Internet of Things and static source code analysis

Your organization is a leader of Internet of Things (or Machine to Machine systems) and Embedded Computing. So you (or your partners) are probably interested in the IoT-03 H2020 call:

I (Basile Starynkevitch) am a research engineer in the software safety lab (Laboratoire de Sûreté des Logiciels) of CEA, LIST (the Information Technology focused institute, 800 persons, of CEA, a public applied research organization of 16000 persons in France).

The LSL lab (software safety laboratory) of CEA, LIST has expertise in static source code analysis, both in a formal methods approach through its flagship product Frama-C and in more heuristic approaches by leveraging on existing compilers like with GCC MELT, which is a domain specific language to work on GCC internal representations, or Clang/LLVM.

We are looking to join an existing consortium working on a proposal related to the topic IoT-03-2017. We suggest to develop a specialized tool (preferably open source, above existing technologies), for developers & engineers writing source code (in C, C++, and Ada if needed...) targeting IoT platforms. This tool will be integrated in the targeted software development kit. This tool could assist IoT software developer by analysing and checking the validity of the source code against coding rules, invariants, and good practices specific to these software frameworks. The main objective is to enhance the software quality and to accelerate the time to market. If relevant, the tool could perform specific source code optimizations to enhance the software performance and/or to decrease the code size.

We are also more broadly interested in bringing static source code analysis techniques to software developers in the Internet Of Things (IoT) and Machine to Machine (M2M) domains.

Feel free to contact me ( and to forward this message (downloadable on to your colleagues and partners.

I look forward to discussing with you.

Basile Starynkevitch,
mobile: +33 6 8501 2359; office: +33 1 6908 6595
CEA LIST Nano-Innov b862 PC 174 - 91191 GIF/YVETTE CEDEX, France