System-Level Test (SLT) is important in semiconductor testing as it can detect defects missed by traditional methods. Test engineers use off-the-shelf software to manually compose test suites, often written in high-level languages such as $\mathrm{C} / \mathrm{C}++$ or Rust. Several methods for automatically generating test programs have been investigated, using assembly language. However, one could argue that the resulting test programs are not capturing all possible interactions in actual software. Large Language Models (LLMs) can generate code in high-level languages closer to actual software. In this work, we examine the limitations of LLMs and high-level languages for generating SLT programs. We run an experiment using genetic programming (GP) to find an assembly snippet with the highest power consumption. Then, we utilize LLMs to generate $\mathbf{C}$ code and demonstrate that the compiler, the enabled optimization level, and the LLM have a significant influence on the resulting power consumption. Furthermore, we show via decompilation that the snippet from the GP run has no direct equivalent in C. Finally, we demonstrate that the initial values have a significant impact on power consumption for both the GP-generated and the decompiled snippet.

Process capability index is a useful metric for maintaining the quality of semiconductor manufacturing. We address, for the first time, the influence of Automated Test Equipment (ATE) drift on process capability. An integrated approach for interpretation of process capability indices considers not only the part variation associated with device manufacturing process, but also the measurement variation due to wearing calibration of the ATE. With a polynomial regression model of ATE correction data and Device Under Test (DUT) measurement results we account for measurement variation due to ATE drift and understand how it influences process capability studies.

The rising complexity of integrated devices has led to new defect types and failure modes at the system level that are not detected by structural tests. System-Level Test (SLT) is another test step to combat this challenge. SLT is in charge of exercising system-level interactions between hardware components and software. Non-functional properties, e.g., temperature, play a major role in SLT.This work focuses on the automatic generation of assembly test programs for SLT that aim to indirectly maximize a particular non-functional property, for example, the temperature. It is based on two-step generation with genetic algorithms. First, a fast architectural simulation is used with the genetic algorithm to provide a structure for the test programs. Afterward, an additional generation is done on the hardware to optimize the initial register contents of the program.The case study for gathering experimental results is a super-scalar out-of-order RISC-V processor, the Berkeley Out-of-Order Machine (BOOM). Experimental results show that the two-step generation is more effective in converging to a better power-hungry test program than only using the power consumption as a fitness function for the genetic algorithm.

System-Level Test (SLT) has been an integral part of integrated circuit test flows for over a decade and continues to be significant. Nevertheless, there is a lack of systematic approaches for generating test programs, specifically focusing on the non-functional aspects of the Device under Test (DUT). Currently, test engineers manually create test suites using commercially available software to simulate the end-user environment of the DUT. This process is challenging and laborious and does not assure adequate control over non-functional properties. This paper proposes to use Large Language Models (LLMs) for SLT program generation. We use a pre-trained LLM and fine-tune it to generate test programs that optimize non-functional properties of the DUT, e.g., instructions per cycle. Therefore, we use Gem5, a microarchitectural simulator, in conjunction with Reinforcement Learning-based training. Finally, we write a prompt to generate C code snippets that maximize the instructions per cycle of the given architecture. In addition, we apply hyperparameter optimization to achieve the best possible results in inference.

Test application to state-of-the-art integrated circuits usually consists of multiple test insertions: wafer sort, final test and system-level test (SLT). This paper considers optimization of test content, taking requirements of specific scenarios, such as expected yield levels, test costs and criticality of test escapes, into account. An integrated cost model is proposed and applied to four different test setups on a medium-complexity RISC-V microprocessor. Our results indicate opportunities for up to ~ 40% total cost reduction compared to today’s industrial practice. They also provide insights on the relative importance of various cost contributors, such as the number of available scan test insertions or the specific SLT workload used.

With the continued success of the open RISC-V architecture, practical deployment of RISC-V processors necessitates an in-depth consideration of their testability, safety and security aspects. This survey provides an overview of recent developments in this quickly-evolving field. We start with discussing the application of state-of-the-art functional and system-level test solutions to RISC-V processors. Then, we discuss the use of RISC-V processors for safety-related applications; to this end, we outline the essential techniques necessary to obtain safety both in the functional and in the timing domain and review recent processor designs with safety features. Finally, we survey the different aspects of security with respect to RISC-V implementations and discuss the relationship between cryptographic protocols and primitives on the one hand and the RISC-V processor architecture and hardware implementation on the other. We also comment on the role of a RISC-V processor for system security and its resilience against side-channel attacks.

System-Level Test (SLT) emerged as an additional test step to detect manufacturing defects not caught by traditional testing. For SLT, the Device Under Test (DUT) is embedded into an environment that emulates the end-user application as closely as possible and runs workloads composed of existing off-the-shelf software. We present an automatic greybox SLT program generation method to find code snippets that control the DUT’s extra-functional properties, to achieve better characterization, or to improve the coverage of emerging defect types. In contrast to ATPG or formal methods, our method does not require structural information and relies solely on simulation results or hardware measurements to guide the generation. We show that our method outperforms hand-crafted snippets on a RISC-V super-scalar processor and look into possible reasons why the snippets perform the way they do.

