Efficient Path Delay Test Generation with Boolean Satisfiability

This dissertation focuses on improving the accuracy and efficiency of path delay test generation using a Boolean satisfiability (SAT) solver. As part of this research, one of the most commonly used SAT solvers, MiniSat, was integrated into the path delay test generator CodGen. A mixed structural-functional approach was implemented in CodGen where longest paths were detected using the K Longest Path Per Gate (KLPG) algorithm and path justification and dynamic compaction were handled with the SAT solver. Advanced techniques were implemented in CodGen to further speed up the performance of SAT based path delay test generation using the knowledge of the circuit structure. SAT solvers are inherently circuit structure unaware, and significant speedup can be availed if structure information of the circuit is provided to the SAT solver. The advanced techniques explored include: Dynamic SAT Solving (DSS), Circuit Observability Don’t Care (Cir-ODC), SAT based static learning, dynamic learnt clause management and Approximate Observability Don’t Care (ACODC). Both ISCAS 89 and ITC 99 benchmarks as well as industrial circuits were used to demonstrate that the performance of CodGen was significantly improved with MiniSat and the use of circuit structure

SAT-based Automatic Test Pattern Generation

Abstract. Due to the rapidly growing size of integrated circuits, there is a need for new algorithms for Automatic Test Pattern Generation (ATPG). While classical algorithms reach their limit, there have been recent advances in algorithms to solve Boolean Satisfiability (SAT). Because Boolean SAT solvers are working on Conjunctive Normal Forms (CNF), the problem has to be transformed. During transformation, relevant information about the problem might get lost and therefore is not available in the solving process. In the following we briefly motivate the problem and provide the latest developments in the field. The technique was implemented and experimental results are presented. The approach was combined with the ATPG framework of NXP Semiconductors. Significant improvements in overall performance and robustness are demonstrated

Scalable algorithms for software based self test using formal methods

textTransistor scaling has kept up with Moore's law with a doubling of the number of transistors on a chip. More logic on a chip means more opportunities for manufacturing defects to slip in. This, in turn, has made processor testing after manufacturing a significant challenge. At-speed functional testing, being completely non-intrusive, has been seen as the ideal way of testing chips. However for processor testing, generating instruction level tests for covering all faults is a challenge given the issue of scalability. Data-path faults are relatively easier to control and observe compared to control-path faults. In this research we present a novel method to generate instruction level tests for hard to detect control-path faults in a processor. We initially map the gate level stuck-at fault to the Register Transfer Level (RTL) and build an equivalent faulty RTL model. The fault activation and propagation constraints are captured using Control and Data Flow Graphs of the RTL as a Liner Temporal Logic (LTL) property. This LTL property is then negated and given to a Bounded Model Checker based on a Bit-Vector Satisfiability Module Theories (SMT) solver. From the counter-example to the property we can extract a sequence of instructions that activates the gate level fault and propagates the fault effect to one of the observable points in the design. Other than the user supplying instruction constraints, this approach is completely automatic and does not require any manual intervention. Not all the design behaviors are required to generate a test for a fault. We use this insight to scale our previous methodology further. Underapproximations are design abstractions that only capture a subset of the original design behaviors. The use of RTL for test generation affords us two types of under-approximations: bit-width reduction and operator approximation. These are abstractions that perform reductions based on semantics of the RTL design. We also explore structural reductions of the RTL, called path based search, where we search through error propagation paths incrementally. This approach increases the size of the test generation problem step by step. In this way the SMT solver searches through the state space piecewise rather than doing the entire search at once. Experimental results show that our methods are robust and scalable for generating functional tests for hard to detect faults.Electrical and Computer Engineerin

