Activity-based function point complexity of use case diagrams for software effort estimation

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Puguh Jayadi
Renny Sari Dewi
Kelik Sussolaikah

Abstract





This study proposes a Function Point Analysis (FPA) based software development effort estimation methodology integrated with Use Case Diagrams. These methods include identifying actor activities, classifying those activities into FPA categories, and calculating Unadjusted Function Points (UFP). Followed by the calculation of Technical Complexity Factors (TCF) and Adjusted Function Points (AFP), this study aims to produce more accurate man-hours estimates. Results show a UFP of 162 TCF of 11, AFP of 123.12, and an estimated effort of 1846.8 hours worked, while the actual effort is 1228 hours. Evaluation of estimates using the metrics Mean Magnitude of Relative Error (MMER) 0.34, Mean Magnitude of Relative Error (MMRE) 0.50, Mean Absolute Error (MAE) 618.80, Mean Balanced Relative Error (MBRE) 0.50, Mean Inverse Balanced Relative Error (MIBRE) 0.34, and Root Mean Squared Error (RMSE) 618.80, showed sufficient precision despite the overestimation. The study suggests the need for adjustments in TCF calculations and considering development environment factors in more detail to improve estimation accuracy. These findings are essential in improving the precision of effort estimation methodologies in software development, particularly in projects that use Use Case Diagrams as the primary framework.





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[1]
P. Jayadi, R. S. . Dewi, and K. Sussolaikah, “Activity-based function point complexity of use case diagrams for software effort estimation”, J. Soft Comput. Explor., vol. 5, no. 1, pp. 1-8, Mar. 2024.
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References

A. A. Nurdin, G. N. Salmi, K. Sentosa, A. R. Wijayanti, and A. Prasetya, “Utilization of Business Intelligence in Sales Information Systems,” J. Inf. Syst. Explor. Res., vol. 1, no. 1, pp. 39–48, Dec. 2022, doi: 10.52465/joiser.v1i1.101.

R. Naufalia, S. A. Usman, and C. L. Bambang, “Analysis and development of company business processes using business process model notation (case study of PT Datacomm Diangraha),” J. Soft Comput. Explor., vol. 2, no. 2, Sep. 2021, doi: 10.52465/joscex.v2i2.48.

A. Purwanto and L. Parningotan Manik, “Software Effort Estimation Using Logarithmic Fuzzy Preference Programming and Least Squares Support Vector Machines,” Sci. J. Informatics, vol. 10, no. 1, pp. 1–12, 2023, doi: 10.15294/sji.v10i1.39865.

S. S. Ali, J. Ren, K. Zhang, J. Wu, and C. Liu, “Heterogeneous Ensemble Model to Optimize Software Effort Estimation Accuracy,” IEEE Access, vol. 11, pp. 27759–27792, 2023, doi: 10.1109/ACCESS.2023.3256533.

A. Y. P. Putri, “Modifikasi Metode Function Point Dengan Menambahkan Kompleksitas Proses Bisnis Pada General System Characteristics Untuk Estimasi Biaya Perangkat Lunak,” Institut Teknologi Sepuluh Nopember, 2018.

M. Lefley and M. J. Shepperd, “Using Genetic Programming to Improve Software Effort Estimation Based on General Data Sets BT - Genetic and Evolutionary Computation — GECCO 2003,” E. Cantú-Paz, J. A. Foster, K. Deb, L. D. Davis, R. Roy, U.-M. O’Reilly, H.-G. Beyer, R. Standish, G. Kendall, S. Wilson, M. Harman, J. Wegener, D. Dasgupta, M. A. Potter, A. C. Schultz, K. A. Dowsland, N. Jonoska, and J. Miller, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2003, pp. 2477–2487.

Z. Polkowski, J. Vora, S. Tanwar, S. Tyagi, P. K. Singh, and Y. Singh, “Machine Learning-based Software Effort Estimation: An Analysis,” in 2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), IEEE, Jun. 2019, pp. 1–6. doi: 10.1109/ECAI46879.2019.9042031.

S. Febriyanti and S. Solehatin, “Application design for web-based car services to increase work time estimates,” J. Student Res. Explor., vol. 2, no. 1, pp. 11–21, Jan. 2024, doi: 10.52465/josre.v2i1.231.

A. B. Nassif, M. Azzeh, A. Idri, and A. Abran, “Software Development Effort Estimation Using Regression Fuzzy Models,” Comput. Intell. Neurosci., vol. 2019, pp. 1–17, Feb. 2019, doi: 10.1155/2019/8367214.

B. K. Park, S. Y. Moon, and R. Y. C. Kim, “Improving Use Case Point (UCP) Based on Function Point (FP) Mechanism,” in 2016 International Conference on Platform Technology and Service (PlatCon), IEEE, Feb. 2016, pp. 1–5. doi: 10.1109/PlatCon.2016.7456803.

R. S. Dewi, A. P. Subriadi, and Sholiq, “A Modification Complexity Factor in Function Points Method for Software Cost Estimation Towards Public Service Application,” Procedia Comput. Sci., vol. 124, pp. 415–422, 2017, doi: 10.1016/j.procs.2017.12.172.

