Robust test generation and coverage for hybrid systems

A. Agung Julius, Georgios Fainekos, Madhukar Anand, Insup Lee, George J. Pappas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

78 Citations (Scopus)

Abstract

Testing is an important tool for validation of the system design and its implementation. Model-based test generation allows to systematically ascertain whether the system meets its design requirements, particularly the safety and correctness requirements of the system. In this paper, we develop a framework for generating tests from hybrid systems' models. The core idea of the framework is to develop a notion of robust test, where one nominal test can be guaranteed to yield the same qualitative behavior with any other test that is close to it. Our approach offers three distinct advantages. 1) It allows for computing and formally quantifying the robustness of some properties, 2) it establishes a method to quantify the test coverage for every test case, and 3) the procedure is parallelizable and therefore, very scalable. We demonstrate our framework by generating tests for a navigation benchmark application.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages329-342
Number of pages14
Volume4416 LNCS
StatePublished - 2007
Externally publishedYes
Event10th International Conference on Hybrid Systems: Computation and Control, HSCC 2007 - Pisa, Italy
Duration: Apr 3 2007Apr 5 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4416 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Conference on Hybrid Systems: Computation and Control, HSCC 2007
CountryItaly
CityPisa
Period4/3/074/5/07

Fingerprint

Robust Tests
Test Generation
Hybrid systems
Hybrid Systems
Coverage
Benchmarking
Navigation
Systems analysis
Safety
Testing
Qualitative Behavior
Requirements
Categorical or nominal
System Design
Correctness
Quantify
Model-based
Benchmark
Robustness
Distinct

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Julius, A. A., Fainekos, G., Anand, M., Lee, I., & Pappas, G. J. (2007). Robust test generation and coverage for hybrid systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4416 LNCS, pp. 329-342). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4416 LNCS).

Robust test generation and coverage for hybrid systems. / Julius, A. Agung; Fainekos, Georgios; Anand, Madhukar; Lee, Insup; Pappas, George J.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4416 LNCS 2007. p. 329-342 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4416 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Julius, AA, Fainekos, G, Anand, M, Lee, I & Pappas, GJ 2007, Robust test generation and coverage for hybrid systems. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4416 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4416 LNCS, pp. 329-342, 10th International Conference on Hybrid Systems: Computation and Control, HSCC 2007, Pisa, Italy, 4/3/07.
Julius AA, Fainekos G, Anand M, Lee I, Pappas GJ. Robust test generation and coverage for hybrid systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4416 LNCS. 2007. p. 329-342. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Julius, A. Agung ; Fainekos, Georgios ; Anand, Madhukar ; Lee, Insup ; Pappas, George J. / Robust test generation and coverage for hybrid systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4416 LNCS 2007. pp. 329-342 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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