Speeding up SAT-Based ATPG Using Dynamic Clause Activation

Abstract—SAT-based ATPG turned out to be a robust alter-native to classical structural ATPG algorithms such as FAN. The number of unclassified faults can be significantly reduced using a SAT-based ATPG approach. In contrast to structural ATPG, SAT solvers work on a Boolean formula in Conjunctive Normal Form (CNF). This results in some disadvantages for SAT solvers when applied to ATPG, e.g. CNF transformation time and loss of structural knowledge. As a result, SAT-based ATPG algorithms are very robust for hard-to-test faults, but suffer from the overhead for easy-to-test faults. We propose the SAT technique Dynamic Clause Activation (DCA) in order to reduce the run time gap between structural and SAT-based ATPG algorithms and, at the same time, retain the high level of robustness. Using DCA, the SAT solver works on a partial formula of a logic circuit which is dynamically extended during the search process using structural knowledge. Furthermore, efficient dynamic learning techniques can be easily integrated within the proposed technique. The approach is evaluated on large industrial circuits. Keywords-SAT; ATPG; Formal methods; CNF; I

Methodology to accelerate diagnostic coverage assessment: MADC

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2016.Os veículos da atualidade vêm integrando um número crescente de eletrônica embarcada, com o objetivo de permitir uma experiência mais segura aos motoristas. Logo, a garantia da segurança física é um requisito que precisa ser observada por completo durante o processo de desenvolvimento. O padrão ISO 26262 provê medidas para garantir que esses requisitos não sejam negligenciados. Injeção de falhas é fortemente recomendada quando da verificação do funcionamento dos mecanismos de segurança implementados, assim como sua capacidade de cobertura associada ao diagnóstico de falhas existentes. A análise exaustiva não é obrigatória, mas evidências de que o máximo esforço foi feito para acurar a cobertura de diagnóstico precisam ser apresentadas, principalmente durante a avalição dos níveis de segurança associados a arquitetura implementada em hardware. Estes níveis dão suporte às alegações de que o projeto obedece às métricas de segurança da integridade física exigida em aplicações automotivas. Os níveis de integridade variam de A à D, sendo este último o mais rigoroso. Essa Tese explora o estado-da-arte em soluções de verificação, e tem por objetivo construir uma metodologia que permita acelerar a verificação da cobertura de diagnóstico alcançado. Diferentemente de outras técnicas voltadas à aceleração de injeção de falhas, a metodologia proposta utiliza uma plataforma de hardware dedicada à verificação, com o intuito de maximizar o desempenho relativo a simulação de falhas. Muitos aspectos relativos a ISO 26262 são observados de forma que a presente contribuição possa ser apreciada no segmento automotivo. Por fim, uma arquitetura OpenRISC é utilizada para confirmar os resultados alcançados com essa solução proposta pertencente ao estado-da-arte.Abstract : Modern vehicles are integrating a growing number of electronics to provide a safer experience for the driver. Therefore, safety is a non-negotiable requirement that must be considered through the vehicle development process. The ISO 26262 standard provides guidance to ensure that such requirements are implemented. Fault injection is highly recommended for the functional verification of safety mechanisms or to evaluate their diagnostic coverage capability. An exhaustive analysis is not required, but evidence of best effort through the diagnostic coverage assessment needs to be provided when performing quantitative evaluation of hardware architectural metrics. These metrics support that the automotive safety integrity level ? ranging from A (lowest) to D (strictest) levels ? was obeyed. This thesis explores the most advanced verification solutions in order to build a methodology to accelerate the diagnostic coverage assessment. Different from similar techniques for fault injection acceleration, the proposed methodology does not require any modification of the design model to enable acceleration. Many functional safety requisites in the ISO 26262 are considered thus allowing the contribution presented to be a suitable solution for the automotive segment. An OpenRISC architecture is used to confirm the results achieved by this state-of-the-art solution

