Manufacture testing of digital integrated circuits is essential for high quality. However, exhaustive testing is impractical, and only a small subset of all possible test patterns (or test pattern pairs) may be applied. Thus, it is crucial to choose a subset that detects a high percentage of the defective parts and produces a low defective part level. Historically, test pattern generation has often been seen as a deterministic endeavor. Test sets are generated to deterministically ensure that a large percentage of the targeted faults are detected. However, many real defects do not behave like these faults, and a test set that detects them all may still miss many defects. Unfortunately, modeling all possible defects as faults is impractical. Thus, it is important to fortuitously detect unmodeled defects using high quality test sets. To maximize fortuitous detection, we do not assume a high correlation between faults and actual defects. Instead, we look at the common requirements for all defect detection. We deterministically maximize the observations of the leastobserved sites while randomly exciting the defects that may be present. The resulting decrease in defective part level is estimated using the MPGD model. This dissertation describes the MPGD defective part level model and shows how it can be used to predict defective part levels resulting from static defect detection. Unlike many other predictors, its predictions are a function of site observations, not fault coverage, and thus it is generally more accurate at high fault coverages. Furthermore, its components model the physical realities of site observation and defect excitation, and thus it can be used to give insight into better test generation strategies. Next, we investigate the effect of additional constraints on the fortuitous detection of defects-specifically, as we focus on detecting dynamic defects instead of static ones. We show that the quality of the randomness of excitation becomes increasingly important as defect complexity increases. We introduce a new metric, called excitation balance, to estimate the quality of the excitation, and we show how excitation balance relates to the constant τ in the MPGD model.

Projekto tikslas – sukurti sistemą, skirtą schemų testinių atvejų atrinkimui naudojant „juodos dėžės“ modelius ir jiems pritaikytus gedimų modelius. Vykdant projektą buvo atlikta kūrino būdų ir technologijų analizė. Sistemos architektūra buvo kuriama atsižvelgiant į reikalavimą, naudoti schemų modelius, kurie yra parašyti c programavimo kalba. Buvo atlikta schemų failų integravimo efektyvumo analizė, tiriamos atsitiktinio testinių atvejų generavimo sekos patobulinimo galimybės, "1" pasiskirstymo 5taka atsitiktinai generuojam7 testini7 atvej7 kokybei. Tyrim7 rezultatai: • Schemų modelių integracijos tipas mažai įtakoja sistemos darbą. • Pusiau deterministinių metodų taikymas parodė, jog atskirų žingsnių optimizacija nepagerina galutinio rezultato. • "1" pasiskirstymas atsitiktinai generuojamose sekose turi įtaką testo kokybei ir gali būti naudojamas testų procesų pagerinimui. / Project objective – to develop a system, which generates functional tests for non-scan synchronous sequential circuits based on functional delay models. During project execution, the analysis of design and technology solutions was performed. The architecture of the developed software is based on the requirement to be able to use the models of the benchmark circuits that are written in C programming language. Analysis of the effectiveness of the model file integration, possibilities of improving random test sequence generation and the influence of distribution of „1“ in randomly generated test patterns was performed. The results of the analysis were: • Type of the model file integration has little effect when using large circuit models. • The implementation of semi deterministic algorithms showed that the optimisation of separate steps by construction of test subsequences doesn’t improve the final outcome. • The distribution of „1“ in randomly generated test patterns has effect on the fault coverage and can be used to improve test generation process.

Στην εργασία, αυτή, εξετάζονται οι μέθοδοι συμπίεσης του συνόλου δοκιμής με τη χρήση πινάκων που έχουν ήδη προταθεί και προτείνεται μία νέα μέθοδος συμπίεσης δεδομένων δοκιμής για πυρήνες που ο έλεγχος ορθής λειτουργίας υλοποιείται μέσω μονοπατιών ολίσθησης. Η νέα μέθοδος επαναχρησιμοποιεί μπλοκ του πίνακα για τη σύνθεση διανυσμάτων δοκιμής. Δύο νέοι αλγόριθμοι παρουσιάζονται για επιλεκτική και πλήρη καταχώρηση τμημάτων του συνόλου δοκιμής σε πίνακα. Η προτεινόμενη μέθοδος συγκρίνεται με τις υπάρχουσες μεθόδους ως προς το ποσοστό συμπίεσης αλλά και ως προς το κόστος υλοποίησης. Για την αξιολόγηση της μεθόδου λαμβάνονται υπόψη σύνολα δοκιμής που έχουν παραχθεί για την ανίχνευση απλών σφαλμάτων μόνιμης τιμής, απλών σφαλμάτων μόνιμης τιμής με πολλαπλότητα ανίχνευσης Ν (Ν-detect) και σφαλμάτων καθυστέρησης μετάβασης. / In this work we refer to dictionary based test data compression methods. At first the already known dictionary based test data compression methods are comparably presented. Then we propose a new method and we show that the test data compression achieved by a dictionary based method can be improved significantly by suitably reusing parts of the dictionary entries. To this end two new algorithms are proposed, suitable for partial and complete dictionary coding respectively. For the evaluation of the proposed method, test sets have been generated and used based on the stuck-at fault model for single and N detection of each fault as well as on the transition fault model.