نتایج جستجو برای: software cost estimation sce
تعداد نتایج: 1033825 فیلتر نتایج به سال:
Software projects mostly exceeds budget, delivered late and does not meet with the customer’s satisfaction for years. In the past, many traditional development models like waterfall, spiral, iterative, and prototyping methods are used to build the software systems. In recent years, agile models are widely used in developing the software products. The major reasons are – simplicity, incorporatin...
-In software industry Constructive Cost Model (COCOMO) is considered to be the most widely used model for effort estimation. Cost drivers have significant influence on the COCOMO and this research investigates the role of cost drivers in improving the precision of effort estimation. It is important to stress that uncertainty at the input level of the COCOMO yields uncertainty at the output, whi...
This paper examines how a team of software professionals goes about estimating the effort of a software project using a judgment-based, bottom-up estimation approach. By employing a social practice perspective that highlights the distributed character of expertise and conceives actions as mediated by cultural tools, the paper analyzes the interactional process through which the estimation tasks...
Accurate estimation of software development effort needs to consider numerous factors in software projects such as project size, programming language, application type, team size, development platform and so on. Software methodology is one of the most effective parameters in this field. Basically, software methodologies are used in software projects in order to manage activities, artifacts, rol...
Software effort estimates is an important part of software development work and provides essential input to project feasibility analyses, bidding, budgeting and planning. Analogy-based estimates models emerge as a promising approach, with comparable accuracy to arithmetic methods, and it is potentially easier to understand and apply. Studies show all the models are sensitive to the quality and ...
This paper exemplifies how better knowledge about human judgement strategies known as heuristics can be used to improve software processes, especially estimation and prediction processes. Human judgement heuristics work well when they exploit a fit between their structure and the structure of the environment in which they are used. This use of environmental fit may lead to amazingly good judgem...
Software cost estimation is known to be a challenging task at best, and these challenges are increased for programmers operating outside the support of an established team programming environment. While many software cost estimation models exist with varying levels of support, the nature of metrics collected for these models is seldom applicable to the solitary programmer. In addition, the work...
Software effort estimation is still a significant challenge for software management. Although Functional Size Measurement (FSM) methods have been standardized and have become widely used by the software organizations, the relationship between functional size and development effort still needs further investigation. Most of the studies focus on the project cost drivers and consider total softwar...
The effort invested in a software project is one of the most challenging task and most analyzed variables in recent years in the process of project management. Software cost estimation predicts the amount of effort and development time required to build a software system. It is one of the most critical tasks and it helps the software industries to effectively manage their software development p...
Software effort estimation requires high accuracy, but accurate estimations are difficult to achieve. Increasingly, data mining is used to improve an organization’s software process quality, e.g. the accuracy of effort estimations .There are a large number of different method combination exists for software effort estimation, selecting the most suitable combination becomes the subject of resear...
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