It is inevitable for any successful IT industry not to estimate the effort, cost, and duration of their projects. As evident by Standish group chaos manifesto that approx 43% of the projects are often delivered late and entered crises because of over budget and less required functions. Improper and inaccurate estimation of software projects leads to a failure, and therefore it must be considered in true letter and spirit. When Agile principle-based process models (e.g. Scrum) came into the market, a significant change can be seen. This change in culture proves to be a boon forstrengthening the collaboration betweendeveloper and customer.Estimation has always been challenging in Agile as requirements are volatile. This encourages researchersto work on effort estimation. There are many reasons for the gap between estimated and actual effort, viz., project, people, and resistance factors, wrong use of cost drivers, ignorance of regression testing effort, understandability of user story size and its associated complexity, etc. This paperreviewed the work of numerous authors and potential researchers working on bridging the gap of actual and estimated effort. Through intensive and literature review, it can be inferred that machine learning models clearly outperformed non-machine learning and traditional techniques of estimation. Keywords: Machine Learning, Scrum, Scrum Projects, Effort Estimation, Agile Software Development
Software Process Models from its inception instill standardization and creates a generic culture of developing software for various IT industries. A great paradigm shift has been observed in terms of embracing Agile Development methodology as a viable development methodology in cross key business units. There is a buffet of agile methodologies comes under the umbrella of ASD, out of which Scrum got the highest popularity and acceptability index. Agile based software development is the need of immediate environment. There is an increasing demand for significant changes to software systems to meet ever-changing user requirements and specifications. As Agile is volatile, so effort estimation is challenging and still striving for perfection to decide size, effort, cost, duration and schedule of projects with minimum error. This cause sensitizes potential researchers all across the globe to start working on addressing the issue of inaccurate predication of efforts. The gap between estimated and actual effort is because of limited or no inclusion of various estimation factors like people and project related factors, inappropriate use of size metric and cost drivers, ignorance of testing effort, team member’s inability to understand user story size and complexity etc. This paper attempts to bridge the gap of estimated and actual effort by the use of soft computing techniques thus taking the research to advance frontier area in terms ofestimation. Keywords: Cost Estimation, Effort Estimation, Scrum, Machine Learning, Agile Software Development
Due to the COVID-19 pandemic unemployment broke all the previous records. Due to the pandemic students cannot go to colleges and have no option of campus placements. The only option available for them is to find a job through online job portals. In this paper we present the online recruitment framework that enables different companies to post their job vacancies, which jobseekers can consider while searching for jobs. This portal can also capture job requirements dependent on employers’ needs. A survey was conducted to identify the problems and requirements of the users with the current job portals and the findings of the survey are incorporated in this portal. The main aim of this job portal is to connect the employers and jobseekers as an e-recruitment to help jobseekers find the right jobs. Keywords: Job Seeker, Employer, Online Job Portal, Online Recruitment, Knowledge Sharing, COVID-19 Pandemic
Architecting is an indispensable activity in all spheres and paradigms of Software Engineering. DevOps, a portmanteau of Development and Operations, has a major adoption challenge in context to Microservices Architecture. Architecture refers to the most important aspect of internal design of a software. Architecture must be good otherwise; it will become slow and much more expensive to add new proficiencies in future. This paper has presented a review of microservices architecture and implementation patterns. Microservice approach is a new concept in software architecture patterns and has leapt up over past few years for describing a certain method to design software applications as collections of individualistically deployable services. In this paper we are looking to discover the role of microservices software architecture in DevOps. It is found that adopting DevOps may carry many challenges/issues like organizational values, immaturity of the tools and infrastructural support with it for architecting with it. Keywords: Microservices Architecture, Microservice, Service Oriented Architecture (SOA), Software Architecture, DevOps
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