Test methods that can keep up with the ongoing increase in complexity of semiconductor products and their underlying technologies are an essential prerequisite for maintaining quality and safety of our daily lives and for continued success of our economies and societies. There is a huge potential how test methods can benefit from recent breakthroughs in domains such as artificial intelligence, data analytics, virtual/augmented reality, and security. The Graduate School on “Intelligent Methods for Semiconductor Test and Reliability” (GS-IMTR) at the University of Stuttgart is a large-scale, radically interdisciplinary effort to address the scientific-technological challenges in this domain. It is funded by Advantest, one of the world leaders in automatic test equipment. In this paper, we describe the overall philosophy of the Graduate School and the specific scientific questions targeted by its ten projects.

Recent breakthroughs in machine learning (ML) technology are shifting the boundaries of what is technologically possible in several areas of Computer Science and Engineering. This paper discusses ML in the context of test-related activities, including fault diagnosis, post-silicon validation and yield optimization. ML is by now an established scientific discipline, and a large number of successful ML techniques have been developed over the years. This paper focuses on how to adapt ML approaches that were originally developed with other applications in mind to test-related problems. We consider two specific applications of learning in more depth: delay fault diagnosis in three-dimensional integrated circuits and tuning performed during post-silicon validation. Moreover, we examine the emerging concept of brain-inspired hyperdimensional computing (HDC) and its potential for addressing test and reliability questions. Finally, we show how to integrate ML into actual industrial test and yield-optimization flows.

RISC-V has emerged as a viable solution on academia and industry. However, to use open source hardware for safety-critical applications, we need a deep understanding of the way in which well established mechanisms for testing and reliability could be integrated and deployed on the RISC-V ecosystem, and we need a clear knowledge on how such an ecosystem can be leveraged to improve security. This paper includes four contributions presenting the potential of RISC-V in security research, the way in which RISC-V can be hardened against power analysis attacks, how to implement, using RISC-V, software and hardware/software solutions for dual core lock step, and how to perform system-level testing in the RISC-V ecosystem.

System-level test (SLT) is gaining in importance in modern test flows. This paper summarizes recent industrial findings from three companies and discusses some of the still open questions. The first two reports focus on the optimization potentials due to defect coverage overlaps between SLT and other test insertions. Results observed on approximately 20 million manufactured 28nm and 40nm automotive system-on-chip (SoC) designs are reported. Costs and benefits of SLT are discussed and the potentials of a test results analytics platform are identified. The third report explores the role of marginalities among SLT fails. The post-silicon investigation of a CPU block in a 7nm 5G mobile SoC product aims at achieving a better understanding, whose fails are due to random variations versus systematic factors.

In several test and reliability problems (from test generation to FMECA and Burn In) it is important to preliminarily identify those lines in a circuit netlist, which can not be controlled, i.e., can not be toggled to both logic values no matter the applied stimuli. Several techniques have been proposed in the past to attack this problem. In this paper we consider the case where the circuit is a pipelined processor, discuss the specific challenges of this scenario and propose some techniques to automatically identify some of the uncontrollable lines. The approach we devised uses SAT solving as underlying technology. We report the results we gathered on the OR1200 processor, showing that our method allows to trade off between the required computational effort and the achieved results. When compared with results produced by a commercial tool, our approach is able to identify a much higher number of uncontrollable lines with reasonable computational requirements.

System-level test, or SLT, is an increasingly important process step in today's integrated circuit testing flows. Broadly speaking, SLT aims at executing functional workloads in operational modes. In this paper, we consolidate available knowledge about what SLT is precisely and why it is used despite its considerable costs and complexities. We discuss the types or failures covered by SLT, and outline approaches to quality assessment, test generation and root-cause diagnosis in the context of SLT. Observing that the theoretical understanding for all these questions has not yet reached the level of maturity of the more conventional structural and functional test methods, we outline new and promising directions for methodical developments leveraging on recent findings from software engineering.

Reconfigurable Scan Networks (RSNs) allow flexible access to embedded instruments for post-silicon test, validation and debug or diagnosis. The increased observability and controllability of registers inside the circuit can be exploited by an attacker to leak or corrupt critical information.Precluding such security threats is of high importance but difficult due to complex data flow dependencies inside the reconfigurable scan network as well as across the underlying circuit logic.This work proposes a method that fine-granularly computes dependencies over circuit logic and the RSN. These dependencies are utilized to detect security violations for a given insecure RSN, which is then transformed into a secure RSN.Experimental results demonstrate the applicability of the method to large academical and industrial designs. Additionally, we report on the required effort to mitigate found security violations which also motivates the necessity to consider the circuit logic in addition to pure scan paths.

Reconfigurable Scan Networks (RSNs) are a powerful tool for testing and maintenance of embedded systems, since they allow for flexible access to on-chip instrumentation such as built-in self-test and debug modules. RSNs, however, can be also exploited by malicious users as a side-channel in order to gain information about sensitive data or intellectual property and to recover secret keys. Hence, implementing appropriate counter-measures to secure the access to and data integrity of embedded instrumentation is of high importance. In this paper we present a novel hardware and software combined approach to ensure data privacy in IEEE Std 1687 (IJTAG) RSNs. To do so, both a secure IJTAG compliant plug-and-play instrument wrapper and a versatile software toolchain are introduced. The wrapper demonstrates the necessary architectural adaptations required when using a lightweight stream cipher, whereas the software toolchain provides a seamless integration of the testing workflow with stream cipher. The applicability of the method is demonstrated by an FPGA-based implementation. We report on the performance of the developed instrument wrapper, which is empirically shown to have only a small impact on the workflow in terms of hardware overhead, operational costs and test time overhead.

