Testing tools (e.g., data generators, coverage testing) (REVISED)
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Domänenspezifische Sprachen gewinnen seit einigen Jahren zunehmend an Bedeutung. Xtext ist eine sogenannte \textit{Language Workbench}, mit der solche Sprachen schnell entwickelt werden können. Neben der Sprachinfrastruktur wird eine inzwischen weit fortgeschrittene Integration in die IDE Eclipse erzeugt und es können optional ein Plug-in für IntelliJ und ein Webeditor erstellt werden. Der Ansatz ist dabei, dass der oder die Codegeneratoren direkt mit dem Abstract Syntax Tree arbeiten. In dieser Arbeit wird gezeigt, wie ein Domänenmodell in eine Xtext-Sprache integriert werden kann und wie Test- und Wartbarkeit davon profitieren. Besondere Beachtung finden, gegeben durch das Projektumfeld, die Anforderungen durch Funktionale Sicherheit.
Online services such as social networks, online shops, and search engines deliver different content to users depending on their location, browsing history, or client device. Since these services have a major influence on opinion forming, understanding their behavior from a social science perspective is of greatest importance. In addition, technical aspects of services such as security or privacy are becoming more and more relevant for users, providers, and researchers. Due to the lack of essential data sets, automatic black box testing of online services is currently the only way for researchers to investigate these services in a methodical and reproducible manner. However, automatic black box testing of online services is difficult since many of them try to detect and block automated requests to prevent bots from accessing them.
In this paper, we introduce a testing tool that allows researchers to create and automatically run experiments for exploratory studies of online services. The testing tool performs programmed user interactions in such a manner that it can hardly be distinguished from a human user. To evaluate our tool, we conducted - among other things - a large-scale research study on Risk-based Authentication (RBA), which required human-like behavior from the client. We were able to circumvent the bot detection of the investigated online services with the experiments. As this demonstrates the potential of the presented testing tool, it remains to the responsibility of its users to balance the conflicting interests between researchers and service providers as well as to check whether their research programs remain undetected.