Estimating Probabilistic Safe WCET Ranges of Real-Time Systems at Design Stages

Jaekwon Lee, Seung Yeob Shin, Shiva Nejati, Lionel Briand, Yago Isasi Parache

Research output: Contribution to journalArticlepeer-review

Abstract

Estimating worst-case execution time (WCET) is an important activity at early design stages of real-time systems. Based on WCET estimates, engineers make design and implementation decisions to ensure that task executions always complete before their specified deadlines. However, in practice, engineers often cannot provide precise point WCET estimates and prefer to provide plausible WCET ranges. Given a set of real-time tasks with such ranges, we provide an automated technique to determine for what WCET values the system is likely to meet its deadlines and, hence, operate safely with a probabilistic guarantee. Our approach combines a search algorithm for generating worst-case scheduling scenarios with polynomial logistic regression for inferring probabilistic safe WCET ranges. We evaluated our approach by applying it to three industrial systems from different domains and several synthetic systems. Our approach efficiently and accurately estimates probabilistic safe WCET ranges within which deadlines are likely to be satisfied with a high degree of confidence.

Original languageEnglish
Article number37
JournalACM Transactions on Software Engineering and Methodology
Volume32
Issue number2
DOIs
Publication statusPublished - 29 Mar 2023
Externally publishedYes

Keywords

  • Schedulability analysis
  • machine learning
  • meta-heuristic search
  • search-based software engineering
  • worst-case execution time

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