Hardware security adds another dimension to the design space, and more and more attention is paid to protect a circuit against various types of attacks like sniffing, spoofing or IP theft. However, all the efforts for security taken by a designer might be sacrificed by afterwards integrating infrastructure for test, diagnosis and reliability management. Especially, access mechanisms like reconfigurable scan networks (RSNs) may open options for side-channel attacks. Using the presented approach an accurate estimation of reachability properties of all considered benchmarks is provided. The method uses a matrix-based reachability analysis of the original design and the augmented design. The reachability analysis covers complex functional dependencies, caused by configuring a single scan path as well as multiple sequentially activated scan paths through the RSN. This approach adds acceptable runtime to the security verification flow of the design, and shows the designer the introduced possible security violations.

Modern systems-on-chip (SoC) designs are requiring more and more infrastructure for validation, debug, volume test as well as in-field maintenance and repair. Reconfigurable scan networks (RSNs), as allowed by IEEE 1687 (IJTAG) standard, provide flexible access to the infrastructure with low access latency. However, they can also pose a security threat to the system, by leaking information about the system state. In this paper, we present a protection method that monitors access and checks for violations of security properties online. The method prevents unauthorized access to sensitive and secure instruments. In addition, the system integrator can specify more complex security requirements, including giving multiple users different access privileges. Simultaneous accesses to multiple instruments, that would expose sensitive data to an untrusted core (e.g. from 3rd party vendors) or instrument, can be prohibited. The method does not require any change to the RSN architecture and is easily integrable with IP core designs. The area overhead with respect to the size of the RSN is below 6% and scales well with larger networks.

Vulnerabilities and design flaws in Network-on-Chip (NoC) routers can be exploited in order to spy, modify and constraint the sensitive communication inside the Multi-Processors Systems-on-Chip (MPSoCs). Although previous works address the NoC threat, finding secure and efficient solutions to verify the security is still a challenge. In this work, we propose for the first time a method to formally verify the correctness and the security properties of a NoC router in order to provide the proper communication functionality and to avoid NoC attacks. We present a generalized verification flow that proves a wide set of implementation-independent security-related properties to hold. We employ unbounded model checking techniques to account for the highly-sequential behaviour of the NoC systems. The evaluation results demonstrate the feasibility of our approach by presenting verification results of six different NoC routing architectures demonstrating the vulnerabilities of each design.

Reconfigurable Scan Networks (RSNs) allow flexible access to embedded instruments for post-silicon validation and debug or diagnosis. However, this scan infrastructure can also be exploited to leak or corrupt critical information as observation and controllability of registers deep inside the circuit are increased. Securing an RSN is mandatory for maintaining safe and secure circuit operations but difficult due to its complex data flow dependencies. This work proposes a method that detects security violations and transforms a given insecure RSN into a secure RSN for which the secure data flow as specified by a user is guaranteed by construction. The presented method is guided by user-defined cost functions that target e.g., test performance or wiring cost. We provide a case study and experimental results demonstrating the applicability of the method to large designs with low runtime.

The characterization of analog-mixed signal (AMS) silicon requires a suitable pattern set able to exercise the parametric operational space to - among other tasks - validate the correct (specified) working behaviour of the device under test. As experience shows, most of the unexpected problems occur for very specific value combinations of a few test condition variables that were not expected to have an influence. Additionally, restrictions on the operational conditions have to be taken into account. We present a method to efficiently create a set of test conditions to cover such a constrained search space with a user-defined density. First, an initial test condition set is generated using quasirandom Sobol sequences. Secondly, we analyse the test conditions to identify and fill uncovered areas in the parameter space using the in-house interval constraint solver iSAT3. The applicability of the method is demonstrated by experimental results on a 19-dimensional search space using a realistic set of constraints.

Physical unclonable functions (PUFs) can be used for a number of security applications, including secure on-chip generation of secret keys. We introduce an embedded PUF concept called sensitized path PUF (SP-PUF) that is based on extracting entropy out of inherent timing variability of modules already present in the circuit. The new PUF sensitizes paths of nearly identical lengths and generates response bits by racing transitions through different paths against each other. SP-PUF has lower area overhead and higher speed than earlier embedded PUFs and requires no helper data stored in non-volatile memory beyond standard error-correction information for fuzzy extraction. Compared with standalone PUFs, the new solution intrinsically and inseparably intertwines PUF behavior with functional circuitry, thus complicating invasive attacks or simplifying their detection. We present a systematic design flow to turn an arbitrary (sufficiently complex) circuit into an SP-PUF. The flow leverages state-of-the-art sensitization algorithms, formal filtering based on statistical analysis, and MaxSAT-based optimization of SP-PUF's area overhead. Experiments show that SP-PUF extracts 256-bit keys with perfect reliability and nearly perfect uniqueness after fuzzy extraction for the majority of standard benchmark circuits.

A large amount of on-chip infrastructure, such as design-for-test, debug, monitoring, or calibration, is required for the efficient manufacturing, debug, and operation of complex hardware systems. The access to such infrastructure poses severe system safety and security threats since it may constitute a side-channel exposing internal state, sensitive data, or IP to attackers. Reconfigurable scan networks (RSNs) have been proposed as a scalable and flexible scan-based access mechanism to on-chip infrastructure. The increasing number and variety of integrated infrastructure as well as diverse access constraints over the system lifetime demand for systematic methods for the specification and formal verification of access protection and security properties in RSNs. This work presents a novel method to specify and verify fine-grained access permissions and restrictions to instruments attached to an RSN. The permissions and restrictions are transformed into predicates that are added to a formal model of a given RSN to prove which access properties hold or do not hold.

