This report gives a brief overview of the main concerns addressed by the authors at the second international track on Formal Verification of Service Based Systems, held at WETICE 2014 conference. A presentation of the main topics is given and then a summary of the paper accepted by this conference track is reported.

This paper proposes an algorithm for the robust reception of compressed HTML files transmitted over a noisy mobile radio channel. Both source encoders and transmission systems are assumed to be standard compliant. The source encoder follows the HTTP1.1 protocol specifications, i.e. the HTML files are encoded by the deflate algorithm, a combination of Lempel-Ziv and Huffman algorithms. The transmission scheme follows IEEE 802.11a (and 802.11n) standard as an example. The proposed receiver is based on an iterative joint source-channel decoding approach. The Soft-Input Soft-Output outer source decoder is based on a sequential M-algorithm, which has been modified to improve the decoding performance by exploiting the specific grammatical and syntax rules of (i) Huffman codes; (ii) Lempel-Ziv codes; and (iii) HTML language. Simulation results following the IEEE 802.11a (and 802.11n) standard over additive white Gaussian noise and Rayleigh fading channels show that the proposed receiver drastically reduces the number of errors occurring in the received HTML files compared to the classical receivers. An EXIT chart analysis illustrates some properties of this combination of source and channel decoders.

This paper concerns the error correction of corrupted compressed HTML pages during their transmission via a noisy mobile channel. The proposed receiver is based on an iterative joint source channel decoding approach similar to the turbo decoding of two serial concatenated codes. We propose a soft-input soft-output Lempel-Ziv inner decoder based on the modified version of the traditional sequential decoding M-algorithm. This new algorithm exploits the specific grammatical rules of the Lempel-Ziv-77 codes which are combined to the syntax of the HTML language. This source decoder is combined to a Soft-Input Soft-Output channel decoder of convolutional codes. Simulation results, over an additive white Gaussian noise channel, show that the proposed method drastically reduces the number of files in error compared to any conventional channel decoding.