Several fields of science are experiencing a ""replication crisis"" that has negatively impacted their credibility. Assessing the validity of a contribution via replicability of its experimental evidence and reproducibility of its analyses requires access to relevant study materials, data, and code. Failing to share them limits the ability to scrutinize or build-upon the research, ultimately hindering scientific progress.Understanding how the diverse research artifacts in HCI impact sharing can help produce informed recommendations for individual researchers and policy-makers in HCI. Therefore, we surveyed authors of CHI 2018-2019 papers, asking if they share their papers' research materials and data, how they share them, and why they do not. The results (34% response rate) show that sharing is uncommon, partly due to misunderstandings about the purpose of sharing and reliable hosting. We conclude with recommendations for fostering open research practices.This paper and all data and materials are freely available at https://osf.io/3bu6t.

Smartphones in general and Android in particular are increasingly shifting into the focus of cyber criminals. For understanding the threat to security and privacy, it is important for security researchers to analyze malicious software written for these systems. The exploding number of Android malware calls for automation in the analysis. In this paper, we present Mobile-Sandbox, a system designed to automatically analyze Android applications in novel ways: First, it combines static and dynamic analysis, i.e., results of static analysis are used to guide dynamic analysis and extend coverage of executed code. Additionally, it uses specific techniques to log calls to native (i.e., "non-Java") APIs, and last but not least it combines these results with machinelearning techniques to cluster the analyzed samples into benign and malicious ones. We evaluated the system on more than 69,000 applications from Asian third-party mobile markets and found that about 21 % of them actually use native calls in their code.

In recent years, a large amount of software for multitouch interfaces with various degrees of similarity has been written. In order to improve interoperability, we aim to identify the common traits of these systems and present a layered software architecture which abstracts these similarities by defining common interfaces between successive layers. This provides developers with a unified view of the various types of multitouch hardware. Moreover, the layered architecture allows easy integration of existing software, as several alternative implementations for each layer can co-exist. Finally, we present our implementation of this architecture, consisting of hardware abstraction, calibration, event interpretation and widget layers.

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