Unknown (X) values in a design introduce pessimism in conventional test generation algorithms, which results in a loss of fault coverage. This pessimism is reduced by a more accurate modeling and analysis. Unfortunately, accurate analysis techniques highly increase runtime and limit scalability. One promising technique to prevent high runtimes while still providing high accuracy is the use of restricted symbolic logic (RSL). However, also pure RSL-based algorithms reach their limits as soon as millon gate circuits need to be processed. In this paper, we propose new ATPG techniques to overcome such limitations. An efficient hybrid encoding combines the accuracy of RSL-based modeling with the compactness of conventional threevalued encoding. A low-cost two-valued SAT-based untestability check is able to classify most untestable faults with low runtime. An incremental and event-based accurate fault simulator is introduced to reduce fault simulation effort. The experiments demonstrate the effectiveness of the proposed techniques. On average, over 99.3% of the considered faults are accurately classified. Both the number of aborts and the total runtime are significantly reduced compared to the state-of-the-art pure RSL-based algorithm. For circuits up to a million gates, the fault coverage could be increased considerably compared to a state-of-the-art commercial tool with very competitive runtimes.

Detailed knowledge of a circuit's timing is essential for performance optimization, timing closure, and generation of test patterns to detect small-delay defects. When an input transition is applied to the circuit's inputs, the resulting delay is not only determined by the propagation path, but also influenced by the power-supply noise. We introduce a path-sensitization procedure which precisely controls the switching activity in the circuit region surrounding the path. The procedure can maximize or minimize switching activity, or set it to a user-specified value. We study the accuracy-vs.-efficiency trade-offs for a hierarchy of timing models, from coarse zero-delay assumption to a waveform-accurate approach with sub-cycle resolution. For the first time, we present a MaxSAT formulation which guarantees maximization or minimization of switching activity, stemming from transitions and from glitches, simultaneously with path sensitization. We validate the quality of the generated test patterns using a mixed-mode IR-drop-aware timing simulator.

Reconfigurable scan networks (RSN) as standardized by IEEE Std 1687 allow flexible and efficient access to on-chip infrastructure for test and diagnosis, post-silicon validation, debug, bring-up, or maintenance in the field. However, unauthorized access or manipulation of the attached instruments, monitors, or controllers pose security and safety risks. Different RSN architectures have recently been proposed to implement secure access to the connected instruments, for instance by authentication and authorization. To ensure that the implemented security schemes cannot be bypassed, design verification of the security properties is mandatory. However, combinational and deep sequential dependencies of modern RSNs and their extensions for security require novel approaches to formal verification for unbounded model checking. This work presents for the first time a formal design verification methodology for security properties of RSNs based on unbounded model checking that is able to verify access protection at logical level. Experimental results demonstrate that state-of-the-art security schemes for RSNs can be efficiently handled, even for very large designs.

Functional test and software-based self-test (SBST) approaches for processors are becoming popular as they enable low-cost production tests and are often the only solution for in-field tests. With the increasing use of volume diagnosis, efficient and cost-effective diagnosis methods are required. A high quality functional or SBST test program can be used to perform logic fault diagnosis with low-cost test equipment and therefore significantly reduce the cost of diagnosis. We present a framework for the automatic generation of functional diagnostic sequences for stuck-at faults. The framework allows a user to specify constraints imposed by the employed test environment and generates diagnostic sequences satisfying these constraints. Furthermore, the framework is able to prove the equivalence of faults under the specified constraints. This enables to compute the best possible diagnostic quality that can be reached under the given environmental constraints. Also, it gives the necessary information for implementing selective DFT techniques in order to differentiate faults which cannot be distinguished otherwise. In our experiments we evaluated a MIPS-like processor. The results show that our approach can effectively distinguish fault pairs or prove their equivalence, under different environmental constraints. To the best, of our knowledge, this is the first approach which, enables the automatic generation of diagnostic SBST, programs and allows to eectively prove the equivalence of faults in functional and SBST test environments.

Knowledge about sensitizable paths through combinational logic is essential for numerous design tasks. We present the framework PHAETON which identifies sensitizable paths and generates test pairs to exercise these paths using Boolean satisfiability (SAT). PHAETON supports a large number of models and sensitization conditions and provides a generic interface that can be used by applications. It incorporates a novel application-specific unary representation of integer numbers to integrate timing information with logical conditions within the same monolithic SAT formula. Due to a number of further elaborate speed-up techniques, PHAETON scales to industrial circuits. Experimental results show the performance of PHAETON in classical K longest path generation tasks and in new post-silicon validation and characterization scenarios.

Software-based self-test (SBST) techniques are used to test processors and processor cores against permanent faults introduced by the manufacturing process or to perform in-field test in safety-critical applications. However, the generation of an SBST program is usually associated with high costs as it requires significant manual effort of a skilled engineer with in-depth knowledge about the processor under test. In this paper, we propose an approach for the automatic generation of SBST programs. First, we detail an automatic test pattern generation (ATPG) framework for the generation of functional test sequences. Second, we describe the extension of this framework with the concept of a validity checker module (VCM), which allows the specification of constraints with regard to the generated sequences. Third, we use the VCM to express typical constraints that exist when SBST is adopted for in-field test. In our experimental results, we evaluate the proposed approach with a microprocessor without interlocked pipeline stages (MIPS)-like microprocessor. The results show that the proposed method is the first approach able to automatically generate SBST programs for both end-of-manufacturing and in-field test whose fault efficiency is superior to those produced by state-of-the-art manual approaches.

