{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T15:08:18Z","timestamp":1775920098191,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,22]],"date-time":"2022-01-22T00:00:00Z","timestamp":1642809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008251","name":"Tomas Bata University in Zl\u00edn","doi-asserted-by":"publisher","award":["RO30216002025\/2102"],"award-info":[{"award-number":["RO30216002025\/2102"]}],"id":[{"id":"10.13039\/501100008251","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Function point analysis is a widely used metric in the software industry for development effort estimation. It was proposed in the 1970s, and then standardized by the International Function Point Users Group, as accepted by many organizations worldwide. While the software industry has grown rapidly, the weight values specified for the standard function point counting have remained the same since its inception. Another problem is that software development in different industry sectors is peculiar, but basic rules apply to all. These raise important questions about the validity of weight values in practical applications. In this study, we propose an algorithm for calibrating the standardized functional complexity weights, aiming to estimate a more accurate software size that fits specific software applications, reflects software industry trends, and improves the effort estimation of software projects. The results show that the proposed algorithms improve effort estimation accuracy against the baseline method.<\/jats:p>","DOI":"10.3390\/computers11020015","type":"journal-article","created":{"date-parts":[[2022,1,23]],"date-time":"2022-01-23T20:32:52Z","timestamp":1642969972000},"page":"15","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A New Approach to Calibrating Functional Complexity Weight in Software Development Effort Estimation"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5427-1960","authenticated-orcid":false,"given":"Vo Van","family":"Hai","sequence":"first","affiliation":[{"name":"Department of Computer and Communication Systems, Tomas Bata University in Zlin, Nam. T.G.M. 5555, 76001 Zlin, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3270-9343","authenticated-orcid":false,"given":"Ho Le Thi Kim","family":"Nhung","sequence":"additional","affiliation":[{"name":"Department of Computer and Communication Systems, Tomas Bata University in Zlin, Nam. T.G.M. 5555, 76001 Zlin, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zdenka","family":"Prokopova","sequence":"additional","affiliation":[{"name":"Department of Computer and Communication Systems, Tomas Bata University in Zlin, Nam. T.G.M. 5555, 76001 Zlin, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Radek","family":"Silhavy","sequence":"additional","affiliation":[{"name":"Department of Computer and Communication Systems, Tomas Bata University in Zlin, Nam. T.G.M. 5555, 76001 Zlin, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3724-7854","authenticated-orcid":false,"given":"Petr","family":"Silhavy","sequence":"additional","affiliation":[{"name":"Department of Computer and Communication Systems, Tomas Bata University in Zlin, Nam. T.G.M. 5555, 76001 Zlin, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,22]]},"reference":[{"key":"ref_1","unstructured":"(2021, September 20). Standish Group Report. Available online: https:\/\/www.standishgroup.com."},{"key":"ref_2","unstructured":"Vera, T., Ochoa, S.F., and Perovich, D. (2017). Survey of Software Development Effort Estimation Taxonomies, Computer Science Department, University of Chile. Technical Report."},{"key":"ref_3","first-page":"1","article-title":"Software cost estimation: Algorithmic and non-algorithmic approaches","volume":"2","author":"Khan","year":"2020","journal-title":"Int. J. Data Sci. Adv. Anal."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Faria, P., and Miranda, E. (2012, January 17\u201319). Expert judgment in software estimation during the bid phase of a project\u2014An exploratory survey. Proceedings of the 2012 Joint Conference of the 22nd International Workshop on Software Measurement and the 2012 Seventh International Conference on Software Process and Product Measurement, IEEE, Assisi, Italy.","DOI":"10.1109\/IWSM-MENSURA.2012.27"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1049\/iet-sen.2013.0165","article-title":"Analogy-based effort estimation: A new method to discover set of analogies from dataset characteristics","volume":"9","author":"Azzeh","year":"2015","journal-title":"IET Softw."