Home/Transport & Automotive/Battery Management System Embedded Numeric Arithmetic Defect Verification Dataset
Battery Management System Embedded Numeric Arithmetic Defect Verification Dataset
#Numeric defect detection #Code verification #Root cause localization #Code repair suggestions #BMS firmware verification #Embedded code debugging #Battery software quality assurance #Code review
- 3580
- 0.4GB
- JSON
- CATL
MOBIUSI INC
Updated:2026-11-04
AI Analysis & Value Prop
This dataset contains verification examples from battery management system (BMS) source code involving fixed-point arithmetic, unit conversions, integer overflow, truncation, and numeric range handling. Examples capture test conditions, expected behavior, and observed failures, with annotations for defect categories, affected expressions, and code-level root causes. Suggested corrections and verification assertions support training and evaluating models for detecting embedded arithmetic defects, tracing their causes, and assisting with code fixes.
Dataset Insights
Sample Examples
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Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| root_cause | string | The implementation-level reason the defect occurs, including relevant type, scaling, conversion, or range-handling details. |
| source_code | string | The BMS source-code snippet being verified, including the relevant arithmetic implementation. |
| test_case_json | string | A JSON-encoded test case containing relevant input values, units, expected behavior, and any applicable numeric limits or tolerances. |
| defect_category | string | The primary category of the identified numeric defect. |
| defect_confirmed | boolean | Indicates whether verification confirms an arithmetic or numeric-handling defect in the source code. |
| observed_failure | string | The incorrect result or runtime behavior observed during verification, such as wraparound, unexpected truncation, or a unit-scale mismatch. |
| numeric_signedness | string | The signedness of the numeric representation relevant to the defect. |
| numeric_width_bits | integer | The relevant integer or fixed-point storage width in bits when it can be determined from the source or verification case. |
| affected_expression | string | The source expression or short code fragment identified as the location of the defect. |
| arithmetic_operation | string | The arithmetic operation or conversion most directly involved in the defect. |
| corrected_expression | string | A suggested corrected expression or implementation fragment that addresses the identified defect. |
| remediation_guidance | string | A concise explanation of the changes needed to correct the defect and avoid similar numeric errors. |
| verification_assertion | string | A concise assertion or expected condition that can be used to verify the implementation after correction. |
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 types of numeric defects are covered?
- Examples focus on embedded numeric handling in BMS source code, including fixed-point arithmetic, unit conversions, integer overflow, truncation, and numeric range handling. They identify observable failures and implementation-level root causes.
- What verification information does each example provide?
- Fields include source code, a JSON-encoded verification case, defect confirmation and category, the relevant operation and affected expression, and, when determinable, numeric width and signedness. Examples can also include a corrected expression, remediation guidance, and a verification assertion.
- Which development and training workflows can use this dataset?
- It can support training or evaluating code models for numeric defect detection, code verification, root-cause localization, and repair suggestions. It is also relevant to BMS firmware validation, embedded software debugging, and code review.
- How can I access the data, and what are the licensing terms?
- Refer to the product page for available access methods, file specifications, and licensing terms. Before use, confirm that the license covers your intended training, evaluation, or commercial use.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Battery Management System Embedded Numeric Arithmetic Defect Verification Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/0773dacf0aa54302466788ee541238e8?dataset_scene_id=1},
urldate={2026-10-22},
keywords={battery management system dataset,BMS code verification,embedded numeric arithmetic,fixed-point arithmetic defects,integer overflow detection,unit conversion verification,source code defect analysis,embedded software testing},
version={1.0}
}Using this in research? Please cite us.
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