simulation is a widely used functional verification method for FBD programs of PLC-based digital I&C system in nuclear power plants. It is difficult, however, to estimate the thoroughness (i.e., effectiveness or q...
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simulation is a widely used functional verification method for FBD programs of PLC-based digital I&C system in nuclear power plants. It is difficult, however, to estimate the thoroughness (i.e., effectiveness or quality) of a simulation in the absence of any clear measure for the estimation. This paper proposes two sets of structural coverage adequacy criteria for the FBD simulation, toggle coverage and modified condition/decision coverage, which can estimate the thoroughness of simulation scenarios for FBD programs, as recommended by international standards for functional safety. We developed two supporting tools to generate numerous simulation scenarios and to measure automatically the coverages of the scenarios. The results of our experiment on five FBD programs demonstrated that the measures and tools can help software engineers estimate the thoroughness and improve the simulation scenarios quantitatively. (c) 2020 Korean Nuclear Society, Published by Elsevier Korea LLC. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
Regression verification at the pre-silicon stage has experienced a dramatic boost in capabilities over the past years. With the aid of assertions, improved simulation coverage and formal verification tools, a vast amo...
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ISBN:
(纸本)9781479947225
Regression verification at the pre-silicon stage has experienced a dramatic boost in capabilities over the past years. With the aid of assertions, improved simulation coverage and formal verification tools, a vast amount of trace data and myriads of failures are often generated after each regression run. Along these lines, modern flows face an emerging need to appropriately categorize, prioritize and distribute these failures to the engineer(s) best-suited for detailed debugging of each failure. This task is known as failure triage. Despite its resource-intensive nature, triage remains a predominantly manual process. In this work, an automated data-mining failure triage framework is introduced that mines simulation and SAT-based design debugging data, uncovers relations among verification failures and automatically groups the related ones together. The core characteristic of the framework is a novel feature-based representation for verification failures and a new multiple-pass clustering strategy that surpass previous methodologies in accuracy, robustness and flexibility. The proposed triage engine achieves an 89% average accuracy in failure categorization and compared to existing solutions, it reduces the number of misplaced verification failures by 47% on the average.
Stochastic sensitivity analyses rarely measure the extent to which realized simulations cover the search space. Rather, simulation lengths are typically chosen according to expert judgement. In response, this paper re...
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Stochastic sensitivity analyses rarely measure the extent to which realized simulations cover the search space. Rather, simulation lengths are typically chosen according to expert judgement. In response, this paper recommends a novel application of Good-Turing estimators of missing distributional mass. Using the United Nations Development Programme's Human Development Index, the empirical performance of such coverage metrics are compared to alternative measures of convergence. The former are advantageous - they provide probabilistic estimates of simulation coverage and permit calculation of strict bounds on estimates of pairwise dominance (for all possible weight vectors, how often country X dominates country Y).
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