Physically unclonable functions (PUFs) based on ring oscillators (ROs) are a popular primitive in hardware security, meant to enable the unambiguous and tamper-proof identification of computer chips. This is achieved by exploiting different signal delays on each chip stemming from uncontrollable variations during the manufacturing process. Thus, the relation between RO frequencies on an individual chip can be used as the chip's unique PUF signature. In this work, we show how ROs implemented on a larger number of Altera Cyclone IV FPGAs are biased towards slower or faster frequencies in non-uniform ways depending on the FPGA's programming with different design; even though the ROs are placed and routed equally. Without considering these biases, inter-device uniqueness of the PUF signatures is degraded. We demonstrate that subtracting the mean frequency of each RO - derived using only a small training set of devices - from the sampled frequencies overcomes this disadvantage; i.e. the uniqueness is increased drastically while maintaining reliability.

Power-related problems in at-speed scan testing have become more and more serious, since excessive IR-drop caused by excessive power consumption results in overtesting. There are two important factors in low-power testing: one is power estimation, the other is power reduction. Several estimation methods have been proposed based on the analysis of switching activity characteristics. In order to estimate the impact of IR-drop, it is more important to consider the area containing many cells which consume excessive power than to consider the total number of switching activity in a circuit. In this paper, we propose a novel method for identifying areas where excessive IR-drop likely occurs without using test vectors. Visualized experimental results for IWLS 2005 benchmark circuits demonstrate that the proposed method can effectively identify areas containing many cells which consume higher power than others. Such areas identified can be used in low-power test generation so as to achieve effective and efficient results.

Interconnect opens are known to be one of the predominant defects in nanoscale technologies. Generating tests to detect such defects is challenging due to the need to accurately determine the coupling capacitances between the open net and its aggressors and fix the state of these aggressors during test. Process variations cause deviations from assumed values of circuit parameters thus potentially invalidating tests generated with assumed circuit parameters. Additionally, recent investigation using test chips showed that the steady state voltage on open nets may drift slowly with the application of circuit inputs and can be different at different nets.

Manufactured VLSI circuits using a new technology typically suffer from systematic defects that are process-dependent and at sub-nanometer feature sizes such defects may be even design-dependent. The root causes for systematic defects must be determined to ramp up yields. Volume diagnosis is becoming popular to identify root causes for systematic defects. Volume diagnosis uses logic diagnosis based on failing circuit responses to production tests of a large number of failing devices, followed by statistical analysis methods to determine the root cause(s) for yield limiters. Typically production tests use fault detection tests and hence may have limited diagnosis resolution. To improve diagnosis resolution diagnostic ATPGs can be used to generate test sets to distinguish all pairs of distinguishable faults in one or more fault models. The sizes of such tests tend to be considerably higher than fault detection test sets used as production tests. For this reason, generation of test sets that detect faults and also possess a high diagnosis resolution is important. In this work we present a method to improve the diagnosis resolution of a compact fault detection test set without increasing pattern count or decreasing fault coverage. The basic idea of the approach is to generate a SAT formula which enforces diagnosis and is solved by a MAX-SAT solver which is a SAT-based maximization tool. We believe this is the first time a method to improve diagnosis resolution of a test set of given size has been reported. Experimental results on ISCAS 89 circuits demonstrate the effectiveness of the proposed method.

Unknown (X) values emerge during the design process as well as during system operation and test application. X-sources are for instance black boxes in design models, clock-domain boundaries, analog-to-digital converters, or uncontrolled or uninitialized sequential elements. To compute a test pattern for a given fault, well-defined logic values are required both for fault activation and propagation to observing outputs. In presence of X-values, conventional test generation algorithms, based on structural algorithms, Boolean satisfiability (SAT), or binary decision diagram-based reasoning may fail to generate test patterns or to prove faults untestable. This paper proposes the first efficient stuck-at and transition-delay fault test generation algorithm able to prove testability or untestability of faults in presence of X-values. It overcomes the principal pessimism of conventional algorithms when X-values are considered by mapping the test generation problem to the SAT of quantified Boolean formulas. Experiments on ISCAS benchmarks and larger industrial circuits investigate the increase in fault coverage for conventional deterministic and potential detection requirements for both randomized and clustered X-sources.

Vulnerability to malicious fault attacks is an emerging concern for hardware circuits that are employed in mobile and embedded systems and process sensitive data. We describe a new methodology to assess the vulnerability of a circuit to such attacks, taking into account built-in protection mechanisms. Our method is based on accurate modeling of fault effects and detection status expressed by Boolean satisfiability (SAT) formulas. Vulnerability is quantified based on the number of solutions of these formulas, which are determined by an efficient #SAT solver. We demonstrate the applicability of this method for design space exploration of a pseudo random number generator and for calculating the attack success rate in a multiplier circuit protected by robust error-detecting codes.

Open defects such as interconnect opens are known to be one of the predominant defects in nanoscale technologies. Yet, test pattern generation for open defects is challenging because of the high number of parameters which need to be considered. Additionally, the assumed values of these parameters may vary due to process variations reducing fault coverage of a test set generated under this assumption. This paper presents a new ATPG approach for circuit Parameter independent (CPI) tests. In addition a definition of oscillation free CPI tests is given. The generated tests are robust against process variations affecting the influence of neighboring interconnects as well as trapped charge and prohibit oscillating behavior. Experimental results show the high efficiency of the new approach, generating CPI tests for circuits with over 500k nonequivalent faults and several thousand aggressors.

