Pith. sign in

REVIEW 1 cited by

Network Simulator-centric Compositional Testing

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2503.04810 v1 pith:CXG5CVBN submitted 2025-03-04 cs.SE cs.CRcs.NIcs.SC

classification cs.SEcs.CRcs.NIcs.SC
keywords networknsctprotocoltestingtime-varyingarticlecompositionalerror
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

This article introduces a novel methodology, Network Simulator-centric Compositional Testing (NSCT), to enhance the verification of network protocols with a particular focus on time-varying network properties. NSCT follows a Model-Based Testing (MBT) approach. These approaches usually struggle to test and represent time-varying network properties. NSCT also aims to achieve more accurate and reproducible protocol testing. It is implemented using the Ivy tool and the Shadow network simulator. This enables online debugging of real protocol implementations. A case study on an implementation of QUIC (picoquic) is presented, revealing an error in its compliance with a time-varying specification. This error has subsequently been rectified, highlighting NSCT's effectiveness in uncovering and addressing real-world protocol implementation issues. The article underscores NSCT's potential in advancing protocol testing methodologies, offering a notable contribution to the field of network protocol verification.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum-Annealing Enhanced Machine Learning for Interpretable Phase Classification of High-Entropy Alloys

    cond-mat.mtrl-sci 2025-07 reject novelty 5.0 of 10

    Quantum annealing based QBoost and QSVM models classify six high-entropy alloy phases with accuracy comparable or superior to classical SVM in several cases, but with a flawed runtime benchmark and unresolved label in...

Pith tools