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1109\/TSE.1978.231521","article-title":"A general empirical solution to the macro software sizing and estimating problem","volume":"4","author":"Putnam","year":"1978","journal-title":"IEEE Trans. Softw. Eng."},{"key":"ref_7","unstructured":"Boehm, B. (1981). Software Engineering Economics, Prentice-Hall."},{"key":"ref_8","unstructured":"Albrecht, A.J. (1979, January 14\u201317). Measuring application development productivity. Proceedings of the IBM Applications Development Symposium, Monterey, CA, USA."},{"key":"ref_9","unstructured":"IFPUG (2010). Function Point Counting Practices, International Function Point Users Group. Manual, Release 4.3.1."},{"key":"ref_10","unstructured":"(2011). Software Engineering\u2014COSMIC: A Functional Size Measurement Method (Standard No. ISO\/IEC 19761:2011)."},{"key":"ref_11","unstructured":"(2010). Information Technology\u2014Systems and Software Engineering\u2014FiSMA 1.1 Functional Size Measurement Method (Standard No. ISO\/IEC 29881:2010)."},{"key":"ref_12","unstructured":"(2002). Software Engineering\u2014MK II Function Point Analysis\u2014Counting Practices Manual (Standard No. ISO\/IEC 20968:2002)."},{"key":"ref_13","unstructured":"(2005). Software Engineering\u2014NESMA Functional Size Measurement Method Version 2.1\u2014Definitions and Counting Guidelines for the Application of Function Point Analysis (Standard No. ISO\/IEC 24570:2005)."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kitchenham, B., and Mendes, E. (2009, January 18). Why comparative effort prediction studies may be invalid. Proceedings of the 5th International Conference on Predictor Models in Software Engineering\u2014PROMISE\u201909, Vancouver, BC, Canada.","DOI":"10.1145\/1540438.1540444"},{"key":"ref_15","unstructured":"Peter, R.H. (2011). Practical Software Project Estimation, McGraw-Hill."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Silhavy, R., Silhavy, P., and Prokopova, Z. (2019). A review of software effort estimation by using functional points analysis. Computational Statistics and Mathematical Modeling Methods in Intelligent Systems, Springer.","DOI":"10.1007\/978-3-030-31362-3"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.jss.2003.12.033","article-title":"Modification of standard Function Point complexity weights system","volume":"74","author":"Sulaiman","year":"2005","journal-title":"J. Syst. Softw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1016\/j.infsof.2007.07.004","article-title":"A new calibration for Function Point complexity weights","volume":"50","author":"Xia","year":"2008","journal-title":"Inf. Softw. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Shukla, S., and Kumar, S. (2019, January 8\u201313). Applicability of neural network based models for software effort estimation. Proceedings of the 2019 IEEE World Congress on Services (SERVICES), Milan, Italy.","DOI":"10.1109\/SERVICES.2019.00094"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Shukla, S., Kumar, S., and Bal, P.R. (2019, January 8\u201313). Analyzing effect of ensemble models on multi-layer perceptron network for software effort estimation. Proceedings of the 2019 IEEE World Congress on Services (SERVICES), Milan, Italy.","DOI":"10.1109\/SERVICES.2019.00116"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Priya, V.A.G., Anitha, K., and Varadarajan, V. (2021). Estimating software development efforts using a random forest-based stacked ensemble approach. Electronics, 10.","DOI":"10.3390\/electronics10101195"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.jss.2016.05.016","article-title":"Systematic literature review of ensemble effort estimation","volume":"118","author":"Idri","year":"2016","journal-title":"J. Syst. Softw."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Idri, A., Hosni, M., and Abran, A. (2016, January 27\u201328). Systematic mapping study of ensemble effort estimation. Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering, Rome, Italy.","DOI":"10.5220\/0005822701320139"},{"key":"ref_24","unstructured":"International Software Benchmarking Standards Groupm (2021, September 20). ISBSG Repository August 2020 R1. Available online: https:\/\/www.isbsg.org."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"9618","DOI":"10.1109\/ACCESS.2019.2891878","article-title":"Categorical variable segmentation model for software development effort estimation","volume":"7","author":"Silhavy","year":"2019","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.jss.2017.11.066","article-title":"An effective approach for software project effort and duration estimation with machine learning algorithms","volume":"137","author":"Pospieszny","year":"2018","journal-title":"J. Syst. Softw."