The presence of delay-inducing defects is causing increasing concern in the semiconductor industry today. To test for such delay-inducing defects, scan-based transition fault testing techniques are being implemented. There exist organized techniques to generate test patterns for the transition fault model and the two popular methods being used are Broad-side delay test (Launch-from-capture) and Skewed load delay test (Launch-from-shift). Each method has its own drawbacks and many practical issues are associated with pattern generation and application. Our work focuses on the implementation and comparison of these transition fault testing techniques on multiple industrial ASIC designs. In this thesis, we present results from multiple designs and compare the two techniques with respect to test coverage, pattern volume and pattern generation time. For both methods, we discuss the effects of multiple clock domains, tester hardware considerations, false and multi-cycle paths and the implications of using a low cost tester. We then consider the implications of pattern volume on testing both stuck-at and transition faults and the effects of using transition fault patterns to test stuck-at faults. Finally, we present results from our analysis on switching activity of nets in the design, while executing transition fault patterns. / Master of Science

Modeliais paremtas testavimas tampa vis populiaresnis. Sudėtingos programinės įrangos kokybės užtikrinimas ir modeliais orientuotas sistemų kūrimas yra pagrindinės šio testavimo būdo išpopuliarėjimo priežastys. Pagrindiniai šio darbo tikslai yra modeliais paremtų testavimo įrankių analizė ir jų tobulinimo galimybės. Darbe naudojama daugiau nei dešimt įvairių įrankių vertinimo kriterijų. Analizuojama testų padengimo kriterijų pritaikymo ir tobulinimo galimybės. Analizuojamos modeliais paremto proceso problemos ir pateikiami sprendimo būdai. Atlikta detali testų kūrimo kriterijų ir modelio perėjimo algoritmų analizė. Atlikus detalę kriterijų ir modelio perėjimo algoritmų analizę, pateikiama kriterijų apjungimo privalumai ir kaip naudojant įvairius kriterijus galima valdyti testų kūrimo procesą ir siekti 100 procentinio modelio padengimo. Pateikiama ir detaliai išanalizuojama kriterijų kūrimo metodika, kurią galim taikyti testavimo įrankiuose. / Model-based testing has become increasingly popular in recent years. Major reasons include the need for quality assurance for increasingly complex systems and the emerging model-centric development paradigm. The present thesis aims at analysing model-based testing tools and presents the possibilities for their improvement. More than dozen criteria are applied in analysing selected tools. The paper analyses the application of testing coverage criteria and presents their possible improvements. The problems occurring in the model-based testing process are being analysed and the solutions presented. The study contains an in-depth analysis of test coverage criteria and model traversal algorithms. A thorough analysis of test criteria and model traversal algorithms being performed, the advantages of the integration of test criteria are presented. Furthermore, a solution for managing the development process of test cases as well as pursuing a hundred percent model coverage is proposed. The paper presents a comprehensive analysis of test criteria development methodology that could be applied in testing tools.

Objective: Particular testing by functional decomposition of the automated driving function can potentially contribute to reducing the effort of validating highly automated driving functions. In this study, the required size of test suites for scenario-based testing and the potential to reduce it by functional decomposition are quantified for the first time. Methods: The required size of test suites for scenario-based approval of a so-called Autobahn-Chauffeur (SAE Level 3) is analyzed for an exemplary set of scenarios. Based on studies of data from failure analyses in other domains, the possible range for the required test coverage is narrowed down and suitable discretization steps, as well as ranges for the influence parameters, are assumed. Based on those assumptions, the size of the test suites for testing the complete system is quantified. The effects that lead to a reduction in the parameter space for particular testing of the decomposed driving function are analyzed and the potential to reduce the validation effort is estimated by comparing the resulting test suite sizes for both methods. Results: The combination of all effects leads to a reduction in the test suites’ size by a factor between 20 and 130, depending on the required test coverage. This means that the size of the required test suite can be reduced by 95–99% by particular testing compared to scenario-based testing of the complete system. Conclusions: The reduction potential is a valuable contribution to overcome the parameter space explosion during the validation of highly automated driving. However, this study is based on assumptions and only a small set of exemplary scenarios. Thus, the findings have to be validated in further studies.

