Category
539 papers
An approach and an associated tool to automate feature identification for web applications are presented and it is indicated that there is a good potential for automating feature identification in web applications.
It is claimed that consumers' technology foresight horizon is limited by the existing technological base and the idea database should be an interesting source of ideas for service developers.
The ongoing work building a Raspberry Pi cluster consisting of 300 nodes is presented, with potential use cases being an inexpensive and green test bed for cloud computing research and a robust and mobile data center for operating in adverse environments.
This paper proposes a research design towards a comparative analysis framework of JSF, which merges researcher needs and practitioner needs and is a call for action to the critical needs.
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It is shown that high article processing charges are not sufficiently justified by the publishers, which often lack transparency and may prevent authors from adopting OA.
In this study, the authors characterize their context and identify common software development startup practices.
This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.
A study with 42 participants investigates the relationship between the affective states, creativity, and analytical problem-solving skills of software developers and offers support for the claim that happy developers are indeed better problem solvers in terms of their analytical abilities.
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
The results of this study show that the Ball ecosystem has the potential to improve the productivity of software development, however, it should produce smaller and more reasonable software systems, leading to a better reusability and a shorter learning phase for new developers.
It's shown that software developers' happiness pays off when it comes to productivity, and it's also shown that happiness boosts productivity.
This research examines whether and how open source communities can leverage microblogging to improve the quality of their software and increase the likelihood of adoption.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
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.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
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…
A Blog post by Multiverse Computing on Hugging Face
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