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WTM to Enhances Predictive Assessment of Systems Development Practices: A Case Study of Petroleum Drilling Project

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Intelligent Human Computer Interaction (IHCI 2021)

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Abstract

Software engineering has devised several project management metrics to optimize implementation and obtain a product with high efficiency, at less time and cost. Inventors faced many challenges to find measurements that able to anticipate accurate results that help avoid errors and risks in the advanced stages of the project. The systems most affected by any errors during the development process are Safety-Critical systems (SCS), as 60% of failures during operation are due to errors during development. This paper proposes a metric that uses weight and milestones to predict implementation in advanced stages of a project. The proposed metric is called Weighted Test Metric (WTM). WTM enhance the reliability assessment and reduce failures during project development by predicting Standards Achievement (SA) in the next test. WTM results showed that faults can be reduced during the development of a petroleum drilling project to 0.67% and enhance the overall reliability to 99.16% while actual results (98.30%). This paper focuses on “How to enhance reliability assessment and reduce failures during project development activities?”. This research raises the question through the application of WTM in the stages of development of the Petroleum Drilling Project.

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References

  1. Garg, R.K., et al.: Ranking of software engineering metrics by fuzzy-based matrix methodology. Softw. Test. Verification Reliab. 23(2), 149–168 (2013). https://doi.org/10.1002/stvr.459

    Article  Google Scholar 

  2. Thawaba, A.A., Ramli, A.A., Fudzee, M.F.M., Wadata, J.: Characteristics for performance optimization of safety-critical system development (SCSD). J. Adv. Comput. Intell. Intell. Inform. 24(2), 232–242 (2020). https://doi.org/10.20965/jaciii.2020.p0232

    Article  Google Scholar 

  3. Martins, L.E.G., Gorschek, T.: Requirements engineering for safety-critical systems: a systematic literature review. Inf. Softw. Technol. 75, 71–89 (2016). https://doi.org/10.1016/j.infsof.2016.04.002

    Article  Google Scholar 

  4. Kuchuk, G., Kharchenko, V., Kovalenko, A., Ruchkov, E.: Approaches to selection of combinatorial algorithm for optimization in network traffic control of safety-critical systems. In: 2016 IEEE East-West Design & Test Symposium (EWDTS), Yerevan, Armenia, pp. 1–6 (2016). https://doi.org/10.1109/EWDTS.2016.7807655

  5. Trivedi, P., Sharma, A.: A comparative study between iterative waterfall and incremental software development life cycle model for optimizing the resources using computer simulation. In: 2013 2nd International Conference on Information Management in the Knowledge Economy, pp. 188–194 (2013)

    Google Scholar 

  6. Liu, S.: How the user liaison’s understanding of development processes moderates the effects of user-related and project management risks on IT project performance. Inf. Manag. 53(1), 122–134 (2016). https://doi.org/10.1016/j.im.2015.09.004

    Article  Google Scholar 

  7. Chen, Y.-S., Wu, C., Chu, H.-H., Lin, C.-K., Chuang, H.-M.: Analysis of performance measures in cloud-based ubiquitous SaaS CRM project systems. J. Supercomput. 74(3), 1132–1156 (2017). https://doi.org/10.1007/s11227-017-1978-x

    Article  Google Scholar 

  8. Silva, N., Vieira, M.: Towards making safety-critical systems safer: learning from mistakes. In: 2014 IEEE International Symposium on Software Reliability Engineering Workshops, Naples, Italy, pp. 162–167 (2014). https://doi.org/10.1109/ISSREW.2014.97

  9. Jethani, K.: Software metrics for effective project management. Int. J. Syst. Assur. Eng. Manag. 4(4), 335–340 (2012). https://doi.org/10.1007/s13198-012-0101-1

    Article  Google Scholar 

  10. Bubevski, V.: A novel approach to software quality risk management. Softw. Test. Verif. Reliab. 24(2), 124–154 (2014). https://doi.org/10.1002/stvr.1488

    Article  Google Scholar 

  11. Zorriassatine, F., Bagherpour, M.: A new method for estimating project weight values. J. Appl. Sci. 9(5), 917–923 (2009)

    Article  Google Scholar 

  12. Hamilton, B.A.: Earned value management tutorial module 5: EVMS concepts and methods. Department of Energy, United States of America (2017). https://www.energy.gov/sites/prod/files/2017/06/f35/EVMModule5_0.pdf

  13. Abd-Elkhalek, H.A., Aziz, R.F., Mohamed, M.M.: EVM Modifications To Improve Cost Control Of Construction Projects. Int. J. Eng. Sci. Res. Technol. (2016)