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"338","DOI":"10.4236\/jsea.2017.104020","article-title":"Estimation models for software functional test effort","volume":"10","author":"Jayakumar","year":"2017","journal-title":"J. Softw. Eng. Appl."},{"key":"ref_28","unstructured":"Wei, K.T., Selamat, M.H., Ghani, A.A.A., and Abdullah, R. (2011, January 24\u201326). Exponential Effort Estimation Model Using Unadjusted Function Points. Proceedings of the 5th International Conference on New Trends in Information Science and Service Science, Macao, China."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"8782","DOI":"10.1109\/ACCESS.2018.2791344","article-title":"A Suite of Object Oriented Cognitive Complexity Metrics","volume":"6","author":"Misra","year":"2018","journal-title":"IEEE Access"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.procs.2017.12.172","article-title":"A modification complexity factor in function points method for software cost estimation towards public service application","volume":"124","author":"Dewi","year":"2017","journal-title":"Procedia Comput. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Leal, L.Q., Fagundes, R.A.A., de Souza, R.M.C.R., Moura, H.P., and Gusmao, C.M.G. (2009, January 11\u201314). Nearest-neighborhood linear regression in an application with software effort estimation. Proceedings of the 2009 IEEE International Conference on Systems, Man and Cybernetics, San Antonio, TX, USA.","DOI":"10.1109\/ICSMC.2009.5346380"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Hamza, H., Kamel, A., and Shams, K. (2013, January 15\u201317). Software effort estimation using artificial neural networks: A survey of the current practices. Proceedings of the 2013 10th International Conference on Information Technology: New Generations, Las Vegas, NV, USA.","DOI":"10.1109\/ITNG.2013.111"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Lenarduzzi, V., Morasca, S., and Taibi, D. (2014, January 27\u201329). Estimating software development effort based on phases. Proceedings of the 2014 40th EUROMICRO Conference on Software Engineering and Advanced Applications, Verona, Italy.","DOI":"10.1109\/SEAA.2014.54"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Silhavy, R., Silhavy, P., and Prokopova, Z. (2019). Influence analysis of selected factors in the function point work effort estimation. Intelligent Systems in Cybernetics and Automation Control Theory, Springer.","DOI":"10.1007\/978-3-030-00184-1"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Hammad, M., and Alqaddoumi, A. (2018, January 18\u201320). Features-level software effort estimation using machine learning algorithms. Proceedings of the 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT), Sakhier, Bahrain.","DOI":"10.1109\/3ICT.2018.8855752"},{"key":"ref_36","unstructured":"Abdellatif, T.M. (2018, January 13\u201316). A comparison study between soft computing and statistical regression techniques for software effort estimation. Proceedings of the 2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE), Quebec, QC, Canada."},{"key":"ref_37","unstructured":"IFPUG (2021, September 20). Announcing the New Business Applications Committee. Available online: https:\/\/www.ifpug.org."},{"key":"ref_38","unstructured":"(2009). Software and Systems Engineering\u2014Software Measurement\u2014IFPUG Functional Size Measurement Method (Standard No. ISO\/IEC 20926:2009)."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"e1882","DOI":"10.1002\/smr.1882","article-title":"Analyzing the relationship between project productivity and environment factors in the use case points method","volume":"29","author":"Azzeh","year":"2017","journal-title":"J. Softw. Evol. Process"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1049\/iet-sen.2016.0322","article-title":"Comparative analysis of soft computing techniques for predicting software effort based use case points","volume":"12","author":"Azzeh","year":"2018","journal-title":"IET Softw."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1162\/neco.1992.4.3.415","article-title":"Bayesian interpolation","volume":"4","author":"MacKay","year":"1992","journal-title":"Neural Comput."},{"key":"ref_42","first-page":"211","article-title":"Sparse Bayesian learning and the relevance vector machine","volume":"1","author":"Michael","year":"2001","journal-title":"J. Mach. Learn. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.jeconom.2008.12.014","article-title":"Maximum entropy autoregressive conditional heteroskedasticity model","volume":"150","author":"Park","year":"2009","journal-title":"J. Econom."