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Home/Virtul & Digital/Cache Invalidation Propagation and Dependency Reasoning Dataset

Cache Invalidation Propagation and Dependency Reasoning Dataset

#code dependency analysis #invalidation propagation reasoning #dirty-data risk detection #distributed cache management #cache invalidation analysis #data consistency assurance

5000
0.4GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-04

AI Analysis & Value Prop

This dataset contains supervised source code examples covering cache writes, updates, deletions, invalidation notifications, and replica synchronization. The examples focus on changed entities, dependency relationships, affected cache scope, invalidation conditions, notification channels and consumers, synchronization timing, and potential dirty-data paths. It supports code reasoning, cache consistency analysis, and evaluation for distributed systems development.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
reasoning	string	Detailed justification based on source code control flow, call relationships, and dependency propagation.
final_label	object	The cache consistency reasoning conclusion used for training and evaluation.
source_code	string	A source code snippet containing cache write, update, deletion, invalidation, notification propagation, or replica synchronization logic.
impact_summary	string	A summary of the overall impact of the write, update, or deletion on caches, notification flows, and replica synchronization scope.
operation_type	string	The primary data operation identified from the source code.
changed_entities	array	The data entities, tables, keyspaces, or sets of cache objects directly modified or deleted by the operation.
dependency_graph	array	The dependencies and propagation directions among changed entities, cache entries, notification topics, and replicas.
dirty_data_paths	array	The complete paths from a data change to dirty data in caches or replicas, with associated risk analysis.
invalidation_assessment	object	An assessment of whether cache invalidation is triggered, its triggering conditions, and the affected cache key scope.
replica_sync_assessment	object	An analysis of whether the change triggers replica synchronization, its targets, and inconsistency risks caused by synchronization timing.
notification_propagation	object	An analysis of whether invalidation or data-change notifications are emitted, which channels carry them, and which consumers process them.

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 contains source code examples involving cache writes, updates, and deletions, with annotations for operation types, changed entities, dependency propagation, invalidation and notification assessments, replica synchronization risks, and reasoning conclusions.

Which capabilities can it support in training?: It can support training models to understand control flow and dependencies in cache-related code, and to infer invalidation conditions, notification paths, affected cache scope, and potential causes of dirty data.

How can I verify data quality and programming languages?: Examples are organized as source code snippets with structured supervision fields. Refer to the product listing or accompanying data documentation for the specific programming languages, dataset size, and quality acceptance details.

How is the data delivered, and what license applies?: Delivery methods, available formats, and license scope depend on the specific product listing. Review its delivery documentation and license terms before use, especially for commercial training or redistribution.

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Cite this Work

@dataset{Mobiusi2026,
  title={Cache Invalidation Propagation and Dependency Reasoning Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/957b0f35b35e126f68a6aa08d745fa3d?dataset_scene_cate_type=9},
  urldate={2026-10-14},
  keywords={cache invalidation dataset,cache consistency reasoning,cache dependency propagation,source code reasoning,cache invalidation analysis,dirty data paths,replica synchronization analysis,distributed caching},
  version={1.0}
}

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