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A FAST 2018 research paper proposing protocol-aware recovery techniques for consensus-based storage systems that efficiently recover state after failures without violating correctness.
This paper presents the revised analysis engine for Verifpal, a symbolic protocol verifier, detailing its formal specification, proofs, and evaluation against other tools like ProVerif and Tamarin.
This article analyzes the trend of AI Agents shifting from MCP to CLI, discusses the advantages of CLI in local execution, context saving, and debugging, and points out the potential future division of labor between MCP and CLI.
The article presents a 31,430-trial cross-vendor study on zero-byte executions under a frozen protocol for AI agents, questioning whether agent runtimes should preserve verified zero-byte terminal states.
This research systematically analyzes five agent interoperability protocols (MCP, A2A, ACP, ANP, ERC-8004) against a six-dimension governance taxonomy, finding that voting, dissent preservation, and human escalation are universally absent, indicating a missing architectural layer for governed agent communities.
This paper introduces PROBE, a multi-stage pipeline for diagnosing 802.11 packet captures that combines deterministic normalization, multi-run ensemble, and a verdict-aware evidence framework to produce reliable and calibrated diagnoses, outperforming single-pass LLM analysis and naive ensemble voting.