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Business rules-driven semi-automatic project effort estimation

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Warianty tytułu
PL
Półautomatyczne estymowanie pracochłonności projektów sterowane regułami biznesowymi
Języki publikacji
EN
Abstrakty
EN
A new approach to project effort estimation is presented in this paper. It is related to Delphi method of estimation by experts. It also makes use of the business processes and business rules related to the newest OMG standards. A software tool implemented to verify the concept correctness is described.
PL
W artykule przedstawiono nowe podejście do estymowania pracochłonności projektów. Z jednej strony nawiązuje ono do metody Delphi estymowania przez niezależnych od siebie nawzajem ekspertów, a z drugiej strony, w ramach najnowszych standardów OMG, wykorzystuje procesy biznesowe oraz reguły biznesowe. Opisano również opracowane narzędzie stanowiące weryfikację poprawności koncepcji.
Rocznik
Strony
125--143
Opis fizyczny
Bibliogr. 36 poz., il.
Twórcy
autor
  • IBM/Rational Certified Consultant, Institute of Computer Science
autor
Bibliografia
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  • [3] Araújo R.A., Oliveira A.L.I., Soares S., A shift-invariant morphological system for software development cost estimation, Expert Systems with Applications 38, 2011, 4162-4168.
  • [4] Araújo R.A., Oliveira A.L.I., Soares S., Hybrid morphological methodology for software development cost estimation, Expert Systems with Applications 39, 2012, 6129-6139.
  • [5] Berlin S., Raz T., Glezer Ch., Zviran M., Comparison of estimation methods of cost and duration in IT projects, Information and Software Technology 51, 2009, 738-748.
  • [6] Boehm B. at al., Software Cost Estimation with Cocomo II, Prentice Hall, 2000.
  • [7] Børte K., Ludvigsen S.R., Mørch A.I., The role of social interaction in software effort estimation: Unpacking the "magic step " between reasoning and decision-making, Information and Software Technology xxx (2012) xxx-xxx (in press).
  • [8] Brown A.W., Boehm B., Software cost estimation in the incremental commitment model, Systems Research Forum Vol. 4, No. 1, 2010, 45-55.
  • [9] Choi S., Park S., Sugumaran V., A rule-based approach for estimating software development cost using function point and goal and scenario based requirements, Expert Systems with Applications 39, 2012, 406-418
  • [10] Cohn M., Agile Estimating and Planning, Prentice Hall, NJ, USA, 2005.
  • [11] Dalal S., Khodyakov D., Srinivasan R., Straus S., Adams J., ExpertLens: A system for eliciting opinions from a large pool of non-collocated experts with diverse knowledge, Technological Forecasting & Social Change 78, 2011, 1426-1444.
  • [12] Di Zio S., Pacinelli A., Opinion convergence in location: A spatial version of the Delphi method, Technological Forecasting & Social Change 78, 2011, 1565-1578.
  • [13] Ding Sh., Yang Sh.-Lin, Fu Ch., A novel evidential reasoning based method for software trustworthiness, evaluation under the uncertain and unreliable environment, Expert Systems with Applications 39, 2012, 2700-2709.
  • [14] El-Sebakhy E.A., Functional networks as a novel data mining paradigm in forecasting software development efforts, Expert Systems with Applications 38, 2011, 2187-2194.
  • [15] Goluchowicz K., Blind K., Identification of future fields of standardisation: An explorative application of the Delphi methodology, Technological Forecasting & Social Change 78, 2011, 1526-1541.
  • [16] Grimstad St., Jørgensen M., Moløkken-Østvold K., Information and Software Technology 48, 2006, 302-310.
  • [17] Heričko M., Živkovič A., The size and effort estimates in iterative development, Information and Software Technology 50, 2008, 772-781.
  • [18] Jørgensen M., Boehm B., Software Development Effort Estimation: Formal Models or Expert Judgment?, IEEE Software, march/april 2009, 14-19.
  • [19] Jørgensen M., Contrasting ideal and realistic conditions as a means to improve judgment-based software development effort estimation, Information and Software Technology 53, 2011, 1382-1390.
  • [20] Jørgensen M., Selection of strategies in judgment-based effort estimation, The Journal of Systems and Software 83, 2010, 1039-1050.
  • [21] Jørgensen M., Shepperd M., A systematic review of software development cost estimation studies, IEEE Transactions on Software Engineering 33 (1) 2007, 35-53.
  • [22] Klęk P., Estymacja projektów informatycznych z wykorzystaniem silnika reguł biznesowych, praca magisterska, Wydział Fizyki, Matematyki i Informatyki Politechniki Krakowskiej, marzec 2012.
  • [23] Koch St., Effort modeling and programmer participation in open source software projects, Information Economics and Policy 20, 2008, 345-355.
  • [24] Koch St., Mitlöhner J., Software project effort estimation with voting rules, Decision Support Systems 46, 2009, 895-901.
  • [25] Muzaffar Z., Ahmed M.A., Software development effort prediction: A study on the factors impacting the accuracy of fuzzy logic systems, Information and Software Technology 52, 2010, 92-109.
  • [26] Ochodek M., Nawrocki J., Kwarciak K., Simplifying effort estimation based on Use Case Points, Information and Software Technology 53, 2011, 200-213.
  • [27] Palmer S.R., Felsing M., A Practical Guide to Feature-Driven Development, Pearson Education, 2001.
  • [28] Pendharkar P.C., Probabilistic estimation of software size and effort, Expert Systems with Applications 37, 2010, 4435-4440.
  • [29] Petersen K., Measuring and predicting software productivity: A systematic map and review, Information and Software Technology 53, 2011, 317-343.
  • [30] Song Q., Shepperd M., Predicting software project effort: A grey relational analysis based method, Expert Systems with Applications 38, 2011, 7302-7316.
  • [31] Szöke Á., Conceptual scheduling model and optimized release scheduling for agile environments, Information and Software Technology 53, 2011, 574-591.
  • [32] Tavana M., Pirdashti M., Kennedy D.T., Belaud J.-P., Behzadian M., A hybrid Delphi-SWOT paradigm for oil and gas pipeline strategie planning in Caspian Sea basin, Energy Policy 40, 2012, 345-360.
  • [33] Verner J.M., Evanco W.M., Cerpa N., State of the practice: An exploratory analysis of schedule estimation and software project success prediction, Information and Software Technology 49, 2007, 181-193.
  • [34] Wang X., Gao Zh., Guo H., Uncertain hypothesis testing for two experts' empirical data, Mathematical and Computer Modelling 55, 2012, 1478-1482.
  • [35] Wena J., Li Sh., Lin Zh., Huc Y., Huang Ch., Systematic literature review of machine learning based software development effort estimation models, Information and Software Technology 54, 2012, 41-59.
  • [36] Yannibelli V., Amandi A., A knowledge-based evolutionary assistant to software development project scheduling, Expert Systems with Applications 38, 2011, 8403-8413.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c21481a8-a4cb-4e34-9902-181029b2b4c7
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