Exactly-Once Event Processing Dependency Reasoning Dataset

#Code dependency reasoning #Exactly-once semantics analysis #Code change impact analysis #Transactional correctness assessment #Distributed event streaming #Transactional messaging systems #Event processing code review #Stream processing reliability assessment

Records: 8600
Size: 0.5GB
Format: JSON
Provider: MOBIUSI INC
Updated: v1.02026-11-04

AI Analysis & Value Prop

Focused on exactly-once processing semantics in distributed messaging and event streaming platforms, this dataset contains source code examples covering transactional production, consumer processing, state updates, deduplication, and commit coordination. It includes processing context, correctness assumptions, call and state dependencies, and code-change impact analysis targets for examining transaction boundaries, processing pipelines, and key invariants. It supports training and evaluation of models that reason about code dependencies, semantic risks, and correctness.

Overview

Dataset Insights

Preview

Sample Examples

sample.json

{}

Schema

Technical Specifications

Field	Type	Description
file_name	string	File name
source_code	string	Source code showing transactional production, consumer processing, state updates, deduplication, or commit coordination logic.
dependency_graph	object	Processing nodes and dependency edges inferred from call relationships and shared state.
mutation_request	string	The requested code modification to analyze and whether it may break exactly-once processing semantics.
dependency_context	object	Original dependency information for the source code, including call chains, shared state, and external services.
processing_pipeline	array	Event processing stages and transaction boundaries derived from the source code and context.
correctness_assessment	object	Overall judgment of whether the source code and its modification preserve exactly-once processing semantics under the stated assumptions.
exactly_once_invariants	array	Exactly-once processing invariants derived from the input example and its correctness assumptions.
correctness_requirements	array	Prerequisites explicitly stated in the example for exactly-once processing semantics to hold.
event_processing_context	object	Original configuration or runtime context related to the event platform, transactions, commits, and state storage.
mutation_impact_analysis	object	Inferred effects of the code change on transaction, deduplication, state update, and commit coordination semantics.

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 contains source code examples involving transactional production, consumer processing, state updates, deduplication, and commit coordination, along with event processing context, correctness assumptions, call dependencies, code change requests, and derived analysis.

Which training and evaluation tasks does it support?: It supports code dependency reasoning, transaction boundary analysis, derivation of exactly-once processing invariants, and assessment of how code changes affect deduplication, state updates, and commit coordination.

How is the dataset delivered, and are there format requirements?: Refer to the product page for the available download or delivery method and file details. Examples use structured fields with string, object, and array values; review the delivered format and field definitions before use.

How can I verify data quality and licensing terms?: The examples provide context and correctness assumptions to support grounded analysis; verify the actual coverage and quality against the delivered content. Consult the applicable product page or dataset package terms before using, modifying, or redistributing the data.

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Cite this Work

@dataset{Mobiusi2026,
  title={Exactly-Once Event Processing Dependency Reasoning Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/5d8f5fea9076757740d76148026c54de?dataset_task_cate_id=6},
  urldate={2026-10-27},
  keywords={exactly-once processing dataset,event streaming code,distributed messaging systems,code dependency reasoning,transaction semantics analysis,deduplication logic analysis,code change impact,event processing correctness},
  version={1.0}
}

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