Simplifying effort estimation based on Use Case Points

Ochodek, Mirosław; Nawrocki, Jerzy; Kwarciak, K.

doi:10.1016/j.infsof.2010.10.005

Cited by 130 publications

(104 citation statements)

References 29 publications

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“…Ever since, multiple recognized standards and public specifications were defined based on the notion of Functional Points. In parallel, other size-based estimation models emerged, such as Use Case Points [31] or story-based estimation in Agile techniques. While complex frameworks might yield precise results, they require experience that students lack and are frequently timeconsuming.…”

Section: A Defining Measurements Unitsmentioning

confidence: 99%

Measuring dimensions of Software Engineering projects' success in Academic context

Włodarski

Poniszewska-Marańda

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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Abstract-The notion of success is unsubstantial, complex and domain-specific. Software companies have been exploring its different aspects and aiming to put forward measures to capture and evaluate them. In this paper three main dimensions of success have been elicited based on previous industrial studies: project quality, project efficiency along with social factors and stakeholder's satisfaction. By investigation of their assessment criteria in commercial context a set of metrics and measures was determined and adapted to provide a structured evaluation approach for projects developed in academic setting. Professionalizing teaching and assessment process is an attempt to close a gap between workforce's expectations towards new graduates and the outcomes of their university education.

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Section: A Defining Measurements Unitsmentioning

confidence: 99%

Measuring dimensions of Software Engineering projects' success in Academic context

Włodarski

Poniszewska-Marańda

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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“…In this research, the Unadjusted Actor Weight (UAW) is neglected as suggested by Ochodek et al (2011) since the estimation accuracy will not be affected.…”

Section: Tablementioning

confidence: 99%

Towards an early software estimation using log-linear regression and a multilayer perceptron model

Nassif

Ho²,

Capretz

2013

Journal of Systems and Software

166

160

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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. a b s t r a c tSoftware estimation is a tedious and daunting task in project management and software development. Software estimators are notorious in predicting software effort and they have been struggling in the past decades to provide new models to enhance software estimation. The most critical and crucial part of software estimation is when estimation is required in the early stages of the software life cycle where the problem to be solved has not yet been completely revealed. This paper presents a novel log-linear regression model based on the use case point model (UCP) to calculate the software effort based on use case diagrams. A fuzzy logic approach is used to calibrate the productivity factor in the regression model. Moreover, a multilayer perceptron (MLP) neural network model was developed to predict software effort based on the software size and team productivity. Experiments show that the proposed approach outperforms the original UCP model. Furthermore, a comparison between the MLP and log-linear regression models was conducted based on the size of the projects. Results demonstrate that the MLP model can surpass the regression model when small projects are used, but the log-linear regression model gives better results when estimating larger projects.

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“…These enhancements cover the review and calibrating the productivity factor such as the work of Subriadi et al [5]. Another enhancement could be the construction investigation and simplification of the Use Case Points method presented by Ochodek et al [6]. The recent work of Silhavy et al [7] suggest a new approach " automatic complexity estimation based on requirements ", which is partly based on Use Case Points method.…”

Section: Related Workmentioning

confidence: 99%

Using improved analytical programming algorithm for effort estimation in software engineering

et al. 2016

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Abstract. This paper evaluates the usage of improved analytical programming algorithm for software effort estimation. The new model was generated by improved analytical programming and it was tested and compared with Karner's model to assess its properties. Least Absolute Deviation and random sub-sampling cross validation were used to assess the reliability to this experiment. The experimental results shows that the new model generated by analytical programming outperforms the Karner's equation about 40 %. Moreover, this work shows that improved analytical programming algorithm is feasible method for calibrating Use Case Points method. All results were evaluated by standard approach: visual inspection and statistical significance testing.

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Simplifying effort estimation based on Use Case Points

Cited by 130 publications

References 29 publications

Measuring dimensions of Software Engineering projects' success in Academic context

Measuring dimensions of Software Engineering projects' success in Academic context

Towards an early software estimation using log-linear regression and a multilayer perceptron model

Using improved analytical programming algorithm for effort estimation in software engineering

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