AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,429 papers
This vision paper presents a workflow that operationalizes constantly evolving regulatory requirements into automated developer-focused tests and orchestration of requirements elicitation, regulatory interpretation, traceability, test generation, and developer feedback into a continuous compliance workflow.
This work developed an LLM-assisted automated discriminatory test generation approach for identifying discriminatory behavior in ML model outcomes using GPT-4o Mini and Claude Sonnet 4 model and shows that LLM-assisted approach achieves higher success rates in identifying discriminatory behavior compared to existing st...
The findings indicate that industry measurement remains largely tool-driven, emphasizing artifact properties that can be readily automated, and more holistic assessments will require practitioners and researchers to develop and validate complementary measures of people and practices.
This paper presents a compact, low-polarization-dependent-loss (PDL) O-band coarse wavelength division multiplexing (CWDM) silicon photonic receiver utilizing active coherent combining. To overcome the substantial footprint of conventional polarization-diversity circuits and mitigate dynamic signal fading in practical...
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An LLM-driven testing framework that reformulates accessibility evaluation into an automated reachability problem and effectively uncovers four types of dynamic accessibility defects: non-interactive control, navigation trap, improper focus ordering, and navigation dead zone is presented.
A systematic evaluation of the capability of large language models (LLMs) in new feature implementation, with a task setup strictly aligned with real-world software development practices, shows that new feature implementation of LLMs adhering to real-world world software development practices remains challenges.
The results show that CoCoS supports the conservative bounding of regression scopes while preserving compliance-oriented reasoning and providing practical evidence for test planning in safety-critical environments.
The design enables continuous execution of large certification test suites while preserving reproducibility, traceability, and result analysis and features a multi-runner model that enables efficient on-commit execution of hundreds of certification test sequences.
This work presents the first formalisation of testability for quantum programs, adapting classical concepts to quantum computation by introducing Quantum Squeeziness, an information-theoretic metric inspired by classical squeeziness to quantify how faults are masked and prevented from propagating to observable outcomes...
It is found that LLM-based approaches can generate incorrect, overspecified, or incomplete test suites in all configurations, and that the configuration has less of an effect on the generated tests than expected.
This talk will look back and forward across space and time with an eye towards a new future of automated system testing.
Results show that FPSieve can reduce false positives, reduce manual effort, and improve OS migration validation throughput, on a large scale OS migration differential testing dataset collected from industrial practice.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
GPT-Lab
· gpt-lab.eu
Sep 23, 2026
Requirements in large systems rarely exist in isolation. Their meaning depends on the wider project context - other requirements, policies, decisions, tests, and implementation details. That becomes especially important when AI is used for review, because spotting a possible conflict or gap is only the beginning. ReqSpace explores how AI, visualisation, and connected project context can help reviewers understand those findings, trace the relationships behind them, and focus on the questions that…
GPT-Lab
· gpt-lab.eu
Sep 17, 2026
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
We’re launching agentic video understanding across our latest Gemini models for improved accuracy and lower costs and token usage.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
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