arXiv subjects

Rajdeep Mondal

Publications and source records attributed to Rajdeep Mondal.

4 recordsLinked to original sources

arXiv2025

Echoes of Traversable Wormhole

We study linear scalar perturbations of the four-dimensional, traversable wormhole solution of Maldacena, Milekhin, and Popov(arXiv:1807.04726). The geometry is constructed by matching an asymptotically flat, near-extremal Reissner--Nordstr\"om region to a throat described by $AdS_2 \times S^2$, supported by charged massless fermions. We derive the effective scalar potential governing wave dynamics, which when viewed in the tortoise coordinate, exhibits two extremely sharp and widely separated barriers. These barriers form a resonant cavity and are a direct consequence of the near-horizon geometry of the wormhole mouths. Using time-domain integration, we analyze the wormhole's response to an initial scalar wave packet inside the throat. We find that the late-time signal contains a distinct train of echoes whose amplitude depends on the angular momentum number $l$. We show that higher $l$ modes produce significantly stronger echoes, as the corresponding potential barriers are taller and more reflective, which results in more efficient trapping of the wave within the wormhole throat.

gr-qc↗

arXiv2025

LLM-Based Config Synthesis requires Disambiguation

Beyond hallucinations, another problem in program synthesis using LLMs is ambiguity in user intent. We illustrate the ambiguity problem in a networking context for LLM-based incremental configuration synthesis of route-maps and ACLs. These structures frequently overlap in header space, making the relative priority of actions impossible for the LLM to infer without user interaction. Measurements in a large cloud identify complex ACLs with 100's of overlaps, showing ambiguity is a real problem. We propose a prototype system, Clarify, which uses an LLM augmented with a new module called a Disambiguator that helps elicit user intent. On a small synthetic workload, Clarify incrementally synthesizes routing policies after disambiguation and then verifies them. Our treatment of ambiguities is useful more generally when the intent of updates can be correctly synthesized by LLMs, but their integration is ambiguous and can lead to different global behaviors.

cs.NI↗

arXiv2023

Eywa: Automating Model Based Testing using LLMs

Model-based testing (MBT), whereby a model of the system under test is analyzed to generate high-coverage test cases, has been used to test protocol implementations. A key barrier to the use of MBT is the need for users to understand protocol RFCs in detail to create a compliant model. Our new approach to MBT uses LLMs to automatically build rich models of intended protocol behavior from knowledge embedded in RFCs, blogs, and other natural language sources. Our approach addresses key challenges with using LLMs, including hallucinations and their inability to monolithically generate complex protocol models. We realize our approach through a novel protocol testing framework Eywa,and demonstrate its effectiveness through extensive case studies of DNS and BGP and a smaller study of SMTP. Despite minimal user effort, applying Eywa enabled the discovery of 32 unique bugs across widely used DNS, BGP, and SMTP implementations, 15 of which were previously undiscovered despite extensive prior testing with manually crafted models.

cs.NI↗

arXiv2023

What do LLMs need to Synthesize Correct Router Configurations?

We investigate whether Large Language Models (e.g., GPT-4) can synthesize correct router configurations with reduced manual effort. We find GPT-4 works very badly by itself, producing promising draft configurations but with egregious errors in topology, syntax, and semantics. Our strategy, that we call Verified Prompt Programming, is to combine GPT-4 with verifiers, and use localized feedback from the verifier to automatically correct errors. Verification requires a specification and actionable localized feedback to be effective. We show results for two use cases: translating from Cisco to Juniper configurations on a single router, and implementing no-transit policy on multiple routers. While human input is still required, if we define the leverage as the number of automated prompts to the number of human prompts, our experiments show a leverage of 10X for Juniper translation, and 6X for implementing no-transit policy, ending with verified configurations.

cs.NI↗