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Analogy-based software effort estimation is a method to estimate the project cost of an unseen project based on analogies against previous projects sharing selected features. The validity of the selected features depends on many factors, and one of most crucial factors is the effectiveness of the datapreprocessing techniques applied to the datasets of the previous projects. In this paper, we report...
In software project management, software effort estimation is an important task. Software effort estimation will be helpful for finding the estimation of cost, duration of the project. In the recent time, many types of model are coming but among all, COCOMO model is widely used model. In past lots of Research have been done for correct and Accurate Effort Estimation. Many Algorithm has been applying...
Feature selection has been recently used in the area of software development effort estimation for improving the accuracy and robustness of prediction techniques. The idea behind selecting the most informative subset of features from a pool of available effort drivers stems from the hypothesis that reducing the dimensionality of datasets may significantly minimize the complexity and time required...
Software Cost estimation (SCE) is an important and necessary issue before starting any software project. Because before starting any software project, we must know the real needs of software implementation cost, required time, required manpower and etc. In fact, the purpose of SCE is that the estimated cost differs slightly with actual cost. Accurate estimation of software projects has been always...
Software effort estimation is amongst the most important tasks in software project management as many decisions like cost estimation, deadline of submitting of project and timely planning a project are dependent on it. Many models are available for effort estimation and most widely used is COCOMO Model. A lot of research work has been done for the correct and accurate use of effort estimation models...
Software cost estimation approximate judgment of the cost and time required to complete the project successfully. The cost estimation is usually measured in terms of effort. The Constructive Cost Model (COCOMO) is one of the most important model for software cost estimation. In this paper, soft computing techniques: genetic algorithm has been used for tuning the parameters of COCOMO model to predicate...
Bat Algorithm is one of the successful metaheuristic algorithms, which is used prominently for the purpose of optimization. But its inherent feature of non-changing parameters with the various iterations makes it less appropriate for optimization of software cost estimation techniques like COCOMO. So the current study proposes a hybrid model for the improvement of Bat algorithm by enhancing the search...
Software development cost estimation is an important activity in the early software design phases. The input datasets are primarily taken from the promise repository. Data mining and soft computing techniques are used to assess the software development cost estimation. Each feature in the input dataset is divided, the linguistic terms along with the membership are identified using trapezoidal membership...
This paper presents an efficient technique for frequency estimation in Electrical Power Systems (EPS) based on Genetic Algorithms (GAs). Frequency estimation of a distorted electrical signal is modeled as an optimization problem. The motivation concerning the use of the GA approach is related to its intrinsic robustness to noise. The GA is implemented in a FPGA (Field-Programmable Gate Array) device...
In modern utility computing infrastructures, like grids and clouds, one of the significant actions of a service provider is to predict the resources needed by the services included in its platform in an automated fashion for service provisioning optimization. Furthermore, a variety of software toolkits exist that implement an extended set of algorithms applicable to workload forecasting. However,...
There is still an urgent need of finding a mathematical model which can provide an accurate relationship between the software project effort/cost and the cost drivers. A powerful algorithm which can optimize such a relationship via developing a mathematical relationship between model variables is urgently needed. In this paper, we explore the use of GP to develop a software cost estimation model utilizing...
This paper presents a hybrid intelligent method to design Morphological-Rank-Linear (MRL) perceptrons to solve the Software Development Cost Estimation (SDCE) problem. The proposed method uses a modified genetic algorithm (MGA) to determine the best particular features to improve the MRL perceptron performance, as well as its initial parameters. Furthermore, for each individual of MGA, a gradient...
This paper proposes an optimal model of human resource allocation at the planning stage of software projects. Considering the different human resources demands required by different tasks and the characteristics of different human resources roles, this model realized the goal of assigning different team members to different tasks at the least cost under the conditions of satisfying the resource demand...
Accurate software effort estimation is essential for successful project management. To improve the accuracy, a number of estimation techniques have been developed. Among those, Analogy-Based Estimation (ABE) has become one of the mainstreams of effort estimation. In general, ABE infers the effort to accomplish a new project from the efforts of the historical projects which possess similar characteristics...
Estimating the amount of effort required for developing a software system is one of the most important project management concerns. This study successfully produces an optimal reduced linear model for software cost estimation by employing a series of methods of multiple regressions to identify the most significant explanatory variables of the fifteen COCOMO cost drivers. The results yielded by the...
This paper presents computational intelligence techniques for software cost estimation. We proposed a new recurrent architecture for genetic programming (GP) in the process. Three linear ensembles based on (i) arithmetic mean (ii) geometric mean and (iii) harmonic mean are implemented. We also performed GP based feature selection. The efficacy of these techniques viz multiple linear regression, polynomial...
Software cost estimation affects almost all activities of software project development such as: bidding, planning, and budgeting, thus it is very crucial to the success of software project management. In past decades, many methods have been proposed for cost estimation. Analogy based cost estimation (ABE) is among the most popular techniques due to its conceptual simplicity and empirical competitiveness...
Software organizations are putting efforts to improve the accuracy of the project cost estimation. This in turn helps them to allocate resources. Software cost estimation has been an area of key interest in software engineering community. Many estimation models divided among various categories have been proposed over a period of time. Function Point (FP) is one of the useful software cost estimation...
In the creation of a release plan developers must attempt to maximise business value while maintaining a high degree of certainty that the product will be completed on time and to budget. As a result of these constraints management is often forced to make the difficult decision as to which stories to complete and which to ignore. The difficulty of this decision is compounded by a high degree of uncertainty...
Software specification is an important element of the software development process. However, in most cases the specifications are out-of-date or even missing. One solution for this kind of problem is to use some process that infers the specification automatically. Work by Ernst et al (2000 ; 2002) has shown how specifications can be generated using program execution traces. These approaches are dependent...
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