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Abstract CO107Abstract + Presentation
A Web-Based Tool for Quantitative Risk Assessment of Digital I&C Systems
This work presents a web-based application developed to support the design and evaluation of digital instrumentation and control (I&C) systems by streamlining quantitative risk assessment. The tool integrates the Bayesian and Human Reliability Analysis (HRA)–Aided Method for the Reliability Analysis of Software (BAHAMAS) with common cause failure (CCF) modeling into a unified, software-based platform.
BAHAMAS is a software failure quantification approach designed for data-limited conditions, such as early design phases or situations where operational or test data are unavailable. The method models human errors occurring during software development life cycle (SDLC) activities and evaluates their impact on the presence of specific defect types remaining in the software. These defect types are then used to quantify software failure probabilities. By combining BAHAMAS with software-focused CCF modeling, the application provides integrated risk insights, including estimates of software failure probability and the identification and quantification of software-related CCFs.
The application includes five primary capabilities:
(1) Preliminary assessment, which enables efficient estimation of software failure probability using stage-level evaluations of SDLC activities to support early design decisions;
(2) Comprehensive assessment, which provides more detailed and refined failure probability estimates based on in-depth evaluations of development activities;
(3) Software quality assessment survey, offering a structured, survey-based approach to assess software reliability attributes;
(4) Software CCF analysis, which identifies potential software-related CCFs through the determination of common cause component groups (CCCGs) based on software-specific coupling factors; and
(5) CCCG evaluation, which assesses the vulnerability of each CCCG to CCF using both qualitative and quantitative measures.
Overall, the web-based tool enhances the efficiency, consistency, and traceability of quantitative risk assessment for digital I&C systems and supports informed design and safety evaluation decisions.
← Check another abstractBAHAMAS is a software failure quantification approach designed for data-limited conditions, such as early design phases or situations where operational or test data are unavailable. The method models human errors occurring during software development life cycle (SDLC) activities and evaluates their impact on the presence of specific defect types remaining in the software. These defect types are then used to quantify software failure probabilities. By combining BAHAMAS with software-focused CCF modeling, the application provides integrated risk insights, including estimates of software failure probability and the identification and quantification of software-related CCFs.
The application includes five primary capabilities:
(1) Preliminary assessment, which enables efficient estimation of software failure probability using stage-level evaluations of SDLC activities to support early design decisions;
(2) Comprehensive assessment, which provides more detailed and refined failure probability estimates based on in-depth evaluations of development activities;
(3) Software quality assessment survey, offering a structured, survey-based approach to assess software reliability attributes;
(4) Software CCF analysis, which identifies potential software-related CCFs through the determination of common cause component groups (CCCGs) based on software-specific coupling factors; and
(5) CCCG evaluation, which assesses the vulnerability of each CCCG to CCF using both qualitative and quantitative measures.
Overall, the web-based tool enhances the efficiency, consistency, and traceability of quantitative risk assessment for digital I&C systems and supports informed design and safety evaluation decisions.