Evaluation of Convertibility Issues Between IFPUG and Cosmic Function Points
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 6
Abstract
Abstract: Software industry has matured with time, from small application of few lines of codes to software application of millions of lines of code. In the past few years, the concern of the industry regarding software size estimation has been the convertibility issue between the International Function Point User Group (IFPUG) and the COmmon Software Measurement International Consortium (COSMIC) in order to leverage their huge investment on the IFPUG. Since there is still no cost and effort estimation tool for COSMIC function points. IFPUG is one of the early estimation methods, however, with the introduction of a more scientific method like COSMIC which has a wider applicability than the IFPUG and both method using the same measuring unit and principle, the continued relevancy of the IFPUG is called to question. Due to similar underlining principle of the two methods and for organizations that have invested so much in the IFPUG not to lose all their investment because of migrating to using COSMIC, researchers have been trying to explore the possibility of converting the output of one method to the other. This paper reviews some of the popular conversion formulas that have been suggested so far to see a trend or how related, consistent and reliable the formulas could be. We estimate the function point of two case studies using the COSMIC and IFPUG. Then we insert our estimation result into the formulas to see how close or diverse the output will be in comparison with our calculation. The result varied widely and nothing conclusive can be said, though, two of the formulas give closer estimation range than others. We also highlight why COSMIC may be more desirable today than the IFPUG and presented the progress level on trying to establish a convertible relationship between the two methods.
Authors and Affiliations
Md. Forhad Rabbi , Shailendra Natraj, Olorisade Babatunde Kazeem
Automatic Image Retrieval through Video Authoring and Transitio
Abstract: An integrated system for video summarization, browsing and presentation, based on large amount of personal and web video clips. Content-consistent shots are retrieved from a video pool in order to form a...
A Review on Diverse Ensemble Methods for Classification
Ensemble methods for different classifiers like Bagging and Boosting which combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity ofthe members of...
Classification of Cardiovascular Disease from ECG using Artificial Neural Network and Hidden Markov Model.
Abstract: this paper deals with the classification of cardiovascular disease for its future analysis. If future progression of the disease can be predicted earlier with proper change in medication patients treatmen...
Enhanced Noise Type Recognition Using Statistical Measures
Noises are the unwanted information in an image, so they should be removed before further processing. Existing methods consider histogram based analysis which is globally varied one. A modified statistical measur...
Selecting the correct Data Mining Method: Classification & InDaMiTe-R
One of the most difficult tasks in the whole KDD process is to choose the right data mining technique, as the commercial software tools provide more and more possibilities together and the decision requir...