Systematic Literature Review: Causes of Rework in GSD

Global Software Development (GSD) involves multiple sites which comprise of different cultures and time zones apart from geographical locations. It is a common software development approach adopted to achieve competitiveness. However, due to multiple challenges it can result in misunderstandings and rework. Rework raises the chance of project failure by delaying the project and increasing the estimated budget. The aim of this study is to identify and categorize the rework causes to reduce its frequency in GSD. To identify the empirical literature related to causes of rework, we performed a Systematic Literature Review (SLR). A total of 23 studies are included as a result of final inclusion. The empirical literature from the year 2009 to 2020 is searched. The overall identified causes of rework in GSD are categorized into 6 major categories which are communication, Requirement Management (RM), roles of stakeholders, product development/integration issues, documentation issues, and differences among stakeholders. The most reported rework causes are related to the category of communication & coordination and RM. Moreover, an industrial survey is conducted to validate the identified rework causes and their mitigation practices from practitioners. This study will help practitioners and researchers in addressing the identified causes and therefore reduce the chances of rework.

Intuitionistic Fuzzy Decision Making Towards Efficient Team Selection in Global Software Development

For successful completion of any software project, an efficient team is needed. This task becomes more challenging when the project is to be completed under global software development umbrella. The manual selection of team members based on some expert judgment may lead to inappropriate selection. In reality, there are hundreds of employees in an organization and a single expert may be biased towards any member. Thus, there is a need to adopt methods which consider multiple selection criteria with multiple expert views for making appropriate selection. This article uses an intuitionistic fuzzy approach to handle uncertainty in the expert's decision in multicriteria group decision making process and ranking among the finite team members. An intuitionistic fuzzy Muirhead Mean (IFMM) is used to aggregate the intuitionistic criteria's. To gain confidence between criteria and expert score relationship, the Annova test is performed. The results are promising with p value as small as 0.02 and one-tail t-test score equals to 0.0000002.

Agile Team Measurement to Review the Performance in Global Software Development

This chapter is aimed at studying the key performance indicators of team members working in an agile project environment and in an extreme programming software development. Practitioners from six different XP projects were selected to respond to the survey measuring the performance indicators, namely, escaped defects, team member's velocity, deliverables, and extra efforts. The chapter presents a comparative view of Scrum and XP, the two renowned agile methods with their processes, methodologies, development cycles, and artifacts, while assessing the base performance indicators in XP setup. These indicators are key to any agile project in a global software development environment. The observed performance indicators were compared against the gold standard industry benchmarks along with best, average, and worst-case scenarios. Practitioners from six agile XP projects were asked to participate in the survey. Observed results best serve the practitioners to take necessary course corrections to stay in the best-case scenarios of their respective projects.

Scrum Team Competencies in Information Technology Professionals in the Global Software Development Environment

The Product Owner and Scrum Master are members of the Scrum Team, which play an essential role in Global Software Development. They must have some competencies that can overcome challenges in the global environment. This study aims to develop the competencies of these two roles and explore issues of global competencies. Researchers conducted a literature study to produce a list of competencies and in-depth interviews to explore the issues. Data processing uses content analysis and descriptive statistics. The author compiled questionnaires and generated three issues, then held a Focus Group Discussion for validation. Without reducing the nature of scrum, the consensus of experts had approved 31 competencies for the product owner while 34 for the scrum master. This research enriches scrum.org and has a global impact on improving Scrum and Global Software Development human capital and IT professionals.

Risk Prediction by Using Artificial Neural Network in Global Software Development

The demand for global software development is growing. The nonavailability of software experts at one place or a country is the reason for the increase in the scope of global software development. Software developers who are located in different parts of the world with diversified skills necessary for a successful completion of a project play a critical role in the field of software development. Using the skills and expertise of software developers around the world, one could get any component developed or any IT-related issue resolved. The best software skills and tools are dispersed across the globe, but to integrate these skills and tools together and make them work for solving real world problems is a challenging task. The discipline of risk management gives the alternative strategies to manage risks that the software experts are facing in today’s world of competitiveness. This research is an effort to predict risks related to time, cost, and resources those are faced by distributed teams in global software development environment. To examine the relative effect of these factors, in this research, neural network approaches like Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient have been implemented to predict the responses of risks related to project time, cost, and resources involved in global software development. Comparative analysis of these three algorithms is also performed to determine the highest accuracy algorithms. The findings of this study proved that Bayesian Regularization performed very well in terms of the MSE (validation) criterion as compared with the Levenberg–Marquardt and Scaled Conjugate Gradient approaches.

Translation of Activities in a Global Virtual Teams Software Development

. This study explores Global Virtual Software Teams’ development practices and try to demystify some of the misconceptions about global software development practices based on findings from the global virtual software teams’ experiment that was carried out at DePaul University from 2011 – 2018. The moments of translation from the perspective of actor-network theory (ANT) was employed in the data analysis, to examine how development approach was selected by the global virtual teams. One of the key findings from our research is that the success of a global software development project does not have a strong dependency on the development approach. While we agree that it is one of the key influencing factors, there are other equally strong factors for global virtual software team’s success.