This paper reports on Zoom Obscura – an artist-based design research project, responding to the ubiquity of video-conferencing as a technical and cultural phenomenon throughout the Covid-19 pandemic. As enterprise software, such as Zoom, rapidly came to mediate even the most personal and intimate interactions, we supported and collaborated with seven independent artists to explore technical and creative interventions in video-conferencing. Our call for participation sought critical interventions that would help users counter, and regain agency in regard to the various ways in which personal data is captured, transmitted and processed in video-conferencing tools. In this design study, we analyse post-hoc how each of the seven projects employed aspects of counterfunctional design to achieve these aims. Each project reveals different avenues and strategies for counterfunctionality in video-conferencing software, as well as opportunities to design critically towards interactions and experiences that challenge existing norms and expectations around these platforms.

High-level C++ source code abstractions such as classes and methods greatly assist human analysts and automated algorithms alike when analyzing C++ programs. Unfortunately, these abstractions are lost when compiling C++ source code, which impedes the understanding of C++ executables. In this paper, we propose a system, OOAnalyzer, that uses an innovative new design to statically recover detailed C++ abstractions from executables in a scalable manner. OOAnalyzer's design is motivated by the observation that many human analysts reason about C++ programs by recognizing simple patterns in binary code and then combining these findings using logical inference, domain knowledge, and intuition. We codify this approach by combining a lightweight symbolic analysis with a flexible Prolog-based reasoning system. Unlike most existing work, OOAnalyzer is able to recover both polymorphic and non-polymorphic C++ classes. We show in our evaluation that OOAnalyzer assigns over 78% of methods to the correct class on our test corpus, which includes both malware and real-world software such as Firefox and MySQL. These recovered abstractions can help analysts understand the behavior of C++ malware and cleanware, and can also improve the precision of program analyses on C++ executables.