Exploring the Mysteries of System-Level Test

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.Comment: 7 pages, 2 figure

New techniques for functional testing of microprocessor based systems

Electronic devices may be affected by failures, for example due to physical defects. These defects may be introduced during the manufacturing process, as well as during the normal operating life of the device due to aging. How to detect all these defects is not a trivial task, especially in complex systems such as processor cores. Nevertheless, safety-critical applications do not tolerate failures, this is the reason why testing such devices is needed so to guarantee a correct behavior at any time. Moreover, testing is a key parameter for assessing the quality of a manufactured product. Consolidated testing techniques are based on special Design for Testability (DfT) features added in the original design to facilitate test effectiveness. Design, integration, and usage of the available DfT for testing purposes are fully supported by commercial EDA tools, hence approaches based on DfT are the standard solutions adopted by silicon vendors for testing their devices. Tests exploiting the available DfT such as scan-chains manipulate the internal state of the system, differently to the normal functional mode, passing through unreachable configurations. Alternative solutions that do not violate such functional mode are defined as functional tests. In microprocessor based systems, functional testing techniques include software-based self-test (SBST), i.e., a piece of software (referred to as test program) which is uploaded in the system available memory and executed, with the purpose of exciting a specific part of the system and observing the effects of possible defects affecting it. SBST has been widely-studies by the research community for years, but its adoption by the industry is quite recent. My research activities have been mainly focused on the industrial perspective of SBST. The problem of providing an effective development flow and guidelines for integrating SBST in the available operating systems have been tackled and results have been provided on microprocessor based systems for the automotive domain. Remarkably, new algorithms have been also introduced with respect to state-of-the-art approaches, which can be systematically implemented to enrich SBST suites of test programs for modern microprocessor based systems. The proposed development flow and algorithms are being currently employed in real electronic control units for automotive products. Moreover, a special hardware infrastructure purposely embedded in modern devices for interconnecting the numerous on-board instruments has been interest of my research as well. This solution is known as reconfigurable scan networks (RSNs) and its practical adoption is growing fast as new standards have been created. Test and diagnosis methodologies have been proposed targeting specific RSN features, aimed at checking whether the reconfigurability of such networks has not been corrupted by defects and, in this case, at identifying the defective elements of the network. The contribution of my work in this field has also been included in the first suite of public-domain benchmark networks

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%

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

Methods for testing of analog circuits

Práce se zabývá metodami pro testování lineárních analogových obvodů v kmitočtové oblasti. Cílem je navrhnout efektivní metody pro automatické generování testovacího plánu. Snížením počtu měření a výpočetní náročnosti lze výrazně snížit náklady za testování. Práce se zabývá multifrekveční parametrickou poruchovou analýzou, která byla plně implementována do programu Matlab. Vhodnou volbou testovacích kmitočtů lze potlačit chyby měření a chyby způsobené výrobními tolerancemi obvodových prvků. Navržené metody pro optimální volbu kmitočtů byly statisticky ověřeny metodou MonteCarlo. Pro zvýšení přesnosti a snížení výpočetní náročnosti poruchové analýzy byly vyvinuty postupy založené na metodě nejmenších čtverců a přibližné symbolické analýze.The thesis deals with methods for testing of linear analog circuits in the frequency domain. The goal is to develop new efficient methods for automatic test plan generation. To reduce test costs a minimum number of measurements as well as less computational demands are the fundamental aims. The thesis is focused on the multi-frequency parametric fault diagnosis which was fully implemented in the Matlab program. The fundamental problem consists in selection of test frequencies which can reduce the influences of measurement errors and errors caused by tolerances of well-working components. The proposed methods for test frequency selection were statistically verified by the MonteCarlo method. To improve the accuracy and reduce the computational complexity of fault diagnosis, the methods based on least-square techniques and approximate symbolic analysis were presented.

Test and Diagnosis of Integrated Circuits

The ever-increasing growth of the semiconductor market results in an increasing complexity of digital circuits. Smaller, faster, cheaper and low-power consumption are the main challenges in semiconductor industry. The reduction of transistor size and the latest packaging technology (i.e., System-On-a-Chip, System-In-Package, Trough Silicon Via 3D Integrated Circuits) allows the semiconductor industry to satisfy the latest challenges. Although producing such advanced circuits can benefit users, the manufacturing process is becoming finer and denser, making chips more prone to defects.The work presented in the HDR manuscript addresses the challenges of test and diagnosis of integrated circuits. It covers:- Power aware test;- Test of Low Power Devices;- Fault Diagnosis of digital circuits