DocumentCode :
707312
Title :
Statistical analysis of defect removal effectiveness to improve the software quality and reducing the estimated cost
Author :
Marandi, Arun Kumar ; Khan, Danish Ali
Author_Institution :
Dept. of Comput. Applic., Nat. Inst. of Technol., Jamshedpur, India
fYear :
2015
fDate :
11-13 March 2015
Firstpage :
509
Lastpage :
513
Abstract :
Software companies need to reduce their estimated cost for surviving the business world. Now the present scenario software industries faces with greater competitive pressures and skyrocketing costs of software breakdown, to push high quality software within their limits to achieve new heights. Software quality and reducing the estimated cost, in this approach method for finding the solution of parameters in linear regression models with cost estimating method. It describes the approach of software and cost analysis with historical project data. In this methodology, Software quality model can make timely predictions of reliability indications; it´s enabling to improve software development processes by target reducing the estimated cost for software products and improve the techniques for more effectively and efficiently.
Keywords :
regression analysis; software cost estimation; software quality; software reliability; cost estimating method; cost reduction; historical project data; linear regression models; reliability indications; software companies; software development processes; software industries; software products; software quality improvement; statistical analysis; Analytical models; Biological system modeling; Mathematical model; Software quality; Statistical analysis; Testing; cost estimation; defect injection; defect removal; defect tracking; linear regression model; quality management; software quality; statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-9-3805-4415-1
Type :
conf
Filename :
7100302
Link To Document :
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