SEffEst: Effort estimation in software projects using fuzzy logic and neural networks

González‐Carrasco, Israel; Colomo‐Palacios, Ricardo; López-Cuadrado, José Luis; García-Peñalvo, Francisco José

doi:10.1080/18756891.2012.718118

Cited by 15 publications

(8 citation statements)

References 65 publications

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“…Software effort estimation is vital task for successful software project management [12,13]. ABE method has been widely used for developing software effort estimation models based upon retrieval by similarity [14][15][16].…”

Section: Related Workmentioning

confidence: 99%

Analogy‐based effort estimation: a new method to discover set of analogies from dataset characteristics

Azzeh

Nassif

2015

IET softw.

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Analogy-based effort estimation (ABE) is one of the efficient methods for software effort estimation because of its outstanding performance and capability of handling noisy datasets. Conventional ABE models usually use the same number of analogies for all projects in the datasets in order to make good estimates. The authors' claim is that using same number of analogies may produce overall best performance for the whole dataset but not necessarily best performance for each individual project. Therefore there is a need to better understand the dataset characteristics in order to discover the optimum set of analogies for each project rather than using a static k nearest projects. The authors propose a new technique based on bisecting k-medoids clustering algorithm to come up with the best set of analogies for each individual project before making the prediction. With bisecting k-medoids it is possible to better understand the dataset characteristic, and automatically find best set of analogies for each test project. Performance figures of the proposed estimation method are promising and better than those of other regular ABE models.

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Section: Related Workmentioning

confidence: 99%

Analogy‐based effort estimation: a new method to discover set of analogies from dataset characteristics

Azzeh

Nassif

2015

IET softw.

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“…There are several libraries for different tasks such as FADAlib [117], which is a C++ library that implements the Fuzzy Array Dataflow Analysis (FADA) method. Many toolboxes can also be found, among which are the following: MRES [118] is a toolbox for selecting resources in software project management; CMMI-ASS [119] is developed to help self-assessment software companies to accomplish the appraisal process; SEffEst [120] combines fuzzy logic and neural networks for effort estimation in software projects; etc.…”

Section: Fuzzy Systems Software To Support Software Engineeringmentioning

confidence: 99%

A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects

Alcalá‐Fdez

Alonso

2016

IEEE Trans. Fuzzy Syst.

106

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Fuzzy systems have been used widely thanks to their ability to successfully solve a wide range of problems in different application fields. However, their replication and application requires a high level of knowledge and experience. Furthermore, few researchers publish the software and/or source code associated with their proposals, which is a major obstacle to scientific progress in other disciplines and in industry. In recent years, most fuzzy system software has been developed in order to facilitate the use of fuzzy systems. Some software is commercially distributed but most software is available as free and open source software, reducing such obstacles and providing many advantages: quicker detection of errors, innovative applications, faster adoption of fuzzy systems, etc. In this paper, we present an overview of freely available and open source fuzzy systems software in order to provide a well-established framework that helps researchers to find existing proposals easily and to develop well founded future work. To accomplish this, we propose a twolevel taxonomy and we describe the main contributions related to each field. Moreover, we provide a snapshot of the status of the publications in this field according to the ISI Web of Knowledge. Finally, some considerations regarding recent trends and potential research directions are presented.

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“…Two of the three most important causes of Information Technology projects failure have been related to a poor resource estimation (González-Carrasco et al, 2012). In average, software developers expend from 30% to 40% more effort than is estimated (Jørgensen & Shepperd, 2007).…”

Section: Introductionmentioning

confidence: 99%

Applying Absolute Residuals as Evaluation Criterion for Estimating the Development Time of Software Projects by Means of a Neuro-Fuzzy Approach

García-Díaz

Verduzo-Ramirez

Garcia-Virgen

et al. 2016

Journal of Information Systems Engineering & Management

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In the software development field, software practitioners expend between 30% and 40% more effort than is predicted. Accordingly, researchers have proposed new models for estimating the development effort such that the estimations of these models are close to actual ones. In this study, an application based on a new neurofuzzy system (NFS) is analyzed. The NFS accuracy was compared to that of a statistical multiple linear regression (MLR) model. The criterion for evaluating the accuracy of estimation models has mainly been the Magnitude of Relative Error (MRE), however, it was recently found that MRE is asymmetric, and the use of Absolute Residuals (AR) has been proposed, therefore, in this study, the accuracy results of the NFS and MLR were based on AR. After a statistical paired t-test was performed, results showed that accuracy of the New-NFS is statistically better than that of the MLR at the 99% confidence level. It can be concluded that a new-NFS could be used for predicting the effort of software development projects when they have been individually developed on a disciplined process.

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SEffEst: Effort estimation in software projects using fuzzy logic and neural networks

Cited by 15 publications

References 65 publications

Analogy‐based effort estimation: a new method to discover set of analogies from dataset characteristics

Analogy‐based effort estimation: a new method to discover set of analogies from dataset characteristics

A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects

Applying Absolute Residuals as Evaluation Criterion for Estimating the Development Time of Software Projects by Means of a Neuro-Fuzzy Approach

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