AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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1,707 papers
SEMAT Accelerator (SematAcc) is a Web-positioning tool for a software engineering endeavor, which implements the SEMAT’s Essence kernel, and permits the use of Essence, thus helping to understand it.
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.
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).
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.
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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.
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.
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.
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.
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.
A Blog post by H company on Hugging Face
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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