EDiFy: An Execution time Distribution Finder

Boudewijn Braams, Sebastian Altmeyer, Andy D. Pimentel

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


Embedded real-Time systems are subjected to stringent timing constraints. Analysing their timing behaviour is therefore of great significance. So far, research on the timing behaviour of real-Time systems has been primarily focused on finding out what happens in the worst-case (i.e., finding the worst case execution time, or WCET). While a WCET estimate can be used to verify that a system is able to meet deadlines, it does not contain any further information about how the system behaves most of the time. An execution time distribution does contain this information and can provide useful insights regarding the timing behaviour of a system. In this paper, we present EDiFy, a measurement-based framework that derives execution time distributions by exhaustive evaluation of program inputs. We overcome the scalability and state-space explosion problem by i) using static analysis to reduce the input space and ii) using an anytime algorithm which allows deriving a precise approximation on the execution time distribution. We exemplify EDiFy on several benchmarks from the TACLeBench and EEMBC benchmark suites, and show that the anytime algorithm provides precise estimates already after a short time.

Original languageEnglish
Title of host publicationProceedings of the 54th Annual Design Automation Conference 2017, DAC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450349277
Publication statusPublished - 18 Jun 2017
Externally publishedYes
Event54th Annual Design Automation Conference, DAC 2017 - Austin, United States
Duration: 18 Jun 201722 Jun 2017

Publication series

NameProceedings - Design Automation Conference
VolumePart 128280
ISSN (Print)0738-100X


Conference54th Annual Design Automation Conference, DAC 2017
Country/TerritoryUnited States


Dive into the research topics of 'EDiFy: An Execution time Distribution Finder'. Together they form a unique fingerprint.

Cite this