machine learning

Learning from agile software development

Self-organized Learning in Software Factory: Experiences and Lessons Learned

A set of themes that can potentially explain self-organization from the learning viewpoint are identified, which include self-decided learning goals and personalized learning outcomes, peer teaching through active collaboration, diversity is the key and the personal attitude towards the learning matters.

What Can Software Startuppers Learn from the Artistic Design Flow? Experiences, Reflections and Future Avenues

This paper aims contributing to this gap by studying the artistic design flow and the tools utilized by architects, industrial designers and artists, and proposes concrete ways to improve the current state-of-practice.

Why Early-Stage Software Startups Fail: A Behavioral Framework

This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Towards Abstraction and Automation in Software Engineering

The results of this study show that the Ball ecosystem has the potential to improve the productivity of software development, however, it should produce smaller and more reasonable software systems, leading to a better reusability and a shorter learning phase for new developers.

A Simultaneous, Multidisciplinary Development and Design Journey - Reflections on Prototyping

A wayfaring approach for the early concept creation stage of development projects that have a very high degree of intended innovation and thus uncertainty and the importance of including all the involved disciplines (knowledge domains) from the beginning of the project on.

What leads developers towards the choice of a JavaScript framework?

A model of factors that are desirable to be found in a JSF and a representation of the decision makers involved in the frameworks selection is offered, which contributes to the body of knowledge related to the decision-making process when selecting aJSF.

Time for AI (Ethics) Maturity Model Is Now

It is argued that AI software is still software and needs to be approached from the software development perspective, and whether the focus should be on AI ethics or the quality of an AI system, called a maturity model for the development of AI systems is discussed.

Implementing AI Ethics in a Software Engineering Project-Based Learning Environment - The Case of WIMMA Lab

Key Challenges in Software Startups Across Life Cycle Stages

It is found that what perceived as biggest challenges by software startups do vary across different life cycle stages, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature.

Minimum Viable Product or Multiple Facet Product? The Role of MVP in Software Startups

Minimum viable product (MVP) is the main focus of both business and product development activities in software startups. We empirically explored five early stage software startups to understand how MVP are used in early stages. Data was collected from interviews, observation and documents. We looked at the MVP usage from two angles, software prototyping and boundary spanning theory. We found that roles of MVPs in startups were not fully aware by entrepreneurs. Besides supporting validated learning, MVPs are used to facilitate product design, to bridge communication gaps and to facilitate cost-effective product development activities. Entrepreneurs should consider a systematic approach to fully explore the value of MVP, as a multiple facet product (MFP). The work also implies several research directions about prototyping practices and patterns in software startups.