J. Rashid, S. Kanwal, M. Wasif Nisar, J. Kim, and A. Hussain, “An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation,” Comput. Syst. Sci. Eng., vol. 44, no. 2, pp. 1309–1324, 2023, doi: 10.32604/csse.2023.026018.

B. Kumar, “Function point analysis based effort estimation and prediction using Lagrange’s interpolation in Agile software development,” Math. Eng. Sci. Aerosp., vol. 14, no. 2, pp. 395–416, 2023.

H. T. Hoc, V. Van Hai, H. L. T. K. Nhung, and R. Jasek, “Improving the Performance of Effort Estimation in Terms of Function Point Analysis by Balancing Datasets,” 2023, pp. 705–714. doi: 10.1007/978-3-031-21435-6_60.

J. T. M. Dhas and J. Midhunchakravarthy, “Modern Metrics (MM): Software size estimation using function points for artificial intelligence and data analytics applications and finding the effort modifiers of the functional units using indian software industry,” J. Discret. Math. Sci. Cryptogr., vol. 26, no. 3, pp. 629–640, 2023, doi: 10.47974/JDMSC-1734.

A. Farhan, “Penggunaan metode use case point activity-based costing dan adjusted function point untuk estimasi biaya pembuatan software,” 2021. [Online]. Available: https://repository.uinjkt.ac.id/dspace/handle/123456789/65074%0Ahttps://repository.uinjkt.ac.id/dspace/bitstream/123456789/65074/1/ANDRIA FARHAN-FST.pdf

R. S. Dewi, T. W. Andari, A. P. Subriadi, and Sholiq, “Function Points Method in Game Casual Context,” in 2018 International Conference on Electrical Engineering and Computer Science (ICECOS), IEEE, Oct. 2018, pp. 367–372. doi: 10.1109/ICECOS.2018.8605188.

P. Jayadi, A. C. Aria Bima, Y. P. Yudha, and Kelik Sussolaikah, “End User Development pada Use Case Point untuk peningkatan Estimasi Perangkat Lunak,” TEMATIK, vol. 10, no. 1, pp. 74–82, Jun. 2023, doi: 10.38204/tematik.v10i1.1289.

P. Jayadi, Juwari, L. Azis, and K. Sussolaikah, “Estimasi Pengembangan Perangkat Lunak Dengan Use Case Size Point,” vol. 3, pp. 332–340, Mar. 2023, doi: 10.47065/bit.v3i1.408.

N. Marcheta, “Effort Estimation Modeling Of E-Government Application Development Using Function Points Based On Tor And Srs Document,” J. Inf. Technol. Its Util., vol. 3, no. 1, p. 5, Aug. 2020, doi: 10.30818/jitu.3.1.2839.

M. Baiquni, R. Sarno, Sarwosri, and Sholiq, “Improving the accuracy of COCOMO II using fuzzy logic and local calibration method,” in 2017 3rd Int. Conf. Sci. Inf. Technol. (ICSITech), IEEE, Oct. 2017, pp. 284–289. doi: 10.1109/ICSITech.2017.8257126.

H. Hamzah, R. Saptono, and R. Anggrainingsih, “Development of Software Size Estimation Application using Function Point Analysis (FPA) Approach with Rapid Application Development (RAD),” ITSmart J. Teknol. dan Inf., vol. 5, pp. 96–103, Dec. 2016, doi: 10.20961/its.v5i2.1988.

S. Sariyanti and A. Ardiansyah, “Pengembangan Kakas Estimasi Perangkat Lunak dengan Function Point dan Use Case Point untuk Praktikum Rekayasa Perangkat Lunak,” J. Sarj. Tek. Inform., vol. 6, no. 2, pp. 89–97, 2018, doi: 10.12928/jstie.v6i2.15233.

Sholiq, R. S. Dewi, and A. P. Subriadi, “A Comparative Study of Software Development Size Estimation Method: UCPabc vs Function Points,” Procedia Comput. Sci., vol. 124, pp. 470–477, 2017, doi: 10.1016/j.procs.2017.12.179.

F. A. Juyuspan and A. Hidayati, “Estimasi Pengelolaan Suatu Proyek Dalam Pengembangan Perangkat Lunak Menggunakan Analisa Function Point,” J. SimanteC, vol. 5, no. 2, pp. 85–92, 2016.

S. Shukla and S. Kumar, “Towards ensemble-based use case point prediction,” Softw. Qual. J., vol. 31, no. 3, pp. 843–864, Sep. 2023, doi: 10.1007/s11219-022-09612-2.

J. F. Vijay, “Retraction Note: Enrichment of accurate software effort estimation using fuzzy-based function point analysis in business data analytics,” Neural Comput. Appl., vol. 35, no. 6, pp. 4797–4797, Feb. 2023, doi: 10.1007/s00521-022-08159-4.

M. Hariyanto and R. S. Wahono, “Estimasi Proyek Pengembangan Perangkat Lunak Dengan Fuzzy Use Case Points,” IlmuKomputer.com J. Softw. Eng., vol. 1, no. 1, pp. 54–63, 2015.

A. Srivastava, S. S.K, and S. Q. Abbas, “Advancement Of UCP With End User Development Factor: AUCP,” Int. J. Softw. Eng. Appl., vol. 6, no. 2, pp. 01–10, Mar. 2015, doi: 10.5121/ijsea.2015.6201.

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