Automated software-based in-field self-test program synthesis

Jasnetski, A.; Ubar, R.; Tsertov, A

Artykuł - szczegóły

Tytuł artykułu

Automated software-based in-field self-test program synthesis

Autorzy

Jasnetski A. , Ubar R. , Tsertov A

Treść / Zawartość

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Jasnetski_Ubar_Tsertov_Automated_2_2017.pdf

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Języki publikacji

Abstrakty

This paper presents a methodology to automate functional Software-Based Self-Test program development. We rely on the previously published research on modeling processors using subclass of acyclic directed graphs called High-Level Decision Diagrams (HLDD). The HLDD model of the processor gets generated from its Instruction Set Architecture. The HLDD model is then used together with beforehand prepared assembly program templates in the generation of the complete self-test program. The research presented in this paper includes examples of test generation for the 32-bit SPARCv8 microprocessor Leon 3. The experimental results demonstrate that automatically generated SBST program obtains comparable to the state-of the art fault coverage data.

Słowa kluczowe

microprocessor software based self-test SBST automatic test program generation high-level decision diagrams HLDD synthesis

mikroprocesor SBST programy ATPG HLDD synteza HLDD

Wydawca

Lodz University of Technology. Department of Microelectronics and Computer Science

Czasopismo

International Journal of Microelectronics and Computer Science

Rocznik

2017

Tom

Vol. 8, nr 2

Strony

57--64

Opis fizyczny

Bibliogr. 43 poz., il. kolor., rys.

Twórcy

autor

Jasnetski A.

ajasn@ati.ttu.ee

Department of Computer Engineering, Tallinn University of Technology, Tallinn, Estonia

autor

Ubar R.

raiub@ati.ttu.ee

Department of Computer Engineering, Tallinn University of Technology, Tallinn, Estonia

autor

Tsertov A

anton.tsertov@ttu.ee

Department of Computer Engineering, Tallinn University of Technology, Tallinn, Estonia

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).

Typ dokumentu

Bibliografia

Identyfikator YADDA

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