DevOps is a fine fusion of development and operations teams together to deliver more efficient, reliable and quality software. DevOps make use of alternative set of automation tools for different development stages of software. The research presented in th is paper analyses selective automation tools to provide comprehensive and comparative tabular analysis followed by graphical comparison according to latest Google Trends. Best performer tools out of these alternative tool sets are grouped together into int egrated tool chain (ITC) in order to escalate DevOps performance in future. A hybrid automated model for software development using these selective automation tools from the ITC is also proposed. This analytic comparison will prove to be a big utility for young researchers, students and software developers to be cognizant with DevOps automation cul ture. Study of other tools or enhancement of the proposed hybrid model could also be considered as a part of future research.
Successful implementations of Software Development Methodologies significantly improve software efficiency, collaboration and security. Most companies are moving away from traditional development methodologies towards DevOps for faster and better software delivery. DevOps, which is a primary need of the IT industry, brings development and operation teams together to overcome communication gaps responsible for software failures. It relies on different sets of automation tools to robotize the tasks of software development from continuous integration, to testing, delivery, and deployment. The existence of several automation tools in each development phase raises the need for an integrated set of tools to reduce development time. For this purpose, we used the DevOps-based hybrid model Integrated Tool Chain (ITC), along with three sample java-based projects or code repositories to quantify the results. This paper evaluates and compares measurement metrics of java projects using traditional development methodologies and DevOps, and the results are shown in tabular and graphical format. The latest Google and Stack Overflow Trends have also been included to retrieve the best performer development methodology. This comparative and evaluative performance analysis will be beneficial to young researchers that study the metrics of software development, while also they will be introduced to the automotive environment of DevOps, the latest emerging buzzword in software development.
Background: The trend of software development has always been challenging for industry experts and software developers. There is tremendous growth in software development methodologies under the influence of evolving technologies and the rising demands of society. The 2019 pandemic forced software developers to shut down their offices and begin working from home, thereby, highlighting the critical necessity for a shared development and operations teams platform. As a result, the development trend moves from waterfall and Agile towards DevOps. Objective: The objective of the research is to review and comparatively analyze the availability factor of different selective and required features in software development methodologies. Software development industries will be benefited in appropriate methodology selection based on the requirement. Methods: The analysis is based on review of different development methodologies based on existing literature study, Google, and Stack Overflow Trends followed by tabular comparison of Waterfall, Iterative, Prototype, Spiral development models under Traditional and Rapid Application Development (RAD), Scrum, Kanban, XP for Agile methods with DevOps automation culture on essential features. Results: The moving trend towards DevOps, from Traditional and Agile development, demonstrate the most recent market swings for these models. Although Traditional models adhere to outdated software development methodologies, they are included in this high-quality survey and evaluation because of their widespread use in the software industry and prominent researcher’s survey work. Conclusion: Software developers, students, and researchers will all find it simple to comprehend the workings of development processes as a result of this analytical review. Additionally, it will also make it easier for these target audiences to choose relevant and effective models for software development.
<span lang="EN-US">Development and operations (DevOps), an accretion of automation tools, efficiently reaches the goals of software development, test, release, and delivery in terms of optimization, speed and quality. Diverse set of alternative automation tools exist for different phases of software development, for which DevOps adopts several selection criteria to choose the best tool. This research paper represents the performance evaluation and analysis of automation tools employed in the coding phase of DevOps culture. We have taken most commonly followed source code management tools-BitBucket, GitHub actions, and GitLab into consideration. Current work assesses and analyzes their performance based on DevOps evaluation criteria that too are categorized into different dimensions. For the purpose of performance evaluation, weightage and overall score is assigned to these criteria based on existing renowned literature and industrial case study of TekMentors Pvt Ltd. On the ground of performance outcome, the tool with the highest overall score is realized as the best source code automation tool. This performance analysis or measure will be a great benefit to our young researchers/students to gain an understanding of the modus operandi of DevOps culture, particularly source code automation tools. As a part of future research, other dimensions of selection criteria can also be considered for evaluation purposes.</span>
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