Teste de Software tem o objetivo de executar um programa sob teste com o objetivo de revelar suas falhas, portanto é uma das fases mais importante do ciclo de vida do desenvolvimento de um software. A testabilidade é um atributo de qualidade fundamental para o sucesso da atividade de teste, pois ela pode ser entendida como o esforço necessário para criar, executar e avaliar os casos de teste em um software. Este atributo não é uma qualidade intrínseca do software, portanto não pode ser medido diretamente como a quantidade de linhas de código, por exemplo. Entretanto, ela pode ser inferida por meio das características ou métricas internas e externas de um software. Entre as características comumente utilizadas na análise da testabilidade estão as métricas CK, que foram propostas por Chidamber e Kemerer com objetivo de analisar software orientado a objetos. A maioria dos trabalhos nesta linha, entretanto, relaciona o tamanho e a quantidade de casos testes com a testabilidade de um software. Entretanto, é fundamental analisar a qualidade dos testes para saber se eles atingem os objetivos para os quais foram propostos, independente de quantidade e tamanho. Portanto, este trabalho de mestrado apresenta um estudo empírico sobre a relação entre as métricas CK e a testabilidade de um software com base na análise da adequação de seus casos de teste unitários, critérios de teste estrutural e de mutação. Inicialmente foi realizada uma Revisão Sistemática cujo objetivo foi avaliar o estado da arte da testabilidade e as métricas CK. Os resultados mostraram que apesar de existirem várias pesquisas relacionadas ao tema, existem lacunas que motivam novas pesquisas no que concerne a análise da qualidade dos testes e identificação das características das métricas que podem ser inferidas para medir e analisar a testabilidade. Em seguida, foram realizadas duas análises empíricas. Na primeira análise, as métricas foram analisadas por meio da correlação das métricas CK com a cobertura de linha de código, cobertura de \\textit (arestas, ramos ou desvio de fluxo) e escore de mutação. Os resultados desta análise demonstraram a importância de cada métrica dentro do contexto da testabilidade. Na segunda análise, foi realizada uma proposta de clusterização das métricas para tentar identificar grupos de classes com características semelhantes relacionadas à testabilidade. Além das análises empíricas, foi desenvolvida e apresentada uma ferramenta de coleta e análise de métricas CK com objetivo de contribuir com novas pesquisas relacionados a proposta deste projeto. Apesar das limitações das análises, os resultados deste trabalho mostraram a importância de cada métrica CK dentro do contexto da testabilidade e fornece aos desenvolvedores e projetistas uma ferramenta de apoio e dados empíricos para melhor desenvolverem e projetarem seus sistemas com o objetivo de facilitar a atividade de teste de software / Software testing have aim to run a program under test with the aim of revealing its failures, so it is one of the most important phases of the software development lifecycle. Testability is a key quality attribute for the success of the test activity, because it can be understood as the effort required to create, execute and evaluate test cases in software. This attribute is not an intrinsic quality of the software, so it can not be measured directly as the number of lines code, for example. However, it can be inferred through the or internal and external metrics of a software. Among the features commonly used in testability analysis are CK metrics, which were proposed by Chidamber and Kemerer in order to analyze object-oriented software. Most of the works in this line, however, relate the size and quantity of test cases with software testability. However, it\'s critical to analyze the quality of the tests to see if they achieve the objectives for which they were proposed, independent of quantity and size. Therefore, this Master\'s degree work presents an empirical study on the relationship between CK metrics and software testability based on the analysis of the adequacy of its unit test cases, structural test criteria and mutation. Initially, a Systematic Review was carried out to evaluate the state of the art of testability and CK metrics. The results showed that although there are several researches related to the subject, there are gaps that motivate new research in what concerns the analysis of the quality of the tests and identification of the features of the metrics that can be inferred to measure and analyze the testability. Two empirical analyzes were performed. In the first analysis, the metrics were analyzed through the correlation of the CK metrics with the code line coverage, branch coverage or mutation score. The results of this analysis showed the importance of each metric within the context of testability. In the second analysis, a metric clustering proposal was made to try to identify groups of classes with similar features related to testability. In addition to the empirical analysis, a tool for the collection and analysis of CK metrics was developed and presented, with aim to contribute with new researches related to the proposal of this project. Despite the limitations of the analyzes, the results of this work showed the importance of each CK metric within the context of testability and provides developers and designers with a support tool and empirical data to better develop and design their systems with the aim of facilitate the activity of software testing

