Document Type

Conference Paper

Subject Area

CPS Medical, CPS Formal Methods

Date of this Version

3-2018

Publication Source

American Control Conference

Abstract

Robustness-Guided Falsification (RGF) is an efficient

testing technique that tries to find a system execution that

violates some formal specification, by minimizing the robustness

of the specification over the set of initial conditions of the

system. Robustness uses an underlying distance function on

the space of system executions. As RGF is applied to new fields

like medicine, it is essential to determine whether our distances

still capture the domain expert’s intuition of which executions

are similar and which are not. Motivated by the problem of

testing the algorithms of cardiac defibrillators implanted in

millions of patients worldwide, this work develops a (pseudo-

)distance function, called conformance, over the space of cardiac

signals. By using it to distinguish between fatal and non-fatal

arrhythmias obtained from real patients, it is demonstrated

that conformance measures the meaningful distance between

cardiac signals much better than distances used in medical

devices today. Next, conformance is used to re-define the

robustness degrees of Metric Temporal Logic (MTL), and it

is shown that conformance-based robust semantics of MTL

can bound the (conformance-based) robustness degree, thus

enabling a principled application of RGF to problems in the

cardiac domain, using the appropriate distance notion. Using

existing robust semantics based on sup norm can yield incorrect

conclusions, with potentially severe consequences to patients.

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Date Posted: 15 July 2018

This document has been peer reviewed.