Investigating Daily Team Meetings in Agile Software Projects

2012 ◽  
Author(s):  
Viktoria Gulliksen Stray ◽  
Nils Brede Moe ◽  
Aybuke Aurum
Keyword(s):  
Software Projects ◽  
Team Meetings ◽  
Agile Software

Case study on risk management practice in large offshore‐outsourced Agile software projects

IET Software ◽  
2014 ◽  
Vol 8 (6) ◽  
pp. 245-257 ◽  
Author(s):  
Srikrishnan Sundararajan ◽  
Marath Bhasi ◽  
Pramod K. Vijayaraghavan
Keyword(s):  
Risk Management ◽  
Management Practice ◽  
Software Projects ◽  
Agile Software

Influential Agile Software Parameters

2011 ◽  
pp. 1938-1943
Author(s):  
Subhas C. Misra ◽  
Vinod Kumar ◽  
Uma Kumar
Keyword(s):  
Project Management ◽  
Software Process ◽  
Systems Development ◽  
The Other ◽  
Software Systems ◽  
Software Projects ◽  
Optimal Cost ◽  
Management Processes ◽  
Agile Software ◽  
Refining Processes

Successful software systems development is a delicate balance among several distinct factors (Jalote, 2002) such as enabling people to grow professionally; documenting processes representing the gained experiences and knowledge of the organization members; using know how to apply the suitable processes to similar circumstances; and refining processes based on achieved experience. Software projects have two main dimensions: engineering and project management. The engineering dimension concerns the construction of a system, and focuses mainly on issues such as how to build a system. The project management dimension is in charge with properly planning and controlling the engineering activities to meet project goals for optimal cost, schedule, and quality. For a project, the engineering processes specify how to perform activities such as requirement specification, design, testing, and so on. The project management processes, on the other hand, specify how to set milestones, organize personnel, manage risks, monitor progress, and so on (Jalote, 2002). A software process may be defined as “a set of activities, methods, practices, and transformations that people use to develop and maintain software, and the associated products and artifacts.”1 This is pictorially depicted in Figure 1 (Donaldson & Siegel, 2000).

scholarly journals From Collaboration to Solitude and Back: Remote Pair Programming During COVID-19

2021 ◽  
pp. 3-18
Author(s):  
Darja Smite ◽  
Marius Mikalsen ◽  
Nils Brede Moe ◽  
Viktoria Stray ◽  
Eriks Klotins
Keyword(s):  
Social Practice ◽  
Pair Programming ◽  
Software Projects ◽  
Collaborative Practices ◽  
Face To Face ◽  
Software Teams ◽  
Software Companies ◽  
Work From Home ◽  
The Usa ◽  
Agile Software

AbstractAlong with the increasing popularity of agile software development, software work has become much more social than ever. Contemporary software teams rely on a variety of collaborative practices, such as pair programming, the topic of our study. Many agilists advocated the importance of collocation, face-to-face interaction, and physical artefacts incorporated in the shared workspace, which the COVID-19 pandemic made unavailable; most software companies around the world were forced to send their engineers to work from home. As software projects and teams overnight turned into distributed collaborations, we question what happened to the pair programming practice in the work-from-home mode. This paper reports on a longitudinal study of remote pair programming in two companies. We conducted 38 interviews with 30 engineers from Norway, Sweden, and the USA, and used the results of a survey in one of the case companies. Our study is unique as we collected the data longitudinally in April/May 2020, Sep/Oct 2020, and Jan/Feb 2021. We found that pair programming has decreased and some interviewees report not pairing at all for almost a full year. The experiences of those who paired vary from actively co-editing the code by using special tools to more passively co-reading and discussing the code and solutions by sharing the screen. Finally, we found that the interest in and the use of PP over time, since the first months of the forced work from home to early 2021, has admittedly increased, also as a social practice.

scholarly journals Estimation Approaches of Machine Learning in Scrum Projects: A Review

2021 ◽  
Vol 9 (11) ◽  
pp. 1110-1118
Author(s):  
Chitrak Vimalbhai Dave
Keyword(s):  
Machine Learning ◽  
Regression Testing ◽  
Process Models ◽  
Effort Estimation ◽  
Software Projects ◽  
It Industry ◽  
Resistance Factors ◽  
User Story ◽  
Inaccurate Estimation ◽  
Agile Software

Abstract: 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

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