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381 papers

#computer vision Conference Open access Aug 2019

Exploring Virtual Reality as an Integrated Development Environment for Cyber-Physical Systems

Cyber Physical Systems (CPS) development approaches tend to start from the physical (hardware) perspective, and the software is the final element in the process. However, this approach is unfit for the more software-intensive world that is increasingly iterative, connected, and constantly online. Many constraints preve...

T. Mikkonen, Kai-Kristian Kemell, Petri Kettunen et al. · 3 citations
#computer vision Open access Nov 2019

Containers in Software Development: A Systematic Mapping Study

Containers are most often discussed in the context of cloud computing, performance and DevOps, and it is found that what is currently missing is more deeply focused research.

Mikael Koskinen, T. Mikkonen, P. Abrahamsson · 15 citations · ⚡1
#computer vision Conference Open access May 2019

How do Startups Develop Internet-of-Things Systems - A Multiple Exploratory Case Study

Internet-of-Things applications are not only the new opportunity for digital businesses but also a major driving force for the modification and creation of software systems in all industries and businesses. Compared to other types of software-intensive products, the development of Internet-of-Things applications lacks...

Anh Nguyen-Duc, K. Khalid, T. Lønnestad et al. · 10 citations
#machine learning Book Open access May 2019

An Empirical Study on Female Participation in Software Project Courses

Gender issues in software engineering education are gaining research attention due to the desire to promote female participation in the field. The objective of this work is to enhance the understanding of female students' participation in software engineering projects to support gender-aware course optimization. Since...

Anh Nguyen-Duc, M. L. Jaccheri, P. Abrahamsson · 9 citations
#computer vision Open access May 2019

Hypotheses Engineering: First Essential Steps of Experiment-Driven Software Development

Recent studies have proposed the use of experiments to guide software development in order to build features that the user really wants. Some authors argue that this approach represents a new way to develop software that is different from the traditional requirement-driven one. In this position paper, we propose the di...

Jorge Melegati, Xiaofeng Wang, P. Abrahamsson · 20 citations · ⚡2
#artificial intelligence Conference Open access May 2019

Ethically Aligned Design: An Empirical Evaluation of the RESOLVEDD-Strategy in Software and Systems Development Context

A key finding from the study indicates that simply the presence of an ethical tool has an effect on ethical consideration, creating more responsibility even in instances where the use of the tool is not intrinsically motivated.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 17 citations · ⚡2
#computer vision Open access Jun 2019

Implementing Ethics in AI: Initial Results of an Industrial Multiple Case Study

This paper begins to address the focal problem of implementing ethics into AI system design and development in practice by providing elements needed for producing a baseline for ethics in AI based software development by means of an industrial multiple case study on AI systems development in the healthcare sector.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 18 citations · ⚡3
#computer vision Open access Jul 2020

Towards a Secure DevOps Approach for Cyber-Physical Systems: An Industrial Perspective

The study shows that, because security is a cross-cutting property in complex CPSs, its proficient management requires system-wide competencies and capabilities across the CPSs development and operation.

P. Abrahamsson, Goetz Botterweck, Hadi Ghanbari et al. · 14 citations
#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Open access 2020

Startup Metrics That Tech Entrepreneurs Need to Know

In this chapter, the results of a multivocal literature review are presented to offer 118 metrics practitioner experts think software startups should measure that can give you ideas for what your startup should measure.

Kai-Kristian Kemell, Xiaofeng Wang, Anh Nguyen-Duc et al. · 8 citations · ⚡1
#artificial intelligence Book Open access Apr 2020

A Multiple Case Study of Artificial Intelligent System Development in Industry

This investigation revealed different types of AI systems and different AI development approaches, but it is common that business opportunities involving with AI systems are not validated and there is lack of business-driven metrics that guide the development ofAI systems.

Anh Nguyen-Duc, Ingrid Sundbø, E. Nascimento et al. · 20 citations · ⚡1

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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