18 research outputs found

    Automated Black-Box Boundary Value Detection

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    The input domain of software systems can typically be divided into sub-domains for which the outputs are similar. To ensure high quality it is critical to test the software on the boundaries between these sub-domains. Consequently, boundary value analysis and testing has been part of the toolbox of software testers for long and is typically taught early to students. However, despite its many argued benefits, boundary value analysis for a given specification or piece of software is typically described in abstract terms which allow for variation in how testers apply it. Here we propose an automated, black-box boundary value detection method to support software testers in systematic boundary value analysis with consistent results. The method builds on a metric to quantify the level of boundariness of test inputs: the program derivative. By coupling it with search algorithms we find and rank pairs of inputs as good boundary candidates, i.e. inputs close together but with outputs far apart. We implement our AutoBVA approach and evaluate it on a curated dataset of example programs. Our results indicate that even with a simple and generic program derivative variant in combination with broad sampling over the input space, interesting boundary candidates can be identified

    Scalable diversified antirandom test pattern generation with improved fault coverage for black-box circuit testing

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    Pseudorandom testing is incapable of utilizing the success rate of preceding test patterns while generating subsequent test patterns. Many redundant test patterns have been generated that increase the test length without any significant increase in the fault coverage. An extension to pseudorandom testing is Antirandom that induces divergent patterns by maximizing the Total Hamming Distance (THD) and Total Cartesian Distance (TCD) of every subsequent test pattern. However, the Antirandom test sequence generation algorithm is prone to unsystematic selection when more than one patterns possess maximum THD and TCD. As a result, diversity among test sequences is compromised, lowering the fault coverage. Therefore, this thesis analyses the effect of Hamming distance in vertical as well as horizontal dimension to enhance diversity among test patterns. First contribution of this thesis is the proposal of a Diverse Antirandom (DAR) test pattern generation algorithm. DAR employs Horizontal Total Hamming Distance (HTHD) along with THD and TCD for diversity enhancement among test patterns as maximum distance test pattern generation. The HTHD and TCD are used as distance metrics that increase computational complexity in divergent test sequence generation. Therefore, the second contribution of this thesis is the proposal of tree traversal search method to maximize diversity among test patterns. The proposed method uses bits mutation of a temporary test pattern following a path leading towards maximization of TCD. Results of fault simulations on benchmark circuits have shown that DAR significantly improves the fault coverage up to 18.3% as compared to Antirandom. Moreover, the computational complexity of Antirandom is reduced from exponential O(2n) to linear O(n). Next, the DARalgorithm is modified to ease hardware implementation for on-chip test generation. Therefore, the third contribution of this thesis is the design of a hardware-oriented DAR (HODA) test pattern generator architecture as an alternative to linear feedback shift register (LFSR) that consists of large number of memory elements. Parallel concatenation of the HODA architecture is designed to reduce the number of memory elements by implementing bit slicing architecture. It has been proven through simulation that the proposed architecture has increased fault coverage up to 66% and a reduction of 46.59% gate count compared to the LFSR. Consequently, this thesis presents uniform and scalable test pattern generator architecture for built-in self-test (BIST) applications and solution to maximum distance test pattern generation for high fault coverage in black-box environment

    ТЕСТОВОЕ ДИАГНОСТИРОВАНИЕ АППАРАТНОГО И ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ ВЫЧИСЛИТЕЛЬНЫХ СИСТЕМ

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    The main scientific and practical results on test diagnostics of hardware and software of computer systems are presented in brief history. More than 500 international and local publications including 17 books and 72 invention certificates reinforce the scientific results. The current state of research and a plan of future research of laboratory are presented.Кратко изложены основные научные и практические результаты исследований в области тестового диагностирования вычислительных систем, полученные в БГУИР в рамках представляемой научной школы. Приведены основные характеристики оригинальных решений в области стендового оборудования для тестирования цифровых модулей, контролепригодного синтеза вычислительных систем, методов компактного тестирования, теории сигнатурного анализа и методов самотестирования вычислительных машин и систем. Описаны новые оригинальные авторские методы псевдослучайного и вероятностного тестирования, исчерпывающего, псевдоисчерпывающего и почти исчерпывающего тестирования, управляемого случайного тестирования и оптимального управляемого случайного тестирования, а также квазислучайного тестирования программного обеспечения. Представлены результаты посвященные тестированию, самотестированию и саморемонтированию запоминающих устройств, а также неразрушающему тестированию оперативных запоминающих устройств (ОЗУ) с применением адаптивного сигнатурного анализа и симметричных маршевых тестов ОЗУ. Кроме того, приведены основные результаты по методам обеспечения целостности данных с использованием цифровых водяных знаков и запутывающих преобразований и их применению по обеспечению авторского права на программное обеспечение. Представлены результаты, полученные в области физической криптографии

    Методы генерирования квазислучайных тестовых последовательностей

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    This thesis deals with quasi-random test sequences and methods of their generation. The advantages of quasi-random sequences over pseudo-random sequences are also shown

