Corpus ID: 49574047

Optimizing Software Effort Estimation Models Using Firefly Algorithm

Published 2019

Computer Science, Mathematics

ArXiv

Software development effort estimation is considered a fundamental task for software development life cycle as well as for managing project cost, time and quality. Therefore, accurate estimation is a… Expand

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37 Citations

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37 Citations

Computer Science

2017 3rd International Conference on Science in Information Technology (ICSITech)

2017

TLDR

The use of Particle Swarm Optimization (PSO) algorithm in optimizing the COCOMO II model parameters is introduced and the method achieves well result and deals proficient with inexplicit data input and further improve a reliability of the estimation method. ExpandComputer Science

2017

TLDR

The influence of components and attributes is investigated and the use of Gaussian Membership Function (GMF) Fuzzy Logic and Multi-Objective Particle Swarm Optimization method (MOPSO) algorithms are introduced in calibrating and optimizing the COCOMO II model parameters to achieve new better accuracy improvement. Expand2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)

2017

The estimation of software effort is an essential and crucial activity for the software development life cycle. Software effort estimation is a challenge that often appears on the project of making a… Expand

Computer Science

2018

TLDR

This study examines the effect of the cost factor and scale factor in improving the accuracy of effort estimation and initialized using Particle Swarm Optimization (PSO) to optimize the parameters in a model of COCOMO II. ExpandComputer Science

2017

TLDR

A hybrid model of cuckoo search and harmony search algorithm for optimizing four coefficients of COCOMO-II to get optimal estimation is proposed and experimental results show that the proposed method is more effective in estimating effort and time development of the software project.ExpandComputer Science

2018

TLDR

Gaussian Membership Function of Fuzzy Logic and Multi-Objective Particle Swarm Optimization method of MOPSO method is introduced to use to calibrate and optimize the parameters of COCOMO II to achieve a new level of accuracy better. ExpandComputer Science

2020

TLDR

A three-phase hybrid approach is proposed to overcome the problem of application specific cost estimation in software development by using a combination of genetic algorithm and perceptron neural network. ExpandComputer Science

2018 International Seminar on Application for Technology of Information and Communication

2018

TLDR

The results show that the proposed model to optimize COCOMO II constants has the smallest value, which means its effort estimation has closer value of actual effort than that of the other methods which exist in the Turkish project dataset. ExpandComputer Science

IEEE Access

2021

TLDR

The proposed DNN model (GWDNNSB) using meta-heuristic algorithms for initial weights and learning rate selection, produced better results compared to existing work on using DNN for software effort estimation. ExpandComputer Science

2018

TLDR

This paper addresses the parameter estimation problem for a manufacturing process based on the Auto-Regressive Moving Average (ARMA) model and reveals that meta-heuristics can provide an outstanding modeling performance. Expand...

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References

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Engineering

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One of the most important effective factors the software companies face is the Software Cost Estimation (SCE) in software development process time. SCE is one of the subjects which have been… Expand

Computer Science

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)

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The use of Soft Computing Techniques is explored to build a suitable model structure to utilize improved estimations of software effort for NASA software projects to tune the parameters of the famous COnstructive COst MOdel (COCOMO). ExpandComputer Science

2006

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A modified version of the famous COCOMO model provided to explore the effect of the software development adopted methodology in effort computation and two new model structures to estimate the effort required for the development of software projects using Genetic Algorithms. Expand2010

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The combination of input features selection and parameters optimization of machine learning methods improves the accuracy of software development effort. ExpandComputer Science

2014

TLDR

The parameters of COCOMO II model is modified by introducing some more parameters to predict the software development effort more precisely and the performance of this parametric model is tested on the past PROMISE and NASA projects data set. ExpandComputer Science

Soft Comput.

2006

TLDR

This paper uses a preprocessing neuro-fuzzy inference system to handle the dependencies among contributing factors and decouple the effects of the contributing factors into individuals, and proposes a default algorithmic model that can be replaced when a better model is available. ExpandComputer Science

2011

TLDR

This paper empirically evaluates and compares the potential of Linear Regression, Artificial Neural Network, Decision Tree, Support Vector Machine and Bagging on software project dataset and shows that the performance of decision tree method is better than all the other compared methods. ExpandComputer Science

2010 10th International Conference on Intelligent Systems Design and Applications

2010

TLDR

The use of GP is explored to develop a software cost estimation model utilizing the effect of both the developed line of code and the used methodology during the development, and an application of estimating the effort for some NASA software projects is introduced. ExpandComputer Science

2010

TLDR

It has been shown that Simulated Annealing algorithm can be used to estimate the optimal parameters of the effort components of software projects.Expand2011

Project planning is one of the most important activities in software projects. Poor planning often leads to project faults and dramatic outcomes for the project team. If cost and effort are… Expand

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Optimizing Basic COCOMO Model Using Simplified Genetic Algorithm

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2016

Abstract The estimation of software effort is an essential and crucial activity for the software development life cycle....

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Firefly Algorithms for Multimodal Optimization

2009

Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a deta...

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37 Citations

25 References

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