An Empirical Study to Develop a Decision Support System (DSS) for Measuring the Impact of Quality Measurements over Agile Software Development (ASD)
Osama Alshareet
Journal of Data Processing, Vol. 8, No. 1, 2018.
DOI: 
Link: http://www.dline.info/jdp/fulltext/v8n1/jdpv8n1_3.pdf
Abstract:
During the Global Financial Crisis in 2008, supply exceeded demand in Information Technology (IT) services.
Indeed, IT organizations reduced IT budgets to meet the competition within IT business, which prompted IT managers to look
for more cost-effective solutions. Arguably, ASD methods fit the new wave of strategic software development methodologies
with cost-effective approaches. In fact, ASD enables IT companies to achieve more for less and develop sophisticated projects
with insignificant resources. However, many IT organizations are still using rule-of-thumb practices to measure the quality of
ASD projects instead of using standardized quality measurements. Additionally, the emergence of Strategic Alignment (SA)
and Strategic Information Systems (SIS) predetermined the need for measuring ASD quality in order to optimize it and turn it
into a competitive advantage. Motivated by the lack of research in this area, this quantitative research aims to study the
strategic impact of integrating quality measurements with ASD, quantify it, and develop a model to predict its outcome. Indeed,
the research tests the relation between quality measurements and ASD using independent t-test design. Based on the results,
the research develops a DSS using machine learning algorithm. Arguably, this research provides an empirical assessment of
the process of integrating quality measurements with ASD and reduces gaps in this research area.
To begin with, the research contains seven sections; these sections are introduction, methodology, results and analysis,
recommendations, conclusions, limitations, and future works. The introduction section introduces the research problem with
literature review. After that, the research presents the methodology with analysis to conceptual framework and experiment
details. Furthermore, the research presents the experiment results with a detailed analysis to pilot study, dataset, independent
t-test, and the regression model. Based on the regression model, the research developed a DSS. Finally yet importantly, the
research summarizes recommendations, conclusions, limitation, and future works.