    УПРАВЛЯЕМОЕ СЛУЧАЙНОЕ ТЕСТИРОВАНИЕ

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    Анализируются управляемые случайные тесты и методы их генерирования. Показываетсяобщность процедур генерирования тестовых векторов управляемых случайных тестов, использующих жадный оптимизационный алгоритм и метрики расстояния между тестовыми наборами. Предлагается метод построения оптимальных управляемых случайных тестов, характеризующихся максимальной полнотой покрытия в сравнении со случайными и управляемыми случайными тестами в силу максимального отличия тестовых наборов. Оптимальные управляемые случайные тесты характеризуются минимальной вычислительной сложностью их генерирования

    Searching for test data with feature diversity

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    There is an implicit assumption in software testing that more diverse and varied test data is needed for effective testing and to achieve different types and levels of coverage. Generic approaches based on information theory to measure and thus, implicitly, to create diverse data have also been proposed. However, if the tester is able to identify features of the test data that are important for the particular domain or context in which the testing is being performed, the use of generic diversity measures such as this may not be sufficient nor efficient for creating test inputs that show diversity in terms of these features. Here we investigate different approaches to find data that are diverse according to a specific set of features, such as length, depth of recursion etc. Even though these features will be less general than measures based on information theory, their use may provide a tester with more direct control over the type of diversity that is present in the test data. Our experiments are carried out in the context of a general test data generation framework that can generate both numerical and highly structured data. We compare random sampling for feature-diversity to different approaches based on search and find a hill climbing search to be efficient. The experiments highlight many trade-offs that needs to be taken into account when searching for diversity. We argue that recurrent test data generation motivates building statistical models that can then help to more quickly achieve feature diversity.Comment: This version was submitted on April 14th 201

    Test vectors reductoin for integrated circuit testing using horizontal hamming distance

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    In testing digital combinational logic for stuck-at faults, it is required to determine the most appropriate test sequence needed to detect the required number of possible faults. The exhaustive test pattern generation method is the simplest approach to implement as it produces test patterns consisting of all possible input combinations of the circuit under test. However, a consequence of this approach is that it results in a large test set when the number of circuit inputs is large. This can take an unnecessarily long time to apply on the circuit under test as during the test process, only a small fraction of all possible test vectors is actually required to produce high percentage of fault coverage. As an alternative, random test pattern generation applies a random set of test patterns which can be used to reduce the number of test patterns compared to exhaustive test. However, both test pattern generation approaches generate unnecessary test vectors to apply to the circuit as multiple patterns typically detect the same fault. Antirandom testing on the other hand ensures that the identified test vectors to use do not detect the same fault by introducing the concept of Hamming distance between test vectors and this distance is be maximized. This results in a reduction in the number of required test vectors when compared to an exhaustive test. However, the algorithm for Antirandom test vector generation is computation intensive and vague in its definition when there are more than one possible next test vectors. In this study, efficient calculation of Hamming distance has been proposed, moreover the choice of the next test vector is addressed by using the proposed Horizontal Hamming distance method which has not yet been explored. The approach effectively detects faults at a much faster rate and produces a much higher fault coverage than the existing Antirandom method

    КВАЗИСЛУЧАЙНОЕ ТЕСТИРОВАНИЕ ВЫЧИСЛИТЕЛЬНЫХ СИСТЕМ

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    Various modified random testing approaches have been proposed for computer system testing in the black box environment. Their effectiveness has been evaluated on the typical failure patterns by employing three measures, namely, P-measure, E-measure and F-measure. A quasi-random testing, being a modified version of the random testing, has been proposed and analyzed. The quasi-random Sobol sequences and modified Sobol sequences are used as the test patterns. Some new methods for Sobol sequence generation have been proposed and analyzed.Анализируются причинно-следственные связи при возникновении неисправностей вычисли-тельных систем. Даются определения понятий «неисправность», «ошибка» и «неисправное поведение вычислительных систем», показывается их общность для программной и аппаратной частей вычислительных систем. Рассматривается классификация обобщенных входных тестовых воздей-ствий на три категории: точечные тестовые наборы, узкополосные тестовые наборы и блочные тестовые наборы. Приводится анализ методов тестирования вычислительных систем по методике черного ящика, показывается эффективность использования квазислучайного тестирования. Анали-зируются и предлагаются методы формирования квазислучайных тестовых воздействий

    МНОГОКРАТНЫЕ УПРАВЛЯЕМЫЕ ВЕРОЯТНОСТНЫЕ ТЕСТЫ

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    Controlled Random Tests and methods for their generation have been analyzed and investigated. The similarities of all known controlled random testing approaches are shown. A new method and algorithm for Multiple Controlled Random Tests have been proposed and analyzed.Рассматриваются однократные управляемые вероятностные тесты, методы их формирования, а также их применение для тестирования средств вычислительных систем. Показываются основные недостатки построения однократных вероятностных тестов. Предлагается метод построения многократных управляемых вероятностных тестов на базе исходного однократного теста. Анализируются различные численные метрики для построения как однократных, так и многократных управляемых вероятностных тестов
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