scholarly journals Improving Software Cost Estimation With Function Points Analysis Using Fuzzy Logic Method

2020 ◽  
Vol 1 (1) ◽  
Keyword(s):  
Fuzzy Logic ◽  
Cost Estimation ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Function Points ◽  
Fuzzy Logic Method ◽  
Logic Method

scholarly journals A Modification Complexity Factor in Function Points Method for Software Cost Estimation Towards Public Service Application

2017 ◽  
Vol 124 ◽  
pp. 415-422 ◽  
Author(s):  
Renny Sari Dewi ◽  
Apol Pribadi Subriadi ◽  
Sholiq
Keyword(s):  
Public Service ◽  
Cost Estimation ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Function Points ◽  
Service Application

scholarly journals EFFORT ESTIMATION MODELING OF E-GOVERNMENT APPLICATION DEVELOPMENT USING FUNCTION POINTS BASED ON TOR AND SRS DOCUMENT

2020 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Noorlela Marcheta
Keyword(s):  
Cost Estimation ◽  
Functional System ◽  
Effort Estimation ◽  
Software Cost Estimation ◽  
Application Development ◽  
Cost Estimates ◽  
Software Cost ◽  
Information Systems Management ◽  
Function Points ◽  
Requirements Specifications

Software cost estimation is important for information systems management and is generally taught in software engineering courses especially to terms of the ever-increasing development of E-Government. A significant challenge for Software Sizing (SS) is to determine cost estimates based on TOR documents that do not yet contain complete Software Requirements Specifications (SRS). This study uses Function Points as one of the measurement methods that can make cost estimates and expert needs based on the desired functional system. On the other hand, there are cases where estimation needs after the SRS document have been made. Thus in this study, the authors discuss the implementation of SS based on TOR and SRS documents for E-Government. The results of this study indicate the closeness of the actual and estimated values of 81.9% for TOR and 93.4% for SRS.

Analysis of Software Cost Estimation Using Fuzzy Logic

2014 ◽  
Vol 4 (3) ◽  
pp. 27-41 ◽  
Author(s):  
Isa Maleki ◽  
Laya Ebrahimi ◽  
Saman Jodati ◽  
Iraj Ramesh
Keyword(s):  
Fuzzy Logic ◽  
Cost Estimation ◽  
Software Cost Estimation ◽  
Software Cost

Fuzzy Logic Based Support Vector Regression (SVR) Model for Software Cost Estimation Using Machine Learning

2022 ◽  
pp. 917-927
Author(s):  
Kamal Upreti ◽  
Umesh Kumar Singh ◽  
Rituraj Jain ◽  
Karamjeet Kaur ◽  
A. K. Sharma
Keyword(s):  
Machine Learning ◽  
Fuzzy Logic ◽  
Support Vector Regression ◽  
Cost Estimation ◽  
Support Vector ◽  
Software Cost Estimation ◽  
Software Cost

scholarly journals Software Cost Estimation using Fuzzy Logic Technique

2017 ◽  
Vol 10 (3) ◽  
Author(s):  
Ravneet Preet Singh Bedi ◽  
Amardeep Singh
Keyword(s):  
Fuzzy Logic ◽  
Cost Estimation ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Fuzzy Logic Technique

A HYBRID SOFTWARE COST ESTIMATION APPROACH UTILIZING DECISION TREES AND FUZZY LOGIC

2012 ◽  
Vol 22 (03) ◽  
pp. 435-465 ◽  
Author(s):  
EFI PAPATHEOCHAROUS ◽  
ANDREAS S. ANDREOU
Keyword(s):  
Fuzzy Logic ◽  
Decision Trees ◽  
Cost Estimation ◽  
Development Effort ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Tree Structures ◽  
Fuzzy Implication ◽  
Development Cycle ◽  
Public Data

Software cost estimation (SCE) is one of the critical activities in software project management. During the past decades various models have been proposed for SCE. However, developing accurate and useful models is limited in practice despite the considerable financial gain they could offer to software stakeholders. Traditional techniques, such as regression, by-analogy and machine learning, face the difficulty of handling the dynamic nature of the software process and the problematic nature of the public data available. This paper addresses the issue of SCE proposing an alternative approach that combines robust decision tree structures with fuzzy logic. Fuzzy decision trees are generated using the CHAID and CART algorithms in a systematic manner, while development effort is treated as the dependent variable against two subsets of factors: The first contains selected attributes from the ISBSG, COCOMO and DESHARNAIS datasets and the second contains a subset of the available factors that can be measured early in the development cycle. The association rules obtained from the trees are then merged and defuzzified through a Fuzzy Implication System (FIS). The fuzzy framework is utilized to perform effort estimations. Experimental results indicate that the proposed approach is promising as it yields quite accurate estimations in most dataset cases considered. Finally, our evaluation suggests that accurate estimations may be produced, even when using only a small set of factors that can be measured early in the development cycle, thus increasing the practical value of the proposed cost model.

scholarly journals A Novel Fuzzy Model for Software Cost Estimation

2020 ◽  
Vol 9 (4) ◽  
pp. 111-119
Keyword(s):  
Fuzzy Logic ◽  
Cost Estimation ◽  
Fuzzy Model ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Hybrid Techniques ◽  
Development Life Cycle ◽  
Specific Order ◽  
The Neural Networks ◽  
Evolution Computation

It predicts the estimated cost at beginning periods of development life cycle is a challenging assignment for the powerful management of any software industry. This model essentially considered on the significance of the datasets was utilized for analysis, kinds of intelligence and Fuzzy Logic were applied to foresee estimated cost lastly, execution assessed of prediction methods. From our model, we found that the COCOMO dataset is the most conspicuous dataset, trailed by NASA, and DESHARNAIS dataset. The MARE and MMRE are noticeable execution assessment methods in the field of study. Further, we found that the Neural Networks technique was repetitively utilized when contrasted with different models pursued by the Hybrid techniques, at that point Fuzzy Logic, Decision Tree and Evolution Computation in a specific order. This model is serving to incredible for research apprentices in the arena of software cost Estimation.

Software cost estimation using fuzzy logic

2010 ◽  
Vol 35 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Anish Mittal ◽  
Kamal Parkash ◽  
Harish Mittal
Keyword(s):  
Fuzzy Logic ◽  
Cost Estimation ◽  
Software Cost Estimation ◽  
Software Cost
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