schwaber, K., Sutherland, J.: The Scrum Guide. Scrum.org (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Miguel De-la-Torre .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Fonseca, J., De-la-Torre, M., Cervantes, S., Granger, E., Mejia, J. (2021). COMET-OCEP: A Software Process for Research and Development. In: Mejia, J., Muñoz, M., Rocha, Á., Quiñonez, Y. (eds) New Perspectives in Software Engineering. CIMPS 2020. Advances in Intelligent Systems and Computing, vol 1297. Springer, Cham. https://doi.org/10.1007/978-3-030-63329-5_7

Download citation

Publish with us

Policies and ethics