A Binary Classifier for Test Case Feasibility Applied to Automatically Generated Tests of Event-Driven Software

Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

The Effect of Package Geometry on Moisture Driven Degradation of Polymer Aluminum Capacitors

Polymer aluminum electrolytic capacitors were introduced to provide an alternative to liquid electrolytic capacitors. Polymer electrolytic capacitor electric parameters of capacitance and ESR are less temperature dependent than those of liquid aluminum electrolytic capacitors. Furthermore, the electrical conductivity of the polymer used in these capacitors (poly-3,4ethylenedioxithiophene) is orders of magnitude higher than the electrolytes used in liquid aluminum electrolytic capacitors, resulting in capacitors with much lower equivalent series resistance which are suitable for use in high ripple-current applications. The presence of the moisture-sensitive polymer PEDOT introduces concerns on the reliability of polymer aluminum capacitors in high humidity conditions. Highly accelerated stress testing (or HAST) (110ºC, 85% relative humidity) of polymer aluminum capacitors in which the parts were subjected to unbiased HAST conditions for 700 hours was done to understand the design factors that contribute to the susceptibility to degradation of a polymer aluminum electrolytic capacitor exposed to HAST conditions. A large scale study involving capacitors of different electrical ratings (2.5V – 16V, 100µF – 470 µF), mounting types (surface-mount and through-hole) and manufacturers (6 different manufacturers) was done to determine a relationship between package geometry and reliability in high temperature-humidity conditions. A Geometry-Based HAST test in which the part selection limited variations between capacitor samples to geometric differences only was done to analyze the effect of package geometry on humidity-driven degradation more closely. Raman spectroscopy, x-ray imaging, environmental scanning electron microscopy, and destructive analysis of the capacitors after HAST exposure was done to determine the failure mechanisms of polymer aluminum capacitors under high temperature-humidity conditions.