We present recent developments in the openSMILE feature extraction toolkit. Version 2.0 now unites feature extraction paradigms from speech, music, and general sound events with basic video features for multi-modal processing. Descriptors from audio and video can be processed jointly in a single framework allowing for time synchronization of parameters, on-line incremental processing as well as off-line and batch processing, and the extraction of statistical functionals (feature summaries), such as moments, peaks, regression parameters, etc. Postprocessing of the features includes statistical classifiers such as support vector machine models or file export for popular toolkits such as Weka or HTK. Available low-level descriptors include popular speech, music and video features including Mel-frequency and similar cepstral and spectral coefficients, Chroma, CENS, auditory model based loudness, voice quality, local binary pattern, color, and optical flow histograms. Besides, voice activity detection, pitch tracking and face detection are supported. openSMILE is implemented in C++, using standard open source libraries for on-line audio and video input. It is fast, runs on Unix and Windows platforms, and has a modular, component based architecture which makes extensions via plug-ins easy. openSMILE 2.0 is distributed under a research license and can be downloaded from http://opensmile.sourceforge.net/.

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Modern test case generation techniques can automatically achieve high code coverage. If they operate on the unit level, they run the risk of generating inputs infeasible in reality, which, when causing failures, are painful to identify and eliminate. Running a unit test generator on five open source Java programs, we found that all of the 181 reported failures were false failures-that is, indicating a problem in the generated test case rather than the program. By generating test cases at the GUI level, our EXSYST prototype can avoid such false alarms by construction. In our evaluation, it achieves higher coverage than search-based test generators at the unit level; yet, every failure can be shown to be caused by a real sequence of input events. Whenever a system interface is available, we recommend considering search-based system testing as an alternative to avoid false failures.

Search-based testing has been successfully applied to generate complex sequences of events for graphical user interfaces (GUIs), but typically relies on simple heuristics or random values for data widgets like text boxes. This may greatly reduce the effectiveness of test generation for applications which expect specific input values to be entered in their GUI by users. Generating such specific input values is one of the virtues of dynamic symbolic execution (DSE), but DSE is less suitable to generate sequences of events. Therefore, this paper describes a hybrid approach that uses search-based testing to generate sequences of events, and DSE to build input data for text boxes. This is achieved by replacing standard widgets in a system under test with symbolic ones, allowing us to execute GUIs symbolically. In this paper, we demonstrate an extension of the search-based GUI testing tool EXSYST, which uses DSE to successfully increase the obtained code coverage on two case study applications.

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