Show simple item record

dc.contributor.authorvan Koten, Chikakoen_NZ
dc.date.available2011-04-07T03:06:44Z
dc.date.copyright2003-11en_NZ
dc.identifier.citationvan Koten, C. (2003, November). An effort prediction model for data-centred fourth-generation-language software development (Thesis No. 2003/04). University of Otago. Retrieved from http://hdl.handle.net/10523/1136en
dc.identifier.urihttp://hdl.handle.net/10523/1136
dc.description.abstractAccurate effort prediction is often an important factor for successful software development. However, the diversity of software development tools observed today has resulted in a situation where existing effort prediction models’ applicability appears to be limited. Data-centred fourth-generation-language (4GL) software development provides one such difficulty. This paper aims to construct an accurate effort prediction model for data-centred 4GL development where a specific tool suite is used. Using historical data collected from 17 systems developed in the target environment, several linear regression models are constructed and evaluated in terms of two commonly used prediction accuracy measures, namely the mean magnitude of relative error (MMRE) and pred measures. In addition, R2, the maximum value of MRE, and statistics of the absolute residuals are used for comparing the models. The results show that models consisting of specification-based software size metrics, which were derived from Entity Relationship Diagrams (ERDs) and Function Hierarchy Diagrams (FHDs), achieve good prediction accuracy in the target environment. The models’ good effort prediction ability is particularly beneficial because specification-based metrics usually become available at an early stage of development. This paper also investigates the effect of developers’ productivity on effort prediction and has found that inclusion of productivity improves the models’ prediction accuracy further. However, additional studies will be required in order to establish the best productivity inclusive effort prediction model.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subjectprediction systemsen_NZ
dc.subject4GLen_NZ
dc.subjectefforten_NZ
dc.subjectmetricsen_NZ
dc.subjectempirical analysisen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleAn effort prediction model for data-centred fourth-generation-language software developmenten_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages12en_NZ
otago.date.accession2006-02-22en_NZ
otago.schoolInformation Scienceen_NZ
thesis.degree.levelHonours Thesesen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints265en_NZ
otago.school.eprintsSoftware Metrics Research Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
dc.description.referencesAlbrecht, A.J. and Gaffney JR., J.E. (1983): Software function, source lines of code, and development effort prediction: a software science validation. IEEE Transactions on Software Engineering SE-9(6):639-648. Basili, V.R. and Weiss, D.M. (1984): A methodology for collecting valid software engineering data. IEEE Transactions on Software Engineering SE-10(6):728-738. Basili, V.R. and Rombach, H.D. (1988): The TAME project: towards improvement-oriented software environments. IEEE Transactions on Software Engineering 14(6):758-773. Boehm, B.W. (1981): Software Engineering Economics. Englewood Cliffs, NJ, Prentice-Hall. Boehm, B.W. (1984): Software engineering economics. IEEE Transactions on Software Engineering 10(1):4-21. Conte, S.D., Dunsmore, H.E. and Shen, V.Y. (1986): Software Engineering Metrics and Models. Menlo Park, CA, Benjamin/Cummings Publishing Company. Dolado, J.J. (1997): A study of the relationships among Albrecht and Mark II Function Points, lines of code 4GL and effort. Journal of Systems Software 37:161-173. Dolado, J.J. (2000): A validation of the component-based method for software size estimation. I E E E Transactions on Software Engineering 26(10):1006-1021. Fenton, N.E. and Pfleeger, S.L. (1997): Software Metrics: A Rigorous & Practical Approach. Boston, MA, PWS Publishing Company. Glass, R.L. (2001): Frequently forgotten fundamental facts about Software Engineering. IEEE Software (May/June 2001):110-112. Kemerer, C.F. (1987): An empirical validation of software cost estimation models. Communications of the ACM 30(5):416-429. Kitchenham, B.A., Pickard, L.M., MacDonell, S.G. and Shepperd, M.J. (2001): What accuracy statistics really measure. IEE Proceedings-Software 148(3):81-85. MacDonell, S.G. (1997): Establishing relationships between specification size and software process effort in CASE environment. Information and Software Technology 39:35-45. MacDonell, S.G., Shepperd, M.J. and Sallis, P.J. (1997): Metrics for database systems: an empirical study. Proc. the 4th International Software metrics Symposium (METRICS’97), Albuquerque, NM, 99-107, IEEE Computer Society Press. MacDonell, S.G. (2003): Software source code sizing using fuzzy logic modelling. Information and Software Technology, 45: 389-404. Oivo, M. and Basili, V.R. (1992): Representing software engineering models: the TAME goal oriented approach. IEEE Transactions on Software Engineering 18(10):886-897. Shepperd, M. J., Cartwright, M. and Kadoda, G. (2000): On building prediction systems for software engineers. Empirical Software Engineering, 5:175-182. Tate, G. and Verner, J.M. (1990): Software sizing and costing models: a survey of empirical validation and comparison studies. Journal of Information Technology 5:12-26. Tate, G. and Verner, J.M. (1991): Approaches to measuring size of application products with CASE tools. Information and Software Technology 33(9):622-628. Verner, J.M. and Tate, G. (1988): Estimating size and effort in fourth-generation development. IEEE Software (July 1988):15-22. Verner, J.M. and Tate, G. (1992): A software size model. IEEE Transactions on Software Engineering 18(4): 265-278. Wrigley, C.D. and Dexter, A.S. (1991): A model for measuring information system size. MIS Quarterly 15:245-257.en_NZ
otago.relation.number2003/04en_NZ
 Find in your library

Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record