scispace - formally typeset
M

Matteo Sonza Reorda

Researcher at Polytechnic University of Turin

Publications -  340
Citations -  5043

Matteo Sonza Reorda is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Fault coverage & Automatic test pattern generation. The author has an hindex of 32, co-authored 295 publications receiving 4525 citations. Previous affiliations of Matteo Sonza Reorda include University of California, Riverside & NXP Semiconductors.

Papers
More filters
Proceedings ArticleDOI

Reliability analysis reloaded: how will we survive?

TL;DR: This paper revisits the state-of-the-art in reliability evaluation starting from the physical device level, to the software system level, all the way up to the product level.
Book ChapterDOI

Software-level soft-error mitigation techniques

TL;DR: This chapter provides an overview of the methods resorting to Soft Errors, outlining their characteristics and summarizing their advantages and limitations.
Proceedings ArticleDOI

Effectiveness and limitations of various software techniques for "soft error" detection: a comparative study

TL;DR: Fault injection experiments put in evidence the detection capabilities and the limitations of each of the studied techniques for bit flip errors arising in microprocessor-based digital architectures as the consequence of the interaction with radiation.
Journal ArticleDOI

Identification and Rejuvenation of NBTI-Critical Logic Paths in Nanoscale Circuits

TL;DR: A new, fast, yet accurate model for computation of NBTI-induced delays at gate-level is developed, based on intensive SPICE simulations of individual gates and the generated rejuvenation stimuli are used to drive those pMOS transistors to the recovery phase, which are the most critical for the NBTi-induced path delay.
Proceedings ArticleDOI

A genetic algorithm for automatic generation of test logic for digital circuits

TL;DR: This approach is the first attempt of exploiting evolutionary techniques for identifying the hardware for input pattern generation in BIST structures and shows that in most of the standard benchmark circuits the cellular automaton selected by the genetic algorithm is able to reach a fault coverage close to the maximum one.