Optimizing Non-orthogonal Space Distance Using PSO in Software Cost Estimation

Qin, Liu; Chu, Xiaoyuan; Xiao, Jiakai; Zhu, Hongming

doi:10.1109/compsac.2014.9

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…After that, Liu et al attempted to use PSO to improve the estimation by minimizing errors in the training of datasets. They performed this task by optimizing non-orthogonal space distance (NoSD) according to the PSO algorithm [41]. In 2016, Azzeh et al [42] stated in a study that three decision-making variables affect the successfulness of estimation, i.e., the number of the nearest projects (k), the set of required optimal features for adaptation, and weights compliance.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Analogy-based Software Cost Estimation using Gray Wolf Optimization Algorithm

Gandomani,

Ansaripour,

Dashti

2024

Preprint

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Human effort is considered one of the most important factors for a better estimation of software development costs. Therefore, the cost of software product development is usually seen based on the amount of effort required for its development. Numerous methods and paradigms are provided for software project estimation. The analogy-based method is one of the simplest and most prevalent methods. There have been many attempts to improve this method, yet, it seems it still can be improved. This research aims to provide a novel model and make use of the gray wolf optimization algorithm inside the similarity function to enhance the analogy-based software development cost. The provided method is compared to four metaheuristic and evolutionary algorithms using four prominent datasets. The evaluation results according to the MMRE, MdMRE, and PRED (0.25) indicate the proposed method provides a higher precision in estimating the analogy-based software development cost.

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Section: Related Workmentioning

confidence: 99%

Enhancing Analogy-based Software Cost Estimation using Gray Wolf Optimization Algorithm

Gandomani,

Ansaripour,

Dashti

2024

Preprint

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“…Wu et al applied the PSO algorithm for feature weight optimization in the predefined similarity measure of the software estimation approach [57]. Liu, et al used PSO to reduce errors during the training phase and enhance estimation [58]. Azzeh, et al [2] utilized the PSO algorithm to identify the optimum decision variable where the trade-off between several evaluation metrics is illustrated.…”

Section: Related Workmentioning

confidence: 99%

Weight Optimization Based on Firefly Algorithm for Analogy-based Effort Estimation

AlMutlaq¹,

Jawawi²,

Arbain³

2023

IJACSA

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Proper cost estimation is one of the vital tasks that must be achieved for software project development. Owing to the complexity and uncertainties of the software development process, this task is ambiguous and difficult. Recently, analogybased estimation (ABE) has become one of the popular approaches in this field due to its effectiveness and practicability in comparing completed projects and new projects in estimating the development effort. However, in spite of its many achievements, this method is not capable to guarantee accurate estimation confronting the complex relation between independent features and software effort. In such a case, the performance of the ABE can be improved by efficient feature weighting. This study introduces an enhanced software estimation method by integrating the firefly algorithm (FA) with the ABE method for improving software development effort estimation (SDEE). The proposed model can provide accurate identification of similar projects by optimising the performances of the similarity function in the estimation process in which the most relevant weights are assigned to project features for obtaining the more accurate estimates. A series of experiments were carried out using six real-world datasets. The results based on the statistical analysis showed that the integration of the FA and ABE significantly outperformed the existing analogy-based approaches especially for the ISBSG dataset.

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“…The analogy-based estimation has been widely used to enhance the accuracy of software cost estimation. Using optimization algorithms, especially swarm intelligence, has been recommended by many researchers in order to improve the accuracy of software development estimation ( Liu et al, 2014 ; Satapathy, Acharya & Rath, 2016 ).…”

Section: Related Workmentioning

confidence: 99%

LEMABE: a novel framework to improve analogy-based software cost estimation using learnable evolution model

Dashti

Gandomani

Adeh

et al. 2022

PeerJ Computer Science

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One of the most important and critical factors in software projects is the proper cost estimation. This activity, which has to be done prior to the beginning of a project in the initial stage, always encounters several challenges and problems. However, due to the high significance and impact of the proper cost estimation, several approaches and methods have been proposed regarding how to perform cost estimation, in which the analogy-based approach is one of the most popular ones. In recent years, many attempts have been made to employ suitable techniques and methods in this approach in order to improve estimation accuracy. However, achieving improved estimation accuracy in these techniques is still an appropriate research topic. To improve software development cost estimation, the current study has investigated the effect of the LEM algorithm on optimization of features weighting and proposed a new method as well. In this research, the effectiveness of this algorithm has been examined on two datasets, Desharnais and Maxwell. Then, MMRE, PRED (0.25), and MdMRE criteria have been used to evaluate and compare the proposed method against other evolutionary algorithms. Employing the proposed method showed considerable improvement in estimating software cost estimation.

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Optimizing Non-orthogonal Space Distance Using PSO in Software Cost Estimation

Cited by 8 publications

References 12 publications

Enhancing Analogy-based Software Cost Estimation using Gray Wolf Optimization Algorithm

Enhancing Analogy-based Software Cost Estimation using Gray Wolf Optimization Algorithm

Weight Optimization Based on Firefly Algorithm for Analogy-based Effort Estimation

LEMABE: a novel framework to improve analogy-based software cost estimation using learnable evolution model

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