Fuzz testing for digital TV receivers and multitasking control software verification

Abstract

This issue contains two very different papers, in terms of subjects and proposed test and verification techniques. The first paper focuses on testing the robustness of digital TV (DTV) receivers through (non)compliance fuzz testing. The second one focuses on a model-based approach to enable the verification of multitasking control software, proposing an OS-in-the-Loop (OiL) verification framework. The first paper, ‘A fuzzing-based test-creation approach for evaluating digital TV receivers via transport streams’ by Fabricio Izumi, Eddie B. de Lima Filho, Lucas C. Cordeiro, Orlewilson Maia, Rômulo Fabrício, Bruno Farias and Aguinaldo Silva, concerns the generation of noncompliance tests using grammar-based guided fuzzing. The originality of this contribution resides in the nature of the test subjects, which are DTV receivers, their (mis)configurations and transport streams. The originality extends to conformance testing by targeting robustness improvements: Instead of checking whether it behaves as expected, the goal is to verify the DTV receiver response against inaccurate or inconsistent data, based on fuzzing input generation. Finally, the approach is supported by a complete evaluation framework, which includes a testing environment, audio and video verification algorithms and a strategy for test creation (recommended by Paul Strooper, Rob Hierons and Yves Le Traon). The second paper, ‘OS-in-the-Loop verification for multi-tasking control software’ by Yunja Choi, presents an original approach to perform verification for embedded control software, specifically an OiL verification framework. This framework is based on a modelling of embedded operating systems, enabling the composition of the interactions of the OS model and the device controllers, thanks to an algorithm described in the paper. Multitasking is thus treated thanks to this composition mechanism. The framework makes it possible to apply various verification methods for multitasking (random simulation, dynamic concolic testing and model checking). The application of the OiL verification to a small-case study illustrates the benefit of the framework, which has been successfully applied on two typical pieces of multitasking embedded software from industry (recommended by Benoit Baudry, Rob Hierons and Yves Le Traon). We hope you will find these papers interesting and inspiring for your future work.