    Google Scholar 

  14. Ju, H., Xu, S.: Research status of earned value management. In: Li, X., Xu, X. (eds.) Proceedings of the Fourth International Forum on Decision Sciences. UOR, pp. 449–459. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-2920-2_38

    Chapter  Google Scholar 

  15. Helmeriksen, I.S.: Enhanced earned value analysis - improving visibility and forecasts in projects by introduction of clusters, 11 S (2017). https://openarchive.usn.no/usn-xmlui/handle/11250/2452715. Accessed 29 Dec 2019

  16. Batselier, J., Vanhoucke, M.: Improving project forecast accuracy by integrating earned value management with exponential smoothing and reference class forecasting. Int. J. Proj. Manag. 35(1), 28–43 (2017). https://doi.org/10.1016/j.ijproman.2016.10.003

    Article  Google Scholar 

  17. Özcan-Top, Ö., McCaffery, F.: To what extent the medical device software regulations can be achieved with agile software development methods? XP—DSDM—Scrum. J. Supercomput. 75(8), 5227–5260 (2019). https://doi.org/10.1007/s11227-019-02793-x

    Article  Google Scholar 

  18. Damiani, E., Spanoudakis, G., Maciaszek, L.A. (eds.): Evaluation of Novel Approaches to Software Engineering. CCIS, vol. 1172. Springer, Cham (2020). https://doi.org/10.1007/978-3-319-94135-6

    Book  Google Scholar 

  19. Agarwal, M., Majumdar, R.: Tracking scrum projects tools, metrics and myths about agile. Int. J. Emerg. Technol. Adv. Eng. 2, 97–104 (2012)

    Google Scholar 

  20. Budacu, E.N., Pocatilu, P.: Real time agile metrics for measuring team performance. Inform. Econ. 22(4), 70–79 (2018)

    Google Scholar 

  21. Thawaba, A., Ramli, A., Fudzee, M.F.Md., Wadata, J.: A mechanism to support agile frameworks enhancing reliability assessment for SCS development: a case study of medical surgery departments. In: Ghazali, R., Nawi, N.M., Deris, M.M., Abawajy, J.H. (eds.) Recent Advances on Soft Computing and Data Mining. Advances in Intelligent Systems and Computing, pp. 66–76. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-36056-6_7

    Chapter  Google Scholar 

  22. Byrne, D.J., Barry, P.H., Lawson, M., Ballentine, C.J.: Noble gases in conventional and unconventional petroleum systems. Geol. Soc. Lond. Spec. Publ. 468(1), 127–149 (2018). https://doi.org/10.1144/SP468.5

    Article  Google Scholar 

  23. Samia, C., Hamzi, R., Chebila, M.: Contribution of the lessons learned from oil refining accidents to the industrial risks assessment. Manag. Environ. Qual. Int. J. 29(4), 643–665 (2018). https://doi.org/10.1108/MEQ-07-2017-0067

    Article  Google Scholar 

  24. Mahmoodian, M., Li, C.Q.: Failure assessment and safe life prediction of corroded oil and gas pipelines. J. Pet. Sci. Eng. 151, 434–438 (2017). https://doi.org/10.1016/j.petrol.2016.12.029

    Article  Google Scholar 

  25. Najar, S., Al-Kawse, N.: The fourth stage of developing sectors A, B, C and D of the oil and gas fields - the sixth zone. Akhsat- Ma’reb/Shabwh, Report of the Department of the Development of Oil and Gas Fields- Sixth Zone 1-43A-DSOG (2018)

    Google Scholar 

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Acknowledgment

This research was supported by Ministry of Higher Education (MOHE) trough Fundamental Research Grant Scheme (FRGS/1/2019/ICT01/UTHM/02/2). We also want to thank to the Government of Malaysia which provide MyBrain15 programme for sponsoring this work under the self-funded research grant and L00022 from Ministry of Science, Technology and Innovation (MOSTI).

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Correspondence to Abdulaziz Ahmed Thawaba .

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Thawaba, A.A., Ramli, A.A., Fudzee, M.F.M. (2022). WTM to Enhances Predictive Assessment of Systems Development Practices: A Case Study of Petroleum Drilling Project. In: Kim, JH., Singh, M., Khan, J., Tiwary, U.S., Sur, M., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2021. Lecture Notes in Computer Science, vol 13184. Springer, Cham. https://doi.org/10.1007/978-3-030-98404-5_54

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  • DOI: https://doi.org/10.1007/978-3-030-98404-5_54

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