AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,118 papers
A human-LLM workflow that pairs each curated semantic mutant with an instructor-approved seed phrase for an on-demand LLM expansion, which shows that the curated semantic-mutant set contains a fraction of the mutants a traditional mutation engine produces.
SAT solving is a core computational challenge across hardware verification, electronic design, and planning; an FPGA can evaluate SAT candidates at hardware clock rates without software overhead, enabling sub-microsecond solving on small instances. Yet, the throughput-area tradeoffs of parallel FPGA SAT datapaths remai...
This proposed dissertation investigates mutation testing from three complementary perspectives: how mutations interact with program executions and test oracles to produce mutant kills and reveal opportunities for test improvement, and how mutation testing is adopted, configured, sustained, and acted upon in popular ope...
This talk explores how agent-first development platforms like Google Antigravity shift the paradigm from manual test authoring to autonomous software verification, and describes recent advances in autonomous visual testing.
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PyMut4SE is a novel mutation tool for Python that focuses on a comprehensive set of mutations for any Python project, providing a rich and extensible set of mutation operators, access to mutated source code and its characteristics, detailed execution and behavioral observations, and support for both selective mutation...
Memory-safety bugs are one of the oldest and most common sources of security vulnerabilities, and their modern-day prevalence is a consequence of the widespread use of non-memory-safe languages such as C and C++. Transitioning away from C and C++ to memory-safe languages, namely Rust, to eliminate memory-safety bugs is...
Fuzzing finds bugs by testing software behavior with high volumes of input. To create semantically valid inputs for different targets, traditional fuzzers require significant engineering effort. LLM-based fuzzing approaches can be adapted to create inputs for a wide range of software but introduce new issues: every tes...
The paper asks whether high-level conceptual specifications improve LLM-generated PBT quality and whether they help developers extend and maintain AI-generated systems (RQ2), and reports preliminary results applying Spinach to two open-source applications.
LLM-based testing can expose subtle reliability issues in numerical software, but monolithic prompts make it hard to inspect which guidance drives effectiveness. We study whether Agent Skills can make such workflows more explainable by factoring procedural knowledge into composable testing components. Using numerical i...
Specifying contracts as program behavior using Hoare triples is an established practice in software engineering. Compared to traditional testing approaches, formal verification of these contracts provides stronger guarantees of functional correctness. However, its practical adoption has remained limited since significa...
Kubernetes is a widely adopted container orchestration framework, yet misconfigurations remain a leading cause of cloud security incidents and a major challenge for practitioners. Automated security scanners are commonly used to detect such misconfigurations, but their effectiveness has not been systematically evaluate...
Modern JVM software increasingly integrates multiple programming languages, such as Java, Kotlin, Groovy, and Scala, within a single application. Supporting such interoperability requires JVM compilers to perform cross-language compilation while reconciling subtle semantic differences across language boundaries. Errors...
“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.
We’re giving developers, enterprises, scientists, and consumers access to Gemini 4 Argon, our latest frontier model.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
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.
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.
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