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quantum computing

539 papers

#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
#computer vision Review Open access Feb 2013

Foundations and Technological Landscape of Cloud Computing

This paper provides a comprehensive review on the building blocks of cloud computing and relevant technological aspects including architecture, virtualization, data management, and security issues.

Nattakarn Phaphoom, Xiaofeng Wang, P. Abrahamsson · 27 citations
#computer vision Open access Oct 2013

Feature Usage Explorer: Usage Monitoring and Visualization Tool in HTML5 Based Applications

Feature Usage Explorer can be reused in any HTML5 based applications where an understanding of how users interact with the system is required (i.e. user experience and usability studies, human computer interaction field, or requirement prioritization area).

Sarunas Marciuska, P. Abrahamsson · 0 citations
#computer vision Open access Apr 2013

Are Happy Developers more Productive? The Correlation of Affective States of Software Developers and their self-assessed Productivity

An empirical study on the impact of affective states on software developers’ performance while programming and the value of applying psychometrics in Software Engineering studies is demonstrated and a call to valorize the human, individualized aspects of software developers is echoed.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 55 citations · ⚡4

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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.

Microsoft Research Blog Sep 29, 2026

Introducing Quine: An AI research system designed for the complexity of biology

Biology doesn't operate in silos, and neither should the AI representation of it. Quine is an early-stage research effort to create a multimodal world model of biology. By connecting insights across biological scales and modalities, Quine helps scientists computationally search a space far larger than intuition allows and prioritize hypotheses before they reach the lab. Experimental results provide important feedback, helping researchers sharpen future research directions. The post Introducing Q…

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