Top 10 tips for better agile [software engineering projects]

2005 ◽  
Vol 2 (6) ◽  
pp. 33-36 ◽  
Author(s):  
C. Bird
Keyword(s):  
Software Engineering ◽  
Agile Software Engineering ◽  
Agile Software ◽  
Engineering Projects

scholarly journals Innovation and Scaling up Agile Software Engineering Projects

10.28945/3357 ◽  
2009 ◽  
Author(s):  
Sita Ramakrishnan
Keyword(s):  
Software Engineering ◽  
Scaling Up ◽  
Distributed Teams ◽  
Agile Methods ◽  
Agile Practices ◽  
Agile Software Engineering ◽  
Capstone Projects ◽  
Agile Software ◽  
Undergraduate Programs ◽  
Engineering Projects

Software Engineering capstone projects have been running successfully since 2002 for the final year software engineering (SE) students of the Bachelor of Software Engineering (BSE) Program at Monash University, accredited by Engineers Australia and Australian Computer Society. Agile methods are being increasingly adopted in the industry. In this paper, we describe the objectives of SE capstone projects and report on how our innovative projects for supporting the software engineering projects in undergraduate programs at Monash University have evolved and have been scaled up to support agile SE capstone projects. We detail the evolution from our early innovative software engineering projects in the mid 1990s that have served as catalysts for more innovation in the early 2000, and for scaling up agile SE projects with increasing central technical infrastructure support from the School. More recently, we have adapted our approach with a combination of open-source and commercial tools under academic licence for developing and deploying these projects effectively with agile distributed teams. The paper concludes with a discussion on lessons learnt from our innovative projects in the mid 1990s and from the evolution in scaling up to agile practices for the SE capstone projects from 2002-2008.

On the Nature of Collaborations in Agile Software Engineering Course Projects

2016 ◽  
Vol 5 (2) ◽  
pp. 42-59 ◽  
Author(s):  
Pankaj Kamthan
Keyword(s):  
Software Engineering ◽  
Software Development ◽  
Software Engineering Education ◽  
Agile Methodologies ◽  
The Social ◽  
Agile Software Engineering ◽  
Technological Means ◽  
Agile Software ◽  
Engineering Projects

If there is a constant in software development, then it is that its ecosystem is a variable. The agile methodologies are part of a relatively recent shift from predictive to adaptive approach towards software development. This change has had a notable impact on software engineering education (SEE). In this article, a glimpse into the state-of-the-art of incorporating agile methodologies in software engineering courses is presented. In doing so, the reasons for including a project component in software engineering courses, and for committing to agile methodologies in software engineering projects in those courses, are given. The significance of collaboration in the execution of agile methodologies, in general, is underscored, and the pivotal role of collaboration in agile course projects, in particular, is emphasized. To lend an understanding to the notion of collaboration in agile methodologies, a conceptual model for collaboration is proposed and elaborated. The types of collaborations that can occur in agile course projects are classified and discussed. The use technological means for facilitating collaboration, including the Social Web and especially the Wiki, is highlighted.

On the Nature of Collaborations in Agile Software Engineering Course Projects

2021 ◽  
pp. 1529-1551
Author(s):  
Pankaj Kamthan
Keyword(s):  
Software Engineering ◽  
Software Development ◽  
Software Engineering Education ◽  
Agile Methodologies ◽  
The Social ◽  
Agile Software Engineering ◽  
Technological Means ◽  
Agile Software ◽  
Engineering Projects

If there is a constant in software development, then it is that its ecosystem is a variable. The agile methodologies are part of a relatively recent shift from predictive to adaptive approach towards software development. This change has had a notable impact on software engineering education (SEE). In this article, a glimpse into the state-of-the-art of incorporating agile methodologies in software engineering courses is presented. In doing so, the reasons for including a project component in software engineering courses, and for committing to agile methodologies in software engineering projects in those courses, are given. The significance of collaboration in the execution of agile methodologies, in general, is underscored, and the pivotal role of collaboration in agile course projects, in particular, is emphasized. To lend an understanding to the notion of collaboration in agile methodologies, a conceptual model for collaboration is proposed and elaborated. The types of collaborations that can occur in agile course projects are classified and discussed. The use technological means for facilitating collaboration, including the Social Web and especially the Wiki, is highlighted.

A Software Engineering Perspective on Building Production-Ready Machine Learning Systems

2021 ◽  
pp. 23-54
Author(s):  
Petra Heck ◽  
Gerard Schouten ◽  
Luís Cruz
Keyword(s):  
Machine Learning ◽  
Software Engineering ◽  
Integrated Approach ◽  
Learning Systems ◽  
Tool Support ◽  
Machine Learning Applications ◽  
Initial Idea ◽  
Software Engineers ◽  
Agile Software Engineering ◽  
Agile Software

This chapter discusses how to build production-ready machine learning systems. There are several challenges involved in accomplishing this, each with its specific solutions regarding practices and tool support. The chapter presents those solutions and introduces MLOps (machine learning operations, also called machine learning engineering) as an overarching and integrated approach in which data engineers, data scientists, software engineers, and operations engineers integrate their activities to implement validated machine learning applications managed from initial idea to daily operation in a production environment. This approach combines agile software engineering processes with the machine learning-specific workflow. Following the principles of MLOps is paramount in building high-quality production-ready machine learning systems. The current state of MLOps is discussed in terms of best practices and tool support. The chapter ends by describing future developments that are bound to improve and extend the tool support for implementing an MLOps approach.

Qualitative Analysis of Semantically Enabled Knowledge Management Systems in Agile Software Engineering

2012 ◽  
pp. 144-164
Author(s):  
Jörg Rech ◽  
Christian Bogner
Keyword(s):  
Knowledge Management ◽  
Software Engineering ◽  
Qualitative Analysis ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Two Phase ◽  
Complex Processes ◽  
Management Processes ◽  
Agile Software Engineering ◽  
Agile Software

In many agile software engineering organizations there is not enough time to follow knowledge management processes, to retrieve knowledge in complex processes, or to systematically elicit knowledge. This chapter gives an overview about the human-centered design of semantically-enabled knowledge management systems based on Wikis used in agile software engineering environments. The methodology – developed in the RISE (Reuse in Software Engineering) project – enables and supports the design of human-centered knowledge sharing platforms, such as Wikis. Furthermore, the paper specifies requirements one should keep in mind when building human-centered systems to support knowledge management. A two-phase qualitative analysis showed that the knowledge management system acts as a flexible and customizable view on the information needed during working-time which strongly relieves software engineers from time-consuming retrieval activities. Furthermore, the observations gave some hints about how the software system supports the collection of vital working experiences and how it could be subsequently formed and refined.

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