Interconnect opens are known to be one of the predominant defects in nanoscale technologies. However, automatic test pattern generation for open faults is challenging, because of their rather unstable behaviour and the numerous electric parameters which need to be considered. Thus, most approaches try to avoid accurate modeling of all constraints and use simplified fault models in order to detect as many faults as possible or make assumptions which decrease both complexity and accuracy. This paper presents a new SMT-based approach which for the first time supports the Robust Enhanced Aggressor Victim model without restrictions and handles oscillations. It is combined with the first open fault simulator fully supporting the Robust Enhanced Aggressor Victim model and thereby accurately considering unknown values. Experimental results show the high efficiency of the new method outperforming previous approaches by up to two orders of magnitude.

In this paper we present MaxBMC, a novel formalism for solving optimization problems in sequential systems. Our approach combines techniques from symbolic SAT-based Bounded Model Checking (BMC) and incremental MaxSAT, leading to the first MaxBMC solver. In traditional BMC safety and liveness properties are validated. We extend this formalism: in case the required property is satisfied, an optimization problem is defined to maximize the quality of the reached witnesses. Further, we compare its qualities in different depths of the system, leading to Pareto-optimal solutions. We state a sound and complete algorithm that not only tackles the optimization problem but moreover verifies whether a global optimum has been identified by using a complete BMC solver as back-end. As a first reference application we present the problem of circuit initialization. Additionally, we give pointers to other tasks which can be covered by our formalism quite naturally and further demonstrate the efficiency and effectiveness of our approach.

Functional microprocessor test methods provide several advantages compared to DFT approaches, like reduced chip cost and at-speed execution. However, the automatic generation of functional test patterns is an open issue. In this work we present an approach for the automatic generation of functional microprocessor test sequences for small-delay faults based on Bounded Model Checking. We utilize an ATPG framework for small-delay faults in sequential, non-scan circuits and propose a method for constraining the input space for generating functional test sequences (i.e., test programs). We verify our approach by evaluating the miniMIPS microprocessor. In our experiments we were able to reach over 97 % fault efficiency. To the best of our knowledge, this is the first fully automated approach to functional microprocessor test for small-delay faults.

In technologies affected by variability, the detection status of a small-delay fault may vary among manufactured circuit instances. The same fault may be detected, missed or provably undetectable in different circuit instances. We introduce the first complete flow to accurately evaluate and systematically maximize the test quality under variability. As the number of possible circuit instances is infinite, we employ statistical analysis to obtain a test set that achieves a fault-efficiency target with an user-defined confidence level. The algorithm combines a classical path-oriented test-generation procedure with a novel waveform-accurate engine that can formally prove that a small-delay fault is not detectable and does not count towards fault efficiency. Extensive simulation results demonstrate the performance of the generated test sets for industrial circuits affected by uncorrelated and correlated variations.

Test generation algorithms based on standard n-valued logic algebras are pessimistic in presence of unknown (X) values, overestimate the number of signals with X-values and underestimate fault coverage.

Logic and fault simulation are essential techniques in electronic design automation. The accuracy of standard simulation algorithms is compromised by unknown or X-values. This results in a pessimistic overestimation of X-valued signals in the circuit and a pessimistic underestimation of fault coverage. This work proposes efficient algorithms for combinational and sequential logic as well as for stuck-at and transition-delay fault simulation that are free of any simulation pessimism in presence of unknowns. The SAT-based algorithms exactly classifiy all signal states. During fault simulation, each fault is accurately classified as either undetected, definitely detected, or possibly detected. The pessimism with respect to unknowns present in classic algorithms is thoroughly investigated in the experimental results on benchmark circuits. The applicability of the proposed algorithms is demonstrated on larger industrial circuits. The results show that, by accurate analysis, the number of detected faults can be significantly increased without increasing the test-set size.

Circuits that employ test pattern compression rely on test cubes to achieve high compression ratios. The less inputs of a test pattern are specified, the better it can be compacted and hence the lower the test application time. Although there exist previous approaches to generate such test cubes, none of them are optimal. We present for the first time a framework that yields provably optimal test cubes by using the theory of quantified Boolean formulas (QBF). Extensive comparisons with previous methods demonstrate the quality gain of the proposed method.

Unknown (X) values in a circuit impair test quality and increase test costs. Classical n-valued algorithms for fault simulation and ATPG, which typically use a three- or four-valued logic for the good and faulty circuit, are in principle pessimistic in presence of X-values and cannot accurately compute the achievable fault coverage. In partial scan or pipelined circuits, X-values originate in non-scan flip-flops. These circuits are tested using multi-cycle tests. Here we present multi-cycle test generation techniques for circuits with X-values due to partial scan or other X-sources. The proposed techniques have been integrated into a multi-cycle ATPG framework which employs formal Boolean and quantified Boolean (QBF) satisfiability techniques to compute the possible signal states in the circuit accurately. Efficient encoding of the problem instance ensures reasonable runtimes. We show that in presence of X-values, the detection of stuck-at faults requires not only exact formal reasoning in a single cycle, but especially the consideration of multiple cycles for excitation of the fault site as well as propagation and controlled reconvergence of fault effects. For the first time, accurate deterministic ATPG for multi-cycle test application is supported for stuck-at faults. Experiments on ISCAS'89 and industrial circuits with X-sources show that this new approach increases the fault coverage considerably.

