The majority of artifacts created during software development are representations of programs in textual syntax. Although graphical descriptions are becoming more widespread, source code is still indispensable. To obtain programs that behave correctly and adhere to given coding conventions, source code must be analyzed — preferably using automated tools. Building source code analyzers has a lon...

Protected module architectures (PMA) are an isolation mechanism that emerging processors provide as security building blocks for modern software systems. Reasoning about these building blocks means reasoning about elaborate assembly code, which can be very complex due to the loose structure of the code. One way to overcome this complexity is providing the code with a well-structured semantics. ...

Proof-Carrying Code (PCC) allows a code producer to provide to a host a program along with its formal safety proof. The proof attests a certain safety policy enforced by the code, and can be mechanically checked by the host. While this language-based approach to code certification is very general in principle, existing PCC systems have only focused on programs whose safety proofs can be automat...

The genetic code is connection between 64 codons, which are building blocks of the genes, and 20 amino acids, which are building blocks of the proteins. In addition to coding amino acids, a few codons code stop signal, which is at the end of genes, i.e. it terminates process of protein synthesis. This article is a review of simple modelling of the genetic code and related subjects by concept of...

The evolution of building codes typically produce design provisions that are expected to create safer and more accurate designs. We as engineers expect building codes to advance the state of the art with each successive edition. The 2009 International Building Code (IBC) and the Building Code Requirements for Structural Concrete (ACI 318-08) have significant revisions affecting the design of ti...

We introduce a linear code based on resilient maps on vector spaces over finite fields, we give a basis of this code and upper and lower bounds for its minimal distance. Then the use of the introduced code for building vector space secret sharing schemes is explained and an estimation of the robustness of the schemes against cheaters is provided.

We introduce a linear code based on resilient maps on vector spaces over finite fields, we give a basis of this code and upper and lower bounds for its minimal distance. Then the use of the introduced code for building vector space secret sharing schemes is explained and an estimation of the robustness of the schemes against cheaters is provided.