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1109\/TSE.2011.111","article-title":"On the value of ensemble effort estimation","volume":"38","author":"Kocaguneli","year":"2012","journal-title":"IEEE Trans. Softw. Eng."},{"key":"ref_45","first-page":"25","article-title":"Combining multiple learners induced on multiple datasets for software effort prediction","volume":"17","author":"Kocaguneli","year":"2009","journal-title":"Int. Symp. Softw. Reliab. Eng."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Huang, D.S., Zhao, Z., Bevilacqua, V., and Figueroa, J.C. (2010). Voting-averaged combination method for regressor ensemble. Advanced Intelligent Computing Theories and Applications, Springer.","DOI":"10.1007\/978-3-642-14922-1_67"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Witten, I.H., Frank, E., Hall, M.A., and Pal, C.J. (2017). Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann.","DOI":"10.1016\/B978-0-12-804291-5.00010-6"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.jss.2015.01.028","article-title":"An empirical evaluation of ensemble adjustment methods for analogy-based effort estimation","volume":"103","author":"Azzeh","year":"2015","journal-title":"J. Syst. Softw."},{"key":"ref_49","first-page":"13","article-title":"Simple regression models","volume":"58","author":"Lichtenberg","year":"2016","journal-title":"Proc. Mach. Learn."},{"key":"ref_50","unstructured":"Upton, G., and Cook, I. (1996). Understanding Statistics, Oxford University Press."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Zwillinger, D., and Kokoska, S. (2000). CRC Standard Probability and Statistics Tables and Formulae, Chapman & Hall\/CRC Press.","DOI":"10.1201\/9780367802417"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1109\/TSE.2003.1245300","article-title":"A simulation study of the model evaluation criterion mmre","volume":"29","author":"Foss","year":"2003","journal-title":"IEEE Trans. Softw. Eng."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1049\/ip-sen:20010506","article-title":"What accuracy statistics really measure","volume":"148","author":"Kitchenham","year":"2001","journal-title":"IEE Proc. Softw."},{"key":"ref_54","unstructured":"Hardin, J., Hardin, J., Hilbe, J., and Hilbe, J. (2007). Generalized Linear Models and Extensions, Stata Press."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jhydrol.2009.08.003","article-title":"Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling","volume":"377","author":"Gupta","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1016\/j.infsof.2011.12.008","article-title":"Evaluating prediction systems in software project estimation","volume":"54","author":"Shepperd","year":"2012","journal-title":"Inf. Softw. Technol."},{"key":"ref_57","unstructured":"Kaiser, M., and Ullrich, C. (2014, January 9\u201311). Estimation accuracy in large is programs insights from a descriptive case study. Proceedings of the 22st European Conference on Information Systems, Tel Aviv, Israel."},{"key":"ref_58","unstructured":"Anderson, D.R., Sweeney, D.J., and William, T.A. (2009). Statistics for Business and Economics, Thomson South-Western, Cengage Learning. [14th ed.]."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Ross, A., and Willson, V.L.. (2017). Paired Samples t-Test. Basic and Advanced Statistical Tests, SensePublishers.","DOI":"10.1007\/978-94-6351-086-8"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.5194\/gmd-7-1247-2014","article-title":"Root mean square error (RMSE) or mean absolute error (MAE)?\u2014Arguments against avoiding RMSE in the literature","volume":"7","author":"Chai","year":"2014","journal-title":"Geosci. Model Dev."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Todros, K., and Tabrikian, J. (2010, January 13\u201318). On order relations between lower bounds on the MSE of unbiased estimators. Proceedings of the 2010 IEEE International Symposium on Information Theory, Austin, TX, USA.","DOI":"10.1109\/ISIT.2010.5513333"}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/11\/2\/15\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:06:02Z","timestamp":1760133962000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/11\/2\/15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,22]]},"references-count":61,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["computers11020015"],"URL":"https:\/\/doi.org\/10.3390\/computers11020015","relation":{},"ISSN":["2073-431X"],"issn-type":[{"value":"2073-431X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,22]]}}}