Ongoing research to shrink feature sizes of LSI circuits leads to an always increasing number of logic gates in a circuit. In general, the complexity of test generation depends on the size of a circuit. Furthermore, modern test generation methods have to consider power reduction in addition to fault detection, since excessive power caused by testing may result in over testing. In this work, we propose a method to reduce the computation time of low-power test generation. The proposed method specifies gates which will cause power issues, consequently reducing the search space for X-filling technique. The reduction of search space for Xfilling also further minimizes the amount of switching activity. Experimental results for circuits of Open Cores provided by IWLS2005 benchmarks show that the proposed method achieves both a reduced computation time and at the same time increased power reduction compared to previous methods.

Comprehensive coverage of small-delay faults under massive process variations is achieved when multiple paths through the fault locations are sensitized by the test pair set. Using one test pair per path may lead to impractical test set sizes and test application times due to the large number of near-critical paths in state-of-the-art circuits.

We consider the partial equivalence checking problem (PEC), i. e., checking whether a given partial implementation of a combinational circuit can (still) be extended to a complete design that is equivalent to a given full specification. To solve PEC, we give a linear transformation from PEC to the question whether a dependency quantified Boolean formula (DQBF) is satisfied. Our novel algorithm to solve DQBF based on quantifier elimination can therefore be applied to solve PEC.We also present first experimental results showing the feasibility of our approach and the inaccuracy of QBF approximations, which are usually used for deciding the PEC so far.

Early-life failures (ELF) result from weak chips that may pass manufacturing tests but fail early in the field, much earlier than expected product lifetime. Recent experimental studies over a range of technologies have demonstrated that ELF defects result in changes in delays over time inside internal nodes of a logic circuit before functional failure occurs. Such changes in delays are distinct from delay degradation caused by circuit aging mechanisms such as Bias Temperature Instability. Traditional transition fault or robust path delay fault test patterns are inadequate for detecting such ELF-induced changes in delays because they do not model the demanding detection conditions precisely. In this paper, we present an automatic test pattern generation (ATPG) technique based on Boolean Satisfiability (SAT) for detecting ELF-induced delay changes at all gates in a given circuit. Our simulation results, using various circuit blocks from the industrial OpenSPARC T2 design as well as standard benchmarks, demonstrate the effectiveness and practicality of our approach in achieving high coverage of ELF-induced delay change detection. We also demonstrate the robustness of our approach to manufacturing process variations.

The shrinking nanometer technologies of modern microprocessors and the aggressive supply voltage down-scaling drastically increase the risk of soft errors. In order to cope with this risk efficiently, selective hardware and software protection schemes are applied. In this paper, we propose an FPGA-based fault injection framework which is able to identify the most critical registers of an entire microprocessor. Further-more, our framework identifies critical variables in the source code of an arbitrary application running in its native environment. We verify the feasibility and relevance of our approach by implementing a lightweight and efficient error correction mechanism protecting only the most critical parts of the system. Experimental results with state estimation applications demonstrate a significantly reduced number of critical calculation errors caused by faults injected into the processor.

An iterative flow to generate test sets providing high fault coverage under extreme parameter variations is presented. The generation is guided by the novel metric of circuit coverage, calculated by massively parallel statistical fault simulation on GPGPUs. Experiments show that the statistical fault coverage of the generated test sets exceeds by far that achieved by standard approaches.

Adequate coverage of small-delay defects in circuits affected by statistical process variations requires identification and sensitization of multiple paths through potential defect sites. Existing K longest path generation (KLPG) algorithms use a data structure called path store to prune the search space by restricting the number of sub-paths considered at the same time. While this restriction speeds up the KLPG process, the algorithms lose their optimality and do not guarantee that the K longest sensitizable paths are indeed found. We investigate, for the first time, the effects of missing some of the longest paths on the defect coverage. We systematically quantify how setting different limits on the path-store size affects the numbers and relative lengths of identified paths, as well as the run-times of the algorithm. We also introduce a new optimal KLPG algorithm that works iteratively and pinpointedly addresses defect locations for which the path-store size limit has been exceeded in previous iterations. We compare this algorithm with a naïve KLPG approach that achieves optimality by setting the path-store size limit to a very large value. Extensive experiments are reported for 45nm-technology data.

Power droop is a non-trivial signal-integrity-related effect triggered by specific power-supply conditions. High-frequency and low-frequency power droop may lead to failure of an IC during application time, but they usually remain undetected by state-of-the-art manufacturing test methods, as the fault excitation imposes particular conditions on global switching activity over several time frames. Hence, ATPG for power-droop test (PD-ATPG) is an extremely hard problem that has not yet been solved optimally. In this paper, we use a SAT-based ATPG engine that employs a mechanism known as SAT-solving with qualitative preferences to generate a solution guaranteed to be optimal for a given set of optimisation criteria, however at the expense of high SAT-solving times. Therefore, a well-balanced set of criteria has to be chosen for the SAT-formulation in order to get as good solutions as possible without rendering the SAT-instances impracticably hard. We explore several strategies and evaluate them experimentally.

