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computer vision

4,009 papers

#computer vision Conference Jun 2006

Does Refactoring Improve Reusability?

The hypothesis that refactoring enhances quality and reusability of – otherwise hard to reuse – classes in an agile development environment is sustained.

Raimund Moser, A. Sillitti, P. Abrahamsson et al. · 113 citations · ⚡6
#computer vision Review Jul 2007

Agile Software Development: Theoretical and Practical Outlook

This tutorial demonstrates how agile solutions are theoretically founded and then in very pragmatic terms shows a longitudinal four-year case study how F-Secure, an antivirus company, from Finland transformed from iterative development to agile development framework.

P. Abrahamsson, Jari Still · 3 citations

An iterative improvement process for agile software development

An Iterative Improvement Process for conducting SPI within individual agile project teams is proposed, which aims at increasing the ability of software developers to improve the development process based on their experiences and context knowledge.

O. Salo, P. Abrahamsson · 81 citations · ⚡5
#computer vision Review Sep 2007

Software Process Improvement - EuroSPI 2007 Conference

This book constitutes the refereed research proceeding of the 14th European Software Process Improvement Conference, EuroSPI 2007, held in Potsdam, Germany in September 2007 and contains 18 revised full papers presented.

P. Abrahamsson, N. Baddoo, T. Margaria et al. · 0 citations
#computer vision Jun 2008

Culture and Agile: Challenges and Synergies

This panel brings together community experts to share and discuss research and field experience that can ameliorate cultural challenges to create synergies in Agile software practices.

S. Fraser, P. Abrahamsson, R. Biddle et al. · 3 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

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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