Skip to content

Category

human-computer interaction

1,707 papers

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.

Xiaofeng Wang, M. I. Lunesu, Juha Rikkilä et al. · 6 citations
#computer vision Aug 2015

Performance Alignment Work: How software developers experience the continuous adaptation of team performance in Lean and Agile environments

This paper aims to understand how software developers experience the continuous adaptation of performance in a modern, highly volatile environment using Lean and Agile software development methodology and generates a grounded theory, Performance Alignment Work, showing howSoftware developers experience performance.

Fabian Fagerholm, Marko Ikonen, Petri Kettunen et al. · 89 citations · ⚡5

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.

Juhani Risku, P. Abrahamsson · 2 citations
#computer vision Conference Open access Jun 2007

Agile Software Development of Mobile Information Systems

The need for agile methods in the focal domain is presented, their shortcomings are identified on the basis of three large-scale case studies from industry and all of the cases deal with the development of mobile information system.

P. Abrahamsson · 28 citations · ⚡1
#computer vision Open access May 2008

Perspectives on Global Software Development: special issue on PROFES 2007

The Profes conference series was established in 1999 to provide a venue for industry and academia to present and discuss the shift from model-based improvement to a product-oriented perspective in the field of software engineering and software process improvement, which includes a context-oriented understanding of the...

P. Abrahamsson, Jürgen Münch, P. Kuvaja · 4 citations
#computer vision Open access 2011

Failure Prediction using the Cox Proportional Hazard Model

Log messages are proposed to be used to predict failures running devices that read log files of running application and warns about the likely failure of the system; the prediction is based on the Cox Proportional Hazards (PH) model that has been applied successfully in various fields of research.

P. Abrahamsson, I. Fronza, Jelena Vlasenko · 1 citation
#computer vision Open access Sep 2012

Making the leap to a software platform strategy: Issues and challenges

A comprehensive taxonomy of the challenges faced when a medium-scale organization decided to adopt software platforms is provided, namely: business challenges, organizational challenges, technical challenges, and people challenges.

Yaser Ghanam, F. Maurer, P. Abrahamsson · 41 citations · ⚡3
#computer vision Open access Aug 2013

Traverse the landscape of the mind by walking: an exploration of a new brainstorming practice

Three preliminary findings are obtained: walking can lead to an effective idea generation session; brainstorming while walking can encourage team members to participate in and contribute to the session in an equal manner; and it can help a team to maintain sustainable mental energy.

Xiaofeng Wang, D. Graziotin, Juha Rikkilä et al. · 1 citation

From tech blogs

See all →
MIT News · Artificial Intelligence Oct 7, 2026

Discovering the value of humanistic inquiry

Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.

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.

MIT News · Artificial Intelligence Sep 30, 2026

This game-playing AI is the new champ at Stratego

Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.