Post-silicon validation, i.e., physical characterization of a small number of fabricated circuit instances before start of high-volume manufacturing, has become an essential step in integrated circuit production. Post-silicon validation is required to identify intricate logic or electrical bugs which could not be found during pre-silicon verification. In addition, physical characterization is useful to determine the performance distribution of the manufactured circuit instances and to derive performance yield. Test vectors used for this step are subject to different requirements compared to vectors for simulation-based verification or for manufacturing test. In particular, they must sensitize a very comprehensive set of paths in the circuit, assuming massive variations and possible modeling deficiencies. An inadequate test vector set may result in overly optimistic yield estimates and wrong manufacturing decisions. On the other hand, the size of the test vector set is less important than in verification or manufacturing test. In this paper, we systematically investigate the relationship between the quality of the employed test vectors and the accuracy of yield-performance predictions. We use a highly efficient SAT-based algorithm to generate comprehensive test vector sets based on simple model assumptions and validate these test sets using simulated circuit instances which incorporate effects of process variations. The obtained vector sets can also serve as a basis for adaptive manufacturing test.

The detection of small-delay faults is traditionally performed by sensitizing transitions on a path of sufficient length from an input to an output of the circuit going through the fault site. While this approach allows efficient test generation algorithms, it may result in false positives and false negatives as well, i.e. undetected faults are classified as detected or detectable faults are classified as undetectable. We present an automatic test pattern generation algorithm which considers waveforms and their propagation on each relevant line of the circuit. The model incorporates individual delays for each gate and filtering of small glitches. The algorithm is based on an optimized encoding of the test generation problem by a Boolean satisfiability (SAT) instance and is implemented in the tool WaveSAT. Experimental results for ISCAS-85, ITC-99 and industrial circuits show that no known definition of path sensitization can eliminate false positives and false negatives at the same time, thus resulting in inadequate small-delay fault detection. WaveSAT generates a test if the fault is testable and is also capable of automatically generating a formal redundancy proof for undetectable small-delay faults; to the best of our knowledge this is the first such algorithm that is both scalable and complete.

We present SATSEQ, a timing-aware ATPG system for small-delay faults in non-scan circuits. The tool identifies the longest paths suitable for functional fault propagation and generates the shortest possible sub-sequences per fault. Based on advanced model-checking techniques, SATSEQ provides detection of small-delay faults through the longest functional paths. All test sequences start at the circuit's initial state; therefore, overtesting is avoided. Moreover, potential invalidation of the fault detection is taken into account. Experimental results show high detection and better performance than scan testing in terms of test application time and overtesting-avoidance.

Failures caused by phenomena such as crosstalk or power-supply noise are gaining in importance in advanced nanoscale technologies. The detection of such complex defects benefits from the satisfaction of certain constraints, for instance justifying specific transitions on neighbouring lines of the defect location. We present a SAT-based ATPG-tool that supports the enhanced conditional multiple-stuck-at fault model (ECMS@). This model can specify multiple fault locations along with a set of hard conditions imposed on arbitrary lines; hard conditions must hold in order for the fault effect to become active. Additionally, optimisation constraints that may be required for best coverage can be specified via a set of soft conditions. The introduced tool justifies as many of these conditions as possible, using a mechanism known as SAT with preferences. Several applications are discussed and evaluated by extensive experimental data. Furthermore, a novel fault-clustering technique is introduced, thanks to which the time required to classify all stuck-at faults in a suite of industrial benchmarks was reduced by up to 65%.

We present a versatile method that enumerates all or a user-specified number of longest sensitisable paths in the whole circuit or through specific components. The path information can be used for design and test of circuits affected by statistical process variations. The algorithm encodes all aspects of the path search as an instance of the Boolean Satisfiability Problem (SAT), which allows the method not only to benefit from recent advances in SAT-solving technology, but also to avoid some of the drawbacks of previous structural approaches. Experimental results for academic and industrial benchmark circuits demonstrate the method's accuracy and scalability.

Manufacturing defects in nanoscale technologies have highly complex timing behaviour that is also affected by process variations. While conventional wisdom suggests that it is optimal to detect a delay defect through the longest sensitisable path, non-trivial defect behaviour along with modelling inaccuracies necessitate consideration of paths of well-controlled length during test generation. We present a generic methodology that yields tests through all sensitisable paths of user-specified length. The resulting tests can be employed within the framework of adaptive testing. The methodology is based on encoding the problem as a Boolean-satisfiability (SAT) instance and thereby leverages recent advances in SAT-solving technology.

Nanoscale integrated circuits suffer both from high defect densities and increased parameter variations possibly affecting the overall timing behaviour. Components with a higher vulnerability to process variations are not just critical during test design and test application, but also during normal operation. In particular, ageing effects and changes in the operation environment including supply voltage, temperature and radiation, can easily aggravate the effects of parameter variations inherent to the manufacturing process. Online and offline techniques that attempt to cope with such effects, like online error detection and correction, online diagnosis and hardening, have high cost and therefore cannot be applied to the whole circuit. Making a good selection of components to apply these techniques to, requires accurate metrics for gate criticality under process variations. This paper presents a SAT-based approach to measure criticality. The algorithm requires a minimal amount of physical and electrical data, but it delivers a very good criticality estimate in a fraction of the time required by accurate statistical simulation. The results are validated by comparison to an exact simulation-based approach.

State-of-the-art cyber-physical systems are increasingly deployed in harsh environments with non-negligible soft error rates, such as aviation or search-and-rescue missions. State-of-the-art nanoscale manufacturing technologies are more vulnerable to soft errors. In this paper, we present an FPGA-based framework for injecting soft errors into user-specified memory elements of an entire microprocessor (MIPS32) running application software. While the framework is applicable to arbitrary software, we demonstrate its usage by characterizing soft errors effects on several software filters used in aviation for probabilistic sensor data fusion.