ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

International Technology Roadmap for Semiconductors 2003の要求清浄度について － シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について －

This paper presents the ITC'02 SOC test benchmarks. The purpose of this new benchmark set is to stimulate research into new methods and tools for modular testing of SOCs and to enable the objective comparison of such methods and tools with respect to effectiveness and efficiency. The paper defines the benchmark format and naming scheme, and presents the benchmark SOCs. In addition, it provides an overview of the research problems that can be addressed and evaluated by means of this benchmark set. These research problems include the design of optimized test access infrastructures and test schedules.

A set of benchmarks for modular testing of SOCs

This paper addresses an important issue known as sensor drift, which exhibits a nonlinear dynamic property in electronic nose (E-nose), from the viewpoint of machine learning. Traditional methods for drift compensation are laborious and costly owing to the frequent acquisition and labeling process for gas samples’ recalibration. Extreme learning machines (ELMs) have been confirmed to be efficient and effective learning techniques for pattern recognition and regression. However, ELMs primarily focus on the supervised, semisupervised, and unsupervised learning problems in single domain (i.e., source domain). To our best knowledge, ELM with cross-domain learning capability has never been studied. This paper proposes a unified framework called domain adaptation extreme learning machine (DAELM), which learns a robust classifier by leveraging a limited number of labeled data from target domain for drift compensation as well as gas recognition in E-nose systems, without losing the computational efficiency and learning ability of traditional ELM. In the unified framework, two algorithms called source DAELM (DAELM-S) and target DAELM (DAELM-T) are proposed in this paper. In order to perceive the differences among ELM, DAELM-S, and DAELM-T, two remarks are provided. Experiments on the popular sensor drift data with multiple batches collected using E-nose system clearly demonstrate that the proposed DAELM significantly outperforms existing drift-compensation methods without cumbersome measures, and also bring new perspectives for ELM.

Domain Adaptation Extreme Learning Machines for Drift Compensation in E-Nose Systems

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing.

/pdf/signal-and-data-processing-for-machine-olfaction-and-3b071xjcub.pdf

Signal and Data Processing for Machine Olfaction and Chemical Sensing: A Review

Memory testing commonly faces two issues: the characterisation of detailed and realistic fault models, and the definition of time-efficient test algorithms able to detect them. Among the different types of algorithms proposed for testing static random access memories (SRAMs), march tests have proven to be faster, simpler and regularly structured. The continuous evolution of the memory technology requires the constant introduction of new classes of faults, such as dynamic and linked faults. Presented here is March AB, a march test targeting realistic memory static linked faults and dynamic unlinked faults. Comparison results show that the proposed march test provides the same fault coverage of already published algorithms reducing the test complexity and therefore the test time

/pdf/march-ab-a-state-of-the-art-march-test-for-realistic-static-3fv0bnwd2t.pdf

March AB, a state-of-the-art march test for realistic static linked faults and dynamic faults in SRAMs

The Functional BIST approach is a rather new BIST technique based on exploiting embedded system functionality to generate deterministic test patterns during BIST. The approach takes advantages of two well-known testing techniques, the arithmetic BIST approach and the reseeding method. The main contribution of the present paper consists in formulating the problem of an optimal reseeding computation as an instance of the set covering problem. The proposed approach guarantees high flexibility, is applicable to different functional modules, and, in general, provides a more efficient test set encoding then previous techniques. In addition, the approach shorts the computation time and allows to better exploiting the tradeoff between area overhead and global test length as well as to deal with larger circuits.

http://www.cecs.uci.edu/~papers/compendium94-03/papers/2001/date01/pdffiles/03c_4.pdf

On applying the set covering model to reseeding

Chip-level failure detection has been a target of research for some time, but today's very deep-submicron technology is forcing such research to move beyond detection. Repair, especially self-repair, has become very important for containing the susceptibility of today's chips. This article introduces a self-repair-solution for the digital FIR filter, one of the key blocks used in DSPs.

/pdf/online-self-repair-of-fir-filters-1xcg5kue4d.pdf

Online self-repair of FIR filters

Design and optimization of adaptable BCH codecs for NAND flash memories

Presents the validation of the strategies employed in the RECCO tool to analyze a C/C++ software; the RECCO compiler scans C/C++ source code to extract information about the significance of the variables that populate the program and the code structure itself. Experimental results gathered on an Open Source Router are used to compare and correlate two sets of critical variables, one obtained by fault injection experiments, and the other applying the RECCO tool, respectively. Then the two sets are analyzed, compared, and correlated to prove the effectiveness of RECCO's methodology.

/pdf/validation-of-a-software-dependability-tool-via-fault-3jlupdr6j8.pdf

S. Di Carlo

Papers

March AB, a state-of-the-art march test for realistic static linked faults and dynamic faults in SRAMs

On applying the set covering model to reseeding

Online self-repair of FIR filters

Design and optimization of adaptable BCH codecs for NAND flash memories

Validation of a software dependability tool via fault injection experiments