Sunday
Jan022011

January/February 2011

Data Mining

Download Entire January/February 2011 Issue (PDF 5.7MB)

Table of Contents
(click below to download individual articles from the Jan/Feb 2011 issue)

Sponsor's Note
by Karl Rogers
Download Article (PDF 140KB)

Interview with Dr. Randall Jensen
Cost estimation guru, Dr. Randall Jensen, gives his insight into tightening up project parameters.
Download Article (PDF 650KB)

Data Mining for Process Improvement
by Paul Below
Data mining techniques can be used to filter many variables to a vital few to build or improve predictive models. Specific examples are provided in four categories: classification, regression, clustering, and association.
Download Article (PDF 1.1MB)

Demystifying Cloud Computing
by Qusay F. Hassan
Is transitioning to the cloud right for your organization? What are the challenges involved with a cloud computing migration? A look at the pros, cons, terminologies of, and alternatives to cloud computing.
Download Article (PDF 380KB)

A Comparison of Parametric Software Estimation Models Using Real Project Data
by George Stark
Researchers and practitioners of software metrics have developed models to help project managers and system engineers produce estimates of project effort, duration, and quality.
Download Article (PDF 900KB)

BackTalk
by Gary Petersen
Download Article (PDF 90KB)

Web Exclusive
Design Point: An Empirical Approach for Estimating Design Effort
Abstract. In this paper, we present an extension to Function Point estimation, Design Point, conceived to estimate size and productivity of design phase for software development projects executed by Infosys. This approach is based on capturing functional and non-functional requirements, identifying design sensitive parameters influencing the design phase, and deriving design size for any development project. An empirical validation and refinement of model (identification of design sensitive parameters and degree of influence for each for the parameters) has been performed to test the hypothesis over a large number of projects in different stages of execution.
by Srinivasan Venkataraman, Pratip Sengupta, Amit Patni, and Bibhash Saha
Download Article (PDF 650KB)