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Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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MicroTESK: Specification-Based Tool for Constructing Test Program Generators

P. 217–220.
Tatarnikov A., Kamkin A., Чупилко М. М., Коцыняк А. М.

The paper presents MicroTESK, a tool that automates construction of test program generators for microprocessors. A constructed generator consists of the core that implements architecture-independent generation methods and the model that holds information required to generate tests for the corresponding architecture. The tool extracts this information from formal specifications of the instruction set architecture. The extracted information is used in multiple ways: (1) to get the assembly format of the instructions; (2) to build the coverage model of the instruction set architecture; (3) to construct the instruction set simulator used as a reference model. Test programs are created on the basis of test templates provided by users. Flexible architecture of the tool facilitates integration of new test generation engines. MicroTESK has been applied to the ARMv8, MIPS64, PowerPC, RISC-V, and x86 architectures.

Language: English
DOI
Text on another site
Keywords: formal specificationsформальные спецификациисистема командмикропроцессорыinstruction setфункциональная верификациягенерация тестовых программfunctional verificationtest program generationmicroprocessors

In book

Hardware and Software: Verification and Testing. HVC 2017. Lecture Notes in Computer Science
Vol. 10629: 13th International Haifa Verification Conference, HVC 2017, Haifa, Israel, November 13-15, 2017. , Cham: Springer, 2017.
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