Video Conferencing Signaling State Verification Dataset
- Records
- 5680
- Size
- 0.5GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
This dataset focuses on signaling state handling in enterprise video conferencing and includes source code for meeting creation, joining, leaving, reconnection, and termination, along with state-transition tests and defect samples. It covers verification workflows such as checking state logic, identifying illegal transitions, analyzing duplicate events, and tracing failure causes. Use it to train and evaluate code-verification and debugging capabilities and to improve the reliability of meeting state machines.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| suggested_fix | string | Recommended code or state-machine change to address the identified signaling defect. |
| defect_sample_code | string | Code containing a signaling state defect or a reproducible faulty event sequence. |
| root_cause_analysis | string | Explanation of the underlying logic or event-handling issue responsible for a verification failure. |
| verification_status | string | Overall outcome of state-logic verification, such as passed, failed, or inconclusive. |
| affected_state_names | array | Names of signaling states implicated by the verification findings. |
| signaling_source_code | string | Source code implementing signaling behavior for meeting creation, joining, leaving, reconnection, or termination. |
| verification_test_code | string | Test code for validating signaling state transitions and event handling. |
| duplicate_event_findings | array | Findings describing duplicate signaling events and their effects on state handling. |
| detected_illegal_transitions | array | State transitions identified as invalid under the expected signaling rules. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What does the dataset contain?
- It includes signaling source code for meeting creation, joining, leaving, reconnection, and termination, as well as state-transition tests, defect samples, verification outcomes, affected states, illegal transitions, and duplicate-event findings.
- Which training and evaluation tasks does it support?
- It can support training or evaluation of models that verify meeting state logic, detect illegal state transitions and duplicate signaling events, and analyze defect causes and potential fixes.
- Does the dataset include reproducible defect cases?
- Its schema includes defect sample code and reproducible faulty event sequences, which can be examined alongside verification tests, findings, and root-cause analyses. The exact coverage depends on the available records.
- How can I obtain the dataset, and what are the licensing terms?
- Refer to the dataset listing for availability, file specifications, and licensing terms. Before use, confirm the permitted scope and follow any requirements for research, commercial use, redistribution, and code security.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
High-quality data, ready for your next AI breakthrough.
Cite this Work
@dataset{Mobiusi2026,
title={Video Conferencing Signaling State Verification Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/43545abeaac6f2b8bc05cdfc7cf23142?dataset_scene_cate_type=9},
urldate={2026-10-26},
keywords={video conferencing dataset,signaling state verification,state machine testing,code verification data,illegal state transitions,duplicate event detection,code defect analysis,root cause localization},
version={1.0}
}Using this in research? Please cite us.