Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing
Conference
·
OSTI ID:2369627
- Idaho National Laboratory
Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.
- Research Organization:
- Idaho National Laboratory (INL), Idaho Falls, ID (United States)
- Sponsoring Organization:
- 58
- DOE Contract Number:
- AC07-05ID14517;
- OSTI ID:
- 2369627
- Report Number(s):
- INL/CON-24-76242-Rev000
- Conference Information:
- 2024 International Congress on Advances in Nuclear Power Plants, Las Vegas, NV, 06/15/2024 - 06/20/2024
- Country of Publication:
- United States
- Language:
- English
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