Teste de Software tem o objetivo de executar um programa sob teste com o objetivo de revelar suas falhas, portanto é uma das fases mais importante do ciclo de vida do desenvolvimento de um software. A testabilidade é um atributo de qualidade fundamental para o sucesso da atividade de teste, pois ela pode ser entendida como o esforço necessário para criar, executar e avaliar os casos de teste em um software. Este atributo não é uma qualidade intrínseca do software, portanto não pode ser medido diretamente como a quantidade de linhas de código, por exemplo. Entretanto, ela pode ser inferida por meio das características ou métricas internas e externas de um software. Entre as características comumente utilizadas na análise da testabilidade estão as métricas CK, que foram propostas por Chidamber e Kemerer com objetivo de analisar software orientado a objetos. A maioria dos trabalhos nesta linha, entretanto, relaciona o tamanho e a quantidade de casos testes com a testabilidade de um software. Entretanto, é fundamental analisar a qualidade dos testes para saber se eles atingem os objetivos para os quais foram propostos, independente de quantidade e tamanho. Portanto, este trabalho de mestrado apresenta um estudo empírico sobre a relação entre as métricas CK e a testabilidade de um software com base na análise da adequação de seus casos de teste unitários, critérios de teste estrutural e de mutação. Inicialmente foi realizada uma Revisão Sistemática cujo objetivo foi avaliar o estado da arte da testabilidade e as métricas CK. Os resultados mostraram que apesar de existirem várias pesquisas relacionadas ao tema, existem lacunas que motivam novas pesquisas no que concerne a análise da qualidade dos testes e identificação das características das métricas que podem ser inferidas para medir e analisar a testabilidade. Em seguida, foram realizadas duas análises empíricas. Na primeira análise, as métricas foram analisadas por meio da correlação das métricas CK com a cobertura de linha de código, cobertura de \\textit (arestas, ramos ou desvio de fluxo) e escore de mutação. Os resultados desta análise demonstraram a importância de cada métrica dentro do contexto da testabilidade. Na segunda análise, foi realizada uma proposta de clusterização das métricas para tentar identificar grupos de classes com características semelhantes relacionadas à testabilidade. Além das análises empíricas, foi desenvolvida e apresentada uma ferramenta de coleta e análise de métricas CK com objetivo de contribuir com novas pesquisas relacionados a proposta deste projeto. Apesar das limitações das análises, os resultados deste trabalho mostraram a importância de cada métrica CK dentro do contexto da testabilidade e fornece aos desenvolvedores e projetistas uma ferramenta de apoio e dados empíricos para melhor desenvolverem e projetarem seus sistemas com o objetivo de facilitar a atividade de teste de software / Software testing have aim to run a program under test with the aim of revealing its failures, so it is one of the most important phases of the software development lifecycle. Testability is a key quality attribute for the success of the test activity, because it can be understood as the effort required to create, execute and evaluate test cases in software. This attribute is not an intrinsic quality of the software, so it can not be measured directly as the number of lines code, for example. However, it can be inferred through the or internal and external metrics of a software. Among the features commonly used in testability analysis are CK metrics, which were proposed by Chidamber and Kemerer in order to analyze object-oriented software. Most of the works in this line, however, relate the size and quantity of test cases with software testability. However, it\'s critical to analyze the quality of the tests to see if they achieve the objectives for which they were proposed, independent of quantity and size. Therefore, this Master\'s degree work presents an empirical study on the relationship between CK metrics and software testability based on the analysis of the adequacy of its unit test cases, structural test criteria and mutation. Initially, a Systematic Review was carried out to evaluate the state of the art of testability and CK metrics. The results showed that although there are several researches related to the subject, there are gaps that motivate new research in what concerns the analysis of the quality of the tests and identification of the features of the metrics that can be inferred to measure and analyze the testability. Two empirical analyzes were performed. In the first analysis, the metrics were analyzed through the correlation of the CK metrics with the code line coverage, branch coverage or mutation score. The results of this analysis showed the importance of each metric within the context of testability. In the second analysis, a metric clustering proposal was made to try to identify groups of classes with similar features related to testability. In addition to the empirical analysis, a tool for the collection and analysis of CK metrics was developed and presented, with aim to contribute with new researches related to the proposal of this project. Despite the limitations of the analyzes, the results of this work showed the importance of each CK metric within the context of testability and provides developers and designers with a support tool and empirical data to better develop and design their systems with the aim of facilitate the activity of software testing

Software testing is considered as one of the key phases in the software-development life cycle (SDLC). The main objective of software testing is to detect the faults either through manual testing or with automated testing approach. The most commonly adopted software testing approach in industries is test case based testing (TCBT) which is usually done manually. TCBT is mainly used by the software testers to formalize and guide their testing activities and set theoretical principals for testing. On the other hand, model based testing (MBT) is widely used automation software testing technique to generate and execute the tests. Both techniques are showing their prominence in real time with some pros and cons. However, there is no formal comparison available between these two techniques. The main objective of this thesis work is to find out the difference in test cases in TCBT and MBT in terms of providing better test coverage ( Statement, Branch and Path), requirement traceability, cost and time. To fulfill the aims of the research we have conducted interviews for static validation, and later we did an experiment for validating those results dynamically. The analysis of experiment results showed that the requirement traceability in MBT generated test cases are very hard to make the test cases traceable to the requirements, particularly with the open-source tool Model J-Unit. However, this can be done by using other commercial tools like Microsoft Spec Explorer or Conformiq Qtronic. Furthermore, we found by conducting experiment, that MBT consumes less time thus it is cost-effective as compared to TCBT and also MBT show better test coverage than TCBT. Moreover, we found that, in our case, requirement traceability is better in traditional TCBT approach as compared to MBT. / +4746851975