Optimization of Pseudo Functional Path Delay Test Through Embedded Memories

Traditional automatic test pattern generation achieves high coverage of logic faults in integrated circuits. Automatic test of embedded memory arrays uses built-in self-test. Testing the memories and logic separately does not fully test the critical timing paths that go into or out of memories. Prior research has developed algorithms and software to test the longest paths into and out of embedded memories. However, in this prior work, the test generation time increased superlinearly with memory size. This is contrary to the intuition that the time should rise approximately linearly with memory size. This behavior limits the algorithm to circuits with relatively small memories. The focus of this research is to analyze the time complexity of the algorithm and propose changes to reduce the time required to test circuits with large memories. We use our prior work on pseudo functional K longest path per gate test generation, and the benchmark circuits with embedded memories developed in the prior work. Since the cells within a memory array are not scan cells, a value that is captured in a memory cell must be moved to a scan cell using low-speed coda cycles. This approach will also support the test of any non-scan flip-flop or latch, in addition to embedded memory arrays. In addition to testing the critical timing paths, testing through memories eliminates the logic “shadows” around the memory where faults cannot be tested. In this research our complexity analysis has identified the reason for the superlinear increase in test generation time with larger memories and verified this analysis with experimental results. We have also developed and implemented several heuristics to increase performance, with experimental results. This research also identifies the major algorithm changes required to further increase performance

Analysis and Test of the Effects of Single Event Upsets Affecting the Configuration Memory of SRAM-based FPGAs

SRAM-based FPGAs are increasingly relevant in a growing number of safety-critical application fields, ranging from automotive to aerospace. These application fields are characterized by a harsh radiation environment that can cause the occurrence of Single Event Upsets (SEUs) in digital devices. These faults have particularly adverse effects on SRAM-based FPGA systems because not only can they temporarily affect the behaviour of the system by changing the contents of flip-flops or memories, but they can also permanently change the functionality implemented by the system itself, by changing the content of the configuration memory. Designing safety-critical applications requires accurate methodologies to evaluate the system’s sensitivity to SEUs as early as possible during the design process. Moreover it is necessary to detect the occurrence of SEUs during the system life-time. To this purpose test patterns should be generated during the design process, and then applied to the inputs of the system during its operation. In this thesis we propose a set of software tools that could be used by designers of SRAM-based FPGA safety-critical applications to assess the sensitivity to SEUs of the system and to generate test patterns for in-service testing. The main feature of these tools is that they implement a model of SEUs affecting the configuration bits controlling the logic and routing resources of an FPGA device that has been demonstrated to be much more accurate than the classical stuck-at and open/short models, that are commonly used in the analysis of faults in digital devices. By keeping this accurate fault model into account, the proposed tools are more accurate than similar academic and commercial tools today available for the analysis of faults in digital circuits, that do not take into account the features of the FPGA technology.. In particular three tools have been designed and developed: (i) ASSESS: Accurate Simulator of SEuS affecting the configuration memory of SRAM-based FPGAs, a simulator of SEUs affecting the configuration memory of an SRAM-based FPGA system for the early assessment of the sensitivity to SEUs; (ii) UA2TPG: Untestability Analyzer and Automatic Test Pattern Generator for SEUs Affecting the Configuration Memory of SRAM-based FPGAs, a static analysis tool for the identification of the untestable SEUs and for the automatic generation of test patterns for in-service testing of the 100% of the testable SEUs; and (iii) GABES: Genetic Algorithm Based Environment for SEU Testing in SRAM-FPGAs, a Genetic Algorithm-based Environment for the generation of an optimized set of test patterns for in-service testing of SEUs. The proposed tools have been applied to some circuits from the ITC’99 benchmark. The results obtained from these experiments have been compared with results obtained by similar experiments in which we considered the stuck-at fault model, instead of the more accurate model for SEUs. From the comparison of these experiments we have been able to verify that the proposed software tools are actually more accurate than similar tools today available. In particular the comparison between results obtained using ASSESS with those obtained by fault injection has shown that the proposed fault simulator has an average error of 0:1% and a maximum error of 0:5%, while using a stuck-at fault simulator the average error with respect of the fault injection experiment has been 15:1% with a maximum error of 56:2%. Similarly the comparison between the results obtained using UA2TPG for the accurate SEU model, with the results obtained for stuck-at faults has shown an average difference of untestability of 7:9% with a maximum of 37:4%. Finally the comparison between fault coverages obtained by test patterns generated for the accurate model of SEUs and the fault coverages obtained by test pattern designed for stuck-at faults, shows that the former detect the 100% of the testable faults, while the latter reach an average fault coverage of 78:9%, with a minimum of 54% and a maximum of 93:16%