AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,089 papers
The 6 week development journey towards a fully functional proof of concept prototype, reflections on the process as well as the technical details of the prototype are described.
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This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Common misconceptions of affects when dealing with job satisfaction, motivation, commitment, well-being, and happiness are provided; validated measurement instruments for affect measurement; and recommendations when measuring the affects of software developers are provided.
This paper conducts a qualitative interpretive study based on face-to-face open-ended interviews, in-field observations, and e-mail exchanges to construct a novel explanatory theory of the impact of affects on development performance.
It is found that what perceived as biggest challenges by software startups do vary across different life cycle stages, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature.
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
A case study of a large software company was conducted to examine how a new product was developed through the internal startup effort and struggled to achieve the desired outcomes set by the management, and the conceptual framework was developed into a Lean startup-enabled new product development model for large softwa...
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
Data Mining & Modeling
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
During the School of Humanities, Arts, and Social Sciences’ 75th Anniversary Symposium, President Sally Kornbluth said “MIT has never needed your particular insight and guidance more than we do now.”
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
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