A comparative evaluation of effort estimation methods in the software life cycle

Popovic, Jovan; Bojic, Dragan

doi:10.2298/csis110316068p

Cited by 17 publications

(9 citation statements)

References 27 publications

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“…In general, only very few studies have empirically investigated the use of approximate size measures for the managerial task to estimate the development effort of a software system. Popovic et al [45], investigated the effectiveness of several FSM to predict effort estimation on 30 software projects, including also an approximation of NESMA. However, the main aim of this paper was to show the great potential of using functional measurement for effort prediction, able to achieve an estimate accuracy close or even better than accuracies found in the practice [45].…”

Section: Further Related Workmentioning

confidence: 99%

Assessing the effectiveness of approximate functional sizing approaches for effort estimation

Martino

Ferrucci

Gravino

et al. 2020

Information and Software Technology

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Context: Functional Size Measurement (FSM) methods, like Function Points Analysis (FPA) or COSMIC, are well-established approaches to estimate software size. Several approximations of these methods have been recently proposed as they require less time/information to be applied, however their effectiveness for effort prediction is not known. Objective: The effectiveness of approximated functional size measures for estimating the development effort is a key open question, since an approximate sizing approach may miss to capture factors affecting the effort. Therefore, we empirically investigated the use of approximate FPA and COSMIC sizing approaches, also compared with their standard versions, for effort estimation. Method: We measured 25 industrial software projects realised by a single company by using FPA, COSMIC, two approximate sizing approaches proposed by IFPUG for FPA (i.e. High Level and Indicative FPA), and three approximate sizing approaches proposed by the COSMIC organisation for COSMIC (i.e. Average Functional Process, Fixed Size Classification, and Equal Size Band). Then we investigated the quality of the regression models built using the obtained measures to estimate the development effort. Results: Models based on High Level FPA are effective, providing a prediction accuracy comparable to the one of the original FPA, while those based on the Indicative FPA method show poor estimation accuracy. Models based on COS-MIC approximate sizing methods are also quite effective, in particular those based on the Equal Size Band approximation provided an accuracy similar to the one of standard COSMIC. Conclusion: Project managers should be aware that predictions based on High Level FPA and standard FPA can be similar, making this approximation very interesting and effective, while Indicative FPA should be avoided. COSMIC approximations can also provide accurate effort estimates, nevertheless, the Fixed Size Classification and Equal Size Band approaches introduce subjectivity in

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Section: Further Related Workmentioning

confidence: 99%

Assessing the effectiveness of approximate functional sizing approaches for effort estimation

Martino

Ferrucci

Gravino

et al. 2020

Information and Software Technology

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“…Popović y Bojić indican que el mayor problema es la ausencia de un estándar que precisamente defina que es un caso de uso debido a que difieren de proyecto a proyecto (Popović & Bojić, 2012). Thomas y Remón indican que debido a las múltiples formas que existen para describir un caso de uso, el resultado del valor de los Puntos de Caso de Uso puede variar considerablemente aplicando contabilización por transacciones u escenarios (Thomas & Remón, 2011).…”

Section: Discusionesunclassified

Factores que Afectan la Precisión de la Estimación del Esfuerzo en Proyectos de Software Usando Puntos de Caso de Uso

Huanca

Oré²

2017

risti

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Resumen: El éxito de un proyecto de desarrollo de software depende de que el producto obtenido cumpla con las especificaciones del usuario y se termine dentro del plazo y con el presupuesto establecido. Muchos proyectos de software presentan el problema de no estar siendo desarrollados dentro del plazo planificado debido a una mala valoración del esfuerzo o duración del proyecto de software. La presente investigación tiene como objetivo determinar los factores que afectan la precisión de la estimación del esfuerzo en proyectos de software, usando Puntos de Caso de Uso como método de estimación. Un total de 37 estudios primarios fueron seleccionados. Los resultados muestran que los factores ambientales, la complejidad de los casos de uso, la falta de estandarización de los casos de uso, factores técnicos y contabilización de las transacciones son algunos de los factores que afectan la precisión del método de Puntos de Caso de Uso.Palabras-clave: Proyecto de Desarrollo de Software; Puntos de Caso de Uso; Estimación de esfuerzo. Factors Affecting the Accuracy of Effort Estimation in Software Projects Using Use Case PointsAbstract: The success of a software development project depends on that the retrieved product complies with the user's specifications and to be completed within the time and within the budget established. Many software projects show the problem about that they are not being developed within the time set due to a bad assessment of the effort or duration of the software project. This research has the objective of determining the factors that affect the accuracy of the effort estimation in software projects using the Use Case Points as estimation method. A total of 37 primarily studies were selected. The results show that the environmental factors, the use cases complexity, the lack of use case standardization, technical factors and counting transactions are some of the factors that affect the accuracy of the Use Case Points method.

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“…Project efforts are in the range from 2 to 14 person-months. The data set is an extension of 27 projects used in our previous research [10], where additional information about the data set can be found.…”

Section: Data Modelmentioning

confidence: 99%

“…In the past two decades, a number of researchers [6][7][8][9][10][11] thoroughly evaluated how effectively UCP size can be applied for estimating project effort. Therefore, research for the past couple of years focused on improving the UCP method using artificial intelligence (AI) techniques or modifications of UCP size [12][13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Analysis of task effort estimation accuracy based on use case point size

Popovic¹,

Bojic

Korolija

2015

IET softw.

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The use case point (UCP) method is one of the most commonly used size estimation methods in software development. Applicability of UCP size for the project effort estimation is thoroughly investigated; however, little attention is devoted to the effort estimation of particular task types. The authors have created and cross-compared prediction models for estimating task-type efforts by means of UCP size using an Online analytical processing model and R packages on a set of 32 real-world projects, with the goal of facilitating analysis of the correlation between project sizes and effort required to complete task types. Requirements, scoping, functional specification, and functional testing task types have up to two times better estimation accuracies than project effort. Implementation has slightly better accuracy than the project effort, while the other task types are not correlated to the UCP size. Using estimates of the most correlated task types and other techniques, such as expert judgment for others, we improved the overall project effort prediction accuracy and decreased the error from 26 to 16%.

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A comparative evaluation of effort estimation methods in the software life cycle

Cited by 17 publications

References 27 publications

Assessing the effectiveness of approximate functional sizing approaches for effort estimation

Assessing the effectiveness of approximate functional sizing approaches for effort estimation

Factores que Afectan la Precisión de la Estimación del Esfuerzo en Proyectos de Software Usando Puntos de Caso de Uso

Analysis of task effort estimation accuracy based on use case point size

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