A literature review of expert problem solving using analogy

We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of non-trivial problems. We identified twelve studies. These studies suggest that analogical reasoning plays an important role in problem solving, but that CBR tools do not model this in a biologically plausible way. For example, the ability to induce structure and therefore find deeper analogies is widely seen as the hallmark of an expert. However, CBR tools fail to provide support for this type of reasoning for prediction. We conclude this mismatch between experts’ cognitive processes and software tools contributes to the erratic performance of analogy-based prediction

Software Effort Prediction - A Fuzzy Logic Approach

Accuracy in the estimation of software Effort/Cost is one of the desirable criteria for any software cost estimation model. The estimation of effort or cost before the actual development of any software is the most crucial task of the present day software development project managers. Software project attributes are often measured in terms of linguistic values such as very low, low, Average, high and very high. The imprecise nature of such attributes constitutes uncertainty and vagueness in their subsequent interpretation. In this paper we propose a Fuzzy logic based model for software effort prediction. We feel that fuzzy Software cost estimation Model should be able to deal with imprecision and uncertainty associated with various parameter values. Fuzzy analogy model has been developed and validated upon student data

A Neuro Fuzzy Algorithm to Compute Software Effort Estimation

Software Effort Estimation is highly important and considered to be a primary activity in software project management The accurate estimates are conducted in the development of business case in the earlier stages of project management This accurate prediction helps the investors and customers to identify the total investment and schedule of the project The project developers define process to estimate the effort more accurately with the available mythologies using the attributes of the project The algorithmic estimation models are very simple and reliable but not so accurate The categorical datasets cannot be estimated using the existing techniques Also the attributes of effort estimation are measured in linguistic values which may leads to confusion This paper looks in to the accuracy and reliability of a non-algorithmic approach based on adaptive neuro fuzzy logic in the problem of effort estimation The performance of the proposed method demonstrates that there is a accurate substantiation of the outcomes with the dataset collected from various projects The results were compared for its accuracy using MRE and MMRE as the metrics The research idea in the proposed model for effort estimation is based on project domain and attribute which incorporates the model with more competence in augmenting the crux of neural network to exhibit the advances in software estimatio

Software Cost Estimation using Function Point with Non Algorithmic Approach

Cost estimation is one of the most challenging tasks in project management. It is to accurately estimate needed resources and required schedules for software development projects. The software estimation process includes estimating the size of the software product to be produced, estimating the effort required, developing preliminary project schedules, and finally, estimating overall cost of the project. Nearly one-third projects over run their budget and late delivered and two-thirds of all major projects substantially over run their original estimates. Effort is a function of size. For estimating effort first we face sizing problem. In direct approach size is measured in lines of code (LOC). In indirect approach, size is represented as Function Points (FP). In this paper we use both approach with different technique

Software Effort Estimation using Neuro Fuzzy Inference System: Past and Present

Most important reason for project failure is poor effort estimation. Software development effort estimation is needed for assigning appropriate team members for development, allocating resources for software development, binding etc. Inaccurate software estimation may lead to delay in project, over-budget or cancellation of the project. But the effort estimation models are not very efficient. In this paper, we are analyzing the new approach for estimation i.e. Neuro Fuzzy Inference System (NFIS). It is a mixture model that consolidates the components of artificial neural network with fuzzy logic for giving a better estimation

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

Function Points Analysis (FPA) is amongst the most generally used method to assess software cost estimation frameworks. This process speaks to the measurement of an undertaking, application, and function by its relative functional complexity. In general, it has numerous effective applications used in both industry and scholarly research. This is noticed that customized estimate technologies which can confront genuine challenges utilizing on programming building information is normally constrained, loosely gathered and deficient. To enquire these queries composite programming models, blend of information, fuzzy logic and master judgment is proposed. This is trusted that outcomes announced here will animate, renew investigation of fuzzy logic to genuine programming designing issues. In this research paper, we use Function Points and apply some new models to pick up a superior estimation of programming properties. The utilization of ideas and characteristics from the fuzzy set hypothesis to stretch out function points analysis to fuzzy function points analysis. Fuzzy hypothesis tries to construct formal quantitative arrangement equipped for imitating imprecision of the human information. With the function points created by Fuzzy FPA, an estimate value for example, expenses/cost and software development can be more correctly determined