The conventional approach for testing RF circuits is specification-based testing, which involves verifying sequentially all specification requirements that are promised in the data sheet. This approach is a long-time effective testapproach but nowadays suffers from significant drawbacks.First, it requires generation and capture of test signals at the DUT operating frequency. As the operational frequencies of DUT are increasing, it becomes difficult to manage signal generation and capture using ATE. As a consequence, there is a need of expensive and specialized equipment. In addition,as conventional tests target several parameters, there is a need of several data captures and multiple test configurations. As a consequence, by adding settling time between each test and test application time, the whole test time becomes very long, and the test board very complex. Another challenge regarding RF circuit testing is wafer-level testing. Indeed, the implementation of specification-based tests at wafer level is extremely difficult due to probing issues and high parasitic effects on the test interface.Moreover, multi-site testing is usually not an option due to the small count of available RF test resources, which decreases test throughput. Hence, the current practice is often to verify the device specifications only after packaging.The problem with this solution is that defective dies are identified late in the manufacturing flow, which leads to packaging loss and decreases the global yield of the process.In order to reduce production costs, there is therefore a need to develop test solutions applicable at wafer level, so that faulty circuits can be removed very early in the production flow. This is particularly important for dies designed to be integrated in Systems-In-Package (SIP).In this context, a promising solution is to develop indirect test methods. Basically, it consists in using DUT signatures to non-conventional stimuli to predict the result of conventional tests. The underlying idea is to learn during an initial phase the unknown dependency between simple measurements and conventional tests. This dependency can then be modeled through regression functions. During the testing phase, only the indirect measurements are performed and specifications are predicted using the regression model built in the learning phase.Our work has been focused on two main directions. First, we have explored the implementation of the alternate test method based on DC measurements for RF circuits and we have proposed a methodology to select the most appropriateset of DC parameters. Results from two test vehicles (a LNA using electrical simulations and a PA using real production data) indicate that the proposed methodology allows precise estimation of the DUT performances while minimizing the number of DC measurements to be carried out.Second, we have proposed a novel implementation of the alternate test strategy in order to improve confidence in alternate test predictions and to overcome the effect of limited training set sizes. The idea is to exploit model redundancy in order to identify, during the production testing phase, devices with suspect predictions; these devices are then are removed from the alternate test tierand directed to a second tier where further testing may apply. / The conventional approach for testing RF circuits is specification-based testing, which involves verifying sequentially all specification requirements that are promised in the data sheet. This approach is a long-time effective testapproach but nowadays suffers from significant drawbacks.First, it requires generation and capture of test signals at the DUT operating frequency. As the operational frequencies of DUT are increasing, it becomes difficult to manage signal generation and capture using ATE. As a consequence, there is a need of expensive and specialized equipment. In addition,as conventional tests target several parameters, there is a need of several data captures and multiple test configurations. As a consequence, by adding settling time between each test and test application time, the whole test time becomes very long, and the test board very complex.Another challenge regarding RF circuit testing is wafer-level testing. Indeed, the implementation of specification-based tests at wafer level is extremely difficult due to probing issues and high parasitic effects on the test interface.Moreover, multi-site testing is usually not an option due to the small count of available RF test resources, which decreases test throughput. Hence, the current practice is often to verify the device specifications only after packaging.The problem with this solution is that defective dies are identified late in the manufacturing flow, which leads to packaging loss and decreases the global yield of the process.In order to reduce production costs, there is therefore a need to develop test solutions applicable at wafer level, so that faulty circuits can be removed very early in the production flow. This is particularly important for dies designed to be integrated in Systems-In-Package (SIP).In this context, a promising solution is to develop indirect test methods. Basically, it consists in using DUT signatures to non-conventional stimuli to predict the result of conventional tests. The underlying idea is to learn during an initial phase the unknown dependency between simple measurements and conventional tests. This dependency can then be modeled through regression functions. During the testing phase, only the indirect measurements are performed and specifications are predicted using the regression model built in the learning phase.Our work has been focused on two main directions. First, we have explored the implementation of the alternate test method based on DC measurements for RF circuits and we have proposed a methodology to select the most appropriateset of DC parameters. Results from two test vehicles (a LNA using electrical simulations and a PA using real production data) indicate that the proposed methodology allows precise estimation of the DUT performances while minimizing the number of DC measurements to be carried out.Second, we have proposed a novel implementation of the alternate test strategy in order to improve confidence in alternate test predictions and to overcome the effect of limited training set sizes. The idea is to exploit model redundancy in order to identify, during the production testing phase, devices with suspect predictions; these devices are then are removed from the alternate test tierand directed to a second tier where further testing may apply.

