Lease and Leader Election Defect Code Verification Dataset

#Code Correctness Verification #Concurrency Defect Detection #Root Cause Analysis #Failure Scenario Evaluation #Distributed Scheduling #High-Availability Control Planes #Leader Election #Failover

7460
0.4GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-04

AI Analysis & Value Prop

This dataset contains source code samples implementing scheduler leases, heartbeats, leader election, and failover in distributed task scheduling systems, paired with verification scenarios for concurrent elections, expired leases, split-brain behavior, and duplicate failovers. Each sample includes a verification conclusion, defect categories, root cause analysis, supporting evidence, and a risk assessment. It supports code correctness review and the investigation of concurrency and failure-handling issues in high-availability scheduling control planes.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
source_code	string	Source code under review that implements scheduler leases, heartbeats, leader election, or failover.
risk_assessment	object	Assessment of defect severity, impact scope, remediation priority, and safe failover capability.
defect_categories	array	Defect types classified under categories such as concurrent elections, expired leases, split-brain behavior, and duplicate failovers.
execution_scenario	object	Original runtime parameters and failure conditions used to reproduce concurrent elections, expired leases, split-brain behavior, or duplicate failovers.
root_cause_analysis	object	Analysis of the triggering conditions, violated invariants, and causal chain behind a verification failure or potential defect.
verification_evidence	array	Code locations and observed-versus-expected behavior comparisons that support the verification conclusion and root cause analysis.
verification_conclusion	string	Overall conclusion on whether the reviewed implementation satisfies correctness requirements for leases, heartbeats, elections, and failover.

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

Frequently Asked Questions

What does the dataset contain?: It includes source code for scheduler leases, heartbeats, leader election, and failover, along with verification scenarios, conclusions, and root cause annotations for issues such as concurrent elections, expired leases, split-brain behavior, and duplicate failovers.

How does the data support code verification and defect localization?: Each sample links code under review with an execution scenario, verification conclusion, defect categories, root cause analysis, and evidence. This structure supports training or evaluating verifiers that identify violated correctness requirements and the conditions that trigger defects.

What is the dataset field structure?: The main fields are source code, execution scenario, verification conclusion, defect categories, root cause analysis, verification evidence, and risk assessment. Refer to the dataset's accompanying schema for field types and organization.

How can I access the data, and what are the licensing terms?: Check the dataset listing for available access methods, license scope, and usage restrictions. Review the applicable terms before use, including any requirements concerning redistribution or commercial use.

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Cite this Work

@dataset{Mobiusi2026,
  title={Lease and Leader Election Defect Code Verification Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/56dd32f6bfd3c8c4bd3426847716866d?dataset_scene_id=19},
  urldate={2026-10-27},
  keywords={lease code verification,leader election defects,distributed scheduler,heartbeat verification,split-brain detection,failover testing,concurrent election analysis,code root cause analysis},
  version={1.0}
}

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