Determinants of Effective Change Management for Software Deployment Projects

Software application deployment change management is one of the emerging research themes that is gaining increased focus day by day. Our study examined the factors that affect software application deployment change management in Agile software development settings. Our study provided a systematic review and synthesized the approaches, practices, and challenges reported for adopting and implementing deployment change management. The prime objective of our study was to systematically synthesize the data extracted and formulate evidence-based practical recommendations that are influential in software deployment change management. Six research themes are proposed to evaluate the rationale of the research question. This qualitative study and systematic review explored the pertinent research articles and key findings from prominent academic databases. Based on the selected criteria, the final screening revealed 25 articles from an immense set of publications. Key findings that emerged from these publications are correlated with the six research themes: (a) timely communication with all stakeholders; (b) the reliance of deployment approaches on past experience; (c) the importance of collaboration among team members having adequate knowledge of DevOps tools; (d) the ramification of the differences among development, test, and production environments; (e) the influential areas that reap the benefits of continuous delivery and deployment; and (f) the challenges of the effective use of containerization. We also found indications of the significance of Lewin’s three-step change process model in the Agile development and deployment environment. Overall, our study deepens understanding of this thriving research area and contributes to the literature on Agile deployment and the software change management process.

Using Katalon for Mobile App Test Automation

Software testing is a study conducted to provide interested parties with information about the quality of the software product or service under test. Software testing also provides an objective independent perspective of the software. Helping companies recognize and understand the risks of software deployment. Testing technique includes the process of running a program or application with the aim of finding errors and verifying that the product is suitable for use. There are two ways of writing tests: manually and automatic. Certain ways of manual testing, which include exploratory testing and usable testing, are not that valuable. One can manually run other types of tests, such as regression tests and functional tests, anyways it doesn’t really make sense for developers to repeat the exact process again and again. Because of this type of iterative test which results us to move towards testing automation.

A review on Continuous Integration, Delivery and Deployment using Jenkins

Continuous Integration (CI) is the technique of integrating small changes made to the code more often rather than waiting till the end of the development cycle for integration. The software practice wherein the software deployment can be done anytime to the market is called Continuous Delivery (CD). With continuous integration and continuous delivery, the problem of taking time to find and resolve the bug can be reduced to a large extent. As the time to find the bugs and fix them gets reduced, many releases adhering to the given timeline can be made by an organization. Various software tools have been developed for the continuous integration process which includes Jenkins, Bitbucket, TeamCity. In this paper, a review on the standard practices, approaches, challenges faced while using the continuous integration/delivery in the software development, methods of solving them, and using Jenkins for the implantation of continuous integration/delivery is done.

Retrofit an 11-meter yacht for autonomous navigation

Intelligent/autonomous ships form a rising field that brings beneficial changes to waterborne transportation such as relieving labour shortages, avoiding collisions, and providing assistance to humans. Many autonomous navigation attempts have been carried out on ship models rather than real ships. The results of these studies have certain gaps with the results of full-scale ships. Cost and risk of intelligent ships for autonomous navigation are yet unclear, which makes retrofitting existing ships for tests and development appealing. This paper introduces the process of retrofitting a full-scale 11-meter yacht, including mechanical retrofit, hardware redesign, software deployment, and functional testing. The process is proposed as a solution of ship retrofit for autonomous navigation functions like heading control, path following, and collision avoidance. In the end, this paper concludes a plan of hardware and software that could help find more retrofit solutions, providing a reference for academic research and practical applications.

Execution of Long-Duration Multi-Cloud Serverless Functions Using Selective Migration-Based Approach

A relatively new paradigm for the Cloud-based software deployment is serverless computing. By adopting stateless loosely-coupled functions, the system can obtain many compositions for several purposes. Contrarily to monolithic approach, serverless computing facilitates the evolution of the applications, since the functions may be independently scheduled for reconstitution. Nevertheless, serverless computing dictates that function execution should be within a short duration (five minutes max in most Cloud platforms), after which the function is abruptly ended even if it has not completed its task. This leads to prevent functions requiring longer time from being adopted as Serverless functions. This paper deals with this drawback. It proposes a migration-based approach that promotes the execution of long-duration serverless functions: each running function that reaches the maximum time limit is repeatedly transferred to another cloud platform where it is carried on. At each migration step, the destination cloud is selected regarding the most relevant criteria.