Category
3,596 papers
Early results suggest that the behaviors introduced in the model are relevant in SPI initiatives, the use of model raises the awareness about the people issues in improving processes, and the model could be used aside with CMM, SPICE or other process improvement models.
This work proposes an enhanced model where the usability capability is analyzed from three dimensions: user- centered infrastructure, implementation of user-centered practices in development projects, and business management commitment to usability as a competitive asset.
The findings indicate an improvement in effort estimation skills and an increase in the resulting product quality in terms of reduced total defect density and the use of the PSP method in the software industry is discussed.
This study suggests that software organizations operate through strategic, operational and personal commitment nets, and shows that SPI is driven through the formation and reformation of commitment nets.
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The requirements for new agile methods targeted to facilitate the development of embedded software, based on an empirical study over a period of 12 months in theDevelopment of low-level telecommunications software, are defined.
This empirical case demonstrates that while the customer was present close to 100% with the development team, only 21% of his work effort was required to assist the team in the development.
The Mobile-D approach is briefly outlined here and the experiences gained from four case studies are discussed, which helped develop an agile development approach for mobile application development.
Results of a case study where a mobile application was developed for global markets, using the TDD approach show that the adoption of TDD is difficult and the potential agility benefits may not be readily available.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
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.
A Blog post by H company on Hugging Face
A Blog post by Liquid AI on Hugging Face
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
Human-Computer Interaction and Visualization
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