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human-computer interaction

1,707 papers

#computer vision Review Mar 2008

Agile methods in European embedded software development organisations: a survey on the actual use and usefulness of Extreme Programming and Scrum

The results show that the embedded industry has been able to apply agile methods in its development processes and that the appreciation of the agile methods and their individual practices appears to increase once adopted and applied in practice.

O. Salo, P. Abrahamsson · 238 citations · ⚡9
#computer vision May 2008

Does Test-Driven Development Improve the Program Code? Alarming Results from a Comparative Case Study

A comparative case study of five small scale software development projects where the effect of TDD on program design was studied using both traditional and package level metrics reveals that an unwanted side effect can be that some parts of the code may deteriorate.

Maria Siniaalto, P. Abrahamsson · 35 citations · ⚡2
#computer vision Jun 2008

Architecture-Centric Methods and Agile Approaches

There is a vital need for devising a research agenda for identifying and dealing with architecture-centric challenges in agile software development to make it possible to guide the future research on integrating Architecture-centric methods in agile approaches and give advice to the software industry on dealing with Ar...

M. Babar, P. Abrahamsson · 13 citations
#computer vision May 2009

The Future of Lean in an Agile World

Questions that will be discussed and debated by this panel of leading practitioners and academics are: is Lean harder to adapt and adopt – does Lean require a greater critical mass to make value tangible?

S. Fraser, P. Abrahamsson, R. Davies et al. · 1 citation
#computer vision May 2009

Long-Term Effects of Test-Driven Development A Case Study

TDD has been found to improve the team confidence in the code quality and simplify significantly the software maintenance and is eager to continue improving the practice application.

A. Marchenko, P. Abrahamsson, T. Ihme · 30 citations · ⚡1
#computer vision May 2009

XP Workshop on Agile Product Line Engineering

Software Product Line Engineering (SPLE) promises to lower the costs of developing individual applications as they heavily reuse existing artifacts and, besides decreasing costs, software reuse achieves faster development and higher quality.

Yaser Ghanam, K. Cooper, P. Abrahamsson et al. · 1 citation

Positioning Agility

Nilay V. Oza, P. Abrahamsson, Kieran Conboy · 4 citations
#computer vision Review Jul 2009

Product-Focused Software Process Improvement, 10th International Conference, PROFES 2009, Oulu, Finland, June 15-17, 2009. Proceedings

The 34 papers presented together with 2 keynote speeches were carefully reviewed and selected and the topics covered are evidence-based software engineering and quality assurance, agile software development, process models and SPI, processes, software as a business.

F. Bomarius, M. Oivo, Pivi Jaring et al. · 3 citations
#computer vision Conference Sep 2010

Exploring the Sources of Waste in Kanban Software Development Projects

The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...

Marko Ikonen, Petri Kettunen, Nilay V. Oza et al. · 67 citations · ⚡9
#computer vision Jun 2010

The set-up of a software engineering research infrastructure of the 2010s

The Software Factory of today is not intellectually following the earlier undertakings with the same name stemming back in 1980s in Japan or in the US, but represents the software development of the 2010s.

P. Abrahamsson, Petri Kettunen, Fabian Fagerholm · 21 citations · ⚡1

From tech blogs

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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.

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