A Comprehensive Test Pattern Generation Approach Exploiting SAT Attack for Logic Locking

The need for reducing manufacturing defect escape in today's safety-critical applications requires increased fault coverage. However, generating a test set using commercial automatic test pattern generation (ATPG) tools that lead to zero-defect escape is still an open problem. It is challenging to detect all stuck-at faults to reach 100% fault coverage. In parallel, the hardware security community has been actively involved in developing solutions for logic locking to prevent IP piracy. Locks (e.g., XOR gates) are inserted in different locations of the netlist so that an adversary cannot determine the secret key. Unfortunately, the Boolean satisfiability (SAT) based attack, introduced in [1], can break different logic locking schemes in minutes. In this paper, we propose a novel test pattern generation approach using the powerful SAT attack on logic locking. A stuck-at fault is modeled as a locked gate with a secret key. Our modeling of stuck-at faults preserves the property of fault activation and propagation. We show that the input pattern that determines the key is a test for the stuck-at fault. We propose two different approaches for test pattern generation. First, a single stuck-at fault is targeted, and a corresponding locked circuit with one key bit is created. This approach generates one test pattern per fault. Second, we consider a group of faults and convert the circuit to its locked version with multiple key bits. The inputs obtained from the SAT tool are the test set for detecting this group of faults. Our approach is able to find test patterns for hard-to-detect faults that were previously failed in commercial ATPG tools. The proposed test pattern generation approach can efficiently detect redundant faults present in a circuit. We demonstrate the effectiveness of the approach on ITC'99 benchmarks. The results show that we can achieve a perfect fault coverage reaching 100%.Comment: 12 pages, 7 figures, 5 table

Narrative “Flow”: A Model of Narrative Processing and its Impact on Information Processing, Knowledge Acquisition and Persuasion

The utility of narrative as a powerful communication tool is undisputed. However, within both narrative and media effects literature, there is a general lack of attention afforded to the process through which narrative influences audiences. This dissertation investigates the distinct cognitive and emotional dimensions that comprise one’s narrative flow and comprehension through the development and validation of a process model. In addition to continuous response measurement and stimulated recall interviews, validation efforts included the use of a scaling technique designed to investigate the conditional nature of narrative flow. These efforts provided evidence for the model’s successful characterization of the psychological processes involved in narrative processing. Insofar as remembering narrative information is a necessary first step toward behavior change, the relationship between narrative flow and memory was explored. A sample of young women (n=115) viewed two excerpts from the primetime medical drama, ER, each addressing a relevant health topic – HPV and BRCA1. Segments of these excerpts, previously found to elicit/inhibit narrative flow, served as a basis for comparison. High engagement produced significantly more recall than low engagement periods. Accurate recognition of key health information was greater when information was presented during low engagement periods

Tools and Algorithms for the Construction and Analysis of Systems

This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

ACR guidance document on MR safe practices: 2013

Because there are many potential risks in the MR environment and reports of adverse incidents involving patients, equipment and personnel, the need for a guidance document on MR safe practices emerged. Initially published in 2002, the ACR MR Safe Practices Guidelines established de facto industry standards for safe and responsible practices in clinical and research MR environments. As the MR industry changes the document is reviewed, modified and updated. The most recent version will reflect these changes. J. Magn. Reson. Imaging 2013;37:501–530. © 2013 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96674/1/24011_ftp.pd