Être en mesure de vérifier si un circuit intégré est fonctionnel après fabrication peut s'avérer très difficile. Dans le cas des circuits analogiques et Radio Fréquence (RF) les procédures et les équipements de test nécessaires ont un impact majeur sur le prix de revient des circuits. Une approche intéressante pour réduire l'impact du coût du test consiste à mesurer des paramètres nécessitant des ressources de test faible coût et corréler ces mesures, dites mesures indirectes, avec les spécifications à tester. On parle alors de technique de test indirect (ou test alternatif) car il n'y a pas de mesure directe des spécifications, qui nécessiterait des équipements et du temps de test importants, mais ces spécifications sont estimées à partir des mesures « faibles couts ». Même si cette approche semble attractive elle n'est viable que si nous sommes en mesure d'établir une précision suffisante de l'estimation des performances et que cette estimation reste stable et indépendante des lots de circuits à traiter. L'objectif principal de cette thèse est de mettre en œuvre une stratégie générique permettant de proposer un flot de test indirect efficace et robuste. Pour être en mesure de construire cette stratégie nous avons amenés différentes contributions. Dans un premier temps, on a développée une nouvelle métrique dans cette thèse pour évaluer la robustesse des prédictions relaissées. Dans un deuxième temps, on a défini et analysé une stratégie pour la construction d'un model optimal. Cette dernière englobe un prétraitement de données ensuite une analyse comparative entre différentes méthodes de sélections de mesures indirectes aussi l'étude d'autres paramètres tels que la taille des combinaisons de mesures indirectes ainsi que celle de la taille de set d'apprentissage. Aussi on a proposé une stratégie pour une confidente exploration d'espace de mesures indirectes afin de construire plusieurs meilleurs modèles qu'on peut se servir par la suite pour résoudre des problèmes de confiance et d'optimisation. Les études comparatives réalisées ont été effectuées sur 2 cas d'études expérimentaux et à partir de métriques classiques et de la nouvelle métrique proposée permettant ainsi d'évaluer objectivement la robustesse de chaque solution.En fin, nous avons développé une stratégie complète mettant en œuvre des techniques de redondance de modèles de corrélation qui permettent d'améliorer grandement la robustesse et l'efficacité de la prise de décision en fonction des mesures obtenues. Cette stratégie est adaptable à n'importe quel contexte en termes de compromis entre le coût du test et le niveau de confiance et de précision attendu. / Being able to check whether an IC is functional or not after the manufacturing process is very difficult. Particularly for analog and Radio Frequency (RF) circuits, test equipment and procedures required have a major impact on the circuits cost. An interesting approach to reduce the impact of the test cost is to measure parameters requiring low cost test resources and correlate these measurements, called indirect measurements, with the targeted specifications. This is known as indirect test technique because there is no direct measurement for these specifications, which requires so expensive test equipment and an important testing time, but these specifications are estimated w.r.t "low-cost measurements". While this approach seems attractive, it is only viable if we are able to establish a sufficient accuracy for the performance estimation and if this estimation remains stable and independent from the circuits sets under test.The main goal of this thesis is to implement a robust and effective indirect test strategy for a given application and to improve test decisions based on data analysis.To be able to build this strategy, we have brought various contributions. Initially, we have defined new metric developed in this thesis to assess the reliability of the estimated performances. Secondly, we have analyzed and defined a strategy for the construction of an optimal model. This latter includes a data preprocessing followed by a comparative analysis of different methods of indirect measurement selection. Then, we have proposed a strategy for a confidant exploration of the indirect measurement space in order to build several best models that can be used later to solve trust and optimization issues. Comparative studies were performed on 2 experimental data sets by using both of the conventional and the developed metrics to evaluate the robustness of each solution in an objective way.Finally, we have developed a comprehensive strategy based on an efficient implementation of the redundancy techniques w.r.t to the build models. This strategy has greatly improved the robustness and the effectiveness of the decision plan based on the obtained measurements. This strategy is adaptable to any context in terms of compromise between the test cost, the confidence level and the expected precision.

To study of cognitive fear networks and associations, indirect experimental paradigms like the Implicit Association Test (IAT, Greenwald et al., 1998) or the Extrinsic Affective Simon Task (EAST, De Houwer, 2003) may be helpful, as they promise to assess the structure of specific associations using a performance based approach without having to ask the participant for a verbal report. Three studies investigated the usefulness and characteristics of IAT and EAST. The aim of the first study was to measure fear associations towards spiders among spider phobic and non-phobic participants as well as in a group of spider enthusiasts. Results indicate that the IAT paradigm is sensitive to the strength of fear relevant associations and able to predict anxious behavior beyond the predictions of direct measures such as questionnaires. The second study focused on some of the mechanisms that underlie IAT effects. With a newly developed masked IAT, these experiments investigated the influences of individual stimuli and superordinate categories on IAT performance. Besides theoretical implications, the results also provide practical, relevant applications for the use of IAT experiments. A third study applied the EAST to investigate how different context conditions lead to differential activation of cognitive schemata in fear of spiders. One can conclude that the impact of automatic threat associations depends on the activated context, and that the EAST is suitable for the assessment of fear associations and their current activation level. This dissertation leads to the conclusion that the performance based methodology of the IAT and EAST is a useful and practical approach to reflect fear associations in phobia indirectly. At this point, the use of indirect measures is still at its beginning, and requires intensive methodological and theoretical efforts. These paradigms, however, may become useful for possible implications in psychopathology and other fields of psychology.