Stress testing real-time systems with genetic algorithms

Lionel C. Briand; Yvan Labiche; Marwa Shousha

doi:10.1145/1068009.1068183

Stress testing real-time systems with genetic algorithms

Lionel C. Briand, Yvan Labiche, Marwa Shousha

Carleton University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Reactive real-time systems have to react to external events within time constraints: Triggered tasks must execute within deadlines. The goal of this article is to automate, based on the system task architecture, the derivation of test cases that maximize the chances of critical deadline misses within the system. We refer to that testing activity as stress testing. We have developed a method based on genetic algorithms and implemented it in a tool. Case studies were run and results show that the tool may actually help testers identify test cases that will likely stress the system to such an extent that some tasks may miss deadlines.

Original language	English
Title of host publication	GECCO 2005 - Genetic and Evolutionary Computation Conference
Editors	H.G. Beyer, U.M. O'Reilly, D. Arnold, W. Banzhaf, C. Blum, E.W. Bonabeau, E. Cantu-Paz, D. Dasgupta, K. Deb, al et al
Pages	1021-1028
Number of pages	8
DOIs	https://doi.org/10.1145/1068009.1068183
Publication status	Published - 2005
Externally published	Yes
Event	GECCO 2005 - Genetic and Evolutionary Computation Conference - Washington, D.C., United States Duration: 25 Jun 2005 → 29 Jun 2005

Publication series

Name	GECCO 2005 - Genetic and Evolutionary Computation Conference

Conference

Conference	GECCO 2005 - Genetic and Evolutionary Computation Conference
Country/Territory	United States
City	Washington, D.C.
Period	25/06/05 → 29/06/05

Keywords

Genetic algorithms
Schedulability theory

Access to Document

10.1145/1068009.1068183

Cite this

Briand, L. C., Labiche, Y., & Shousha, M. (2005). Stress testing real-time systems with genetic algorithms. In H. G. Beyer, U. M. O'Reilly, D. Arnold, W. Banzhaf, C. Blum, E. W. Bonabeau, E. Cantu-Paz, D. Dasgupta, K. Deb, & A. et al (Eds.), GECCO 2005 - Genetic and Evolutionary Computation Conference (pp. 1021-1028). (GECCO 2005 - Genetic and Evolutionary Computation Conference). https://doi.org/10.1145/1068009.1068183

Briand, Lionel C. ; Labiche, Yvan ; Shousha, Marwa. / Stress testing real-time systems with genetic algorithms. GECCO 2005 - Genetic and Evolutionary Computation Conference. editor / H.G. Beyer ; U.M. O'Reilly ; D. Arnold ; W. Banzhaf ; C. Blum ; E.W. Bonabeau ; E. Cantu-Paz ; D. Dasgupta ; K. Deb ; al et al. 2005. pp. 1021-1028 (GECCO 2005 - Genetic and Evolutionary Computation Conference).

@inproceedings{f0e9fdec18ce4096ab1b9834a64540d4,

title = "Stress testing real-time systems with genetic algorithms",

abstract = "Reactive real-time systems have to react to external events within time constraints: Triggered tasks must execute within deadlines. The goal of this article is to automate, based on the system task architecture, the derivation of test cases that maximize the chances of critical deadline misses within the system. We refer to that testing activity as stress testing. We have developed a method based on genetic algorithms and implemented it in a tool. Case studies were run and results show that the tool may actually help testers identify test cases that will likely stress the system to such an extent that some tasks may miss deadlines.",

keywords = "Genetic algorithms, Schedulability theory",

author = "Briand, {Lionel C.} and Yvan Labiche and Marwa Shousha",

year = "2005",

doi = "10.1145/1068009.1068183",

language = "English",

isbn = "1595930108",

series = "GECCO 2005 - Genetic and Evolutionary Computation Conference",

pages = "1021--1028",

editor = "H.G. Beyer and U.M. O'Reilly and D. Arnold and W. Banzhaf and C. Blum and E.W. Bonabeau and E. Cantu-Paz and D. Dasgupta and K. Deb and {et al}, al",

booktitle = "GECCO 2005 - Genetic and Evolutionary Computation Conference",

note = "GECCO 2005 - Genetic and Evolutionary Computation Conference ; Conference date: 25-06-2005 Through 29-06-2005",

}

Briand, LC, Labiche, Y & Shousha, M 2005, Stress testing real-time systems with genetic algorithms. in HG Beyer, UM O'Reilly, D Arnold, W Banzhaf, C Blum, EW Bonabeau, E Cantu-Paz, D Dasgupta, K Deb & A et al (eds), GECCO 2005 - Genetic and Evolutionary Computation Conference. GECCO 2005 - Genetic and Evolutionary Computation Conference, pp. 1021-1028, GECCO 2005 - Genetic and Evolutionary Computation Conference, Washington, D.C., United States, 25/06/05. https://doi.org/10.1145/1068009.1068183

Stress testing real-time systems with genetic algorithms. / Briand, Lionel C.; Labiche, Yvan; Shousha, Marwa.
GECCO 2005 - Genetic and Evolutionary Computation Conference. ed. / H.G. Beyer; U.M. O'Reilly; D. Arnold; W. Banzhaf; C. Blum; E.W. Bonabeau; E. Cantu-Paz; D. Dasgupta; K. Deb; al et al. 2005. p. 1021-1028 (GECCO 2005 - Genetic and Evolutionary Computation Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Stress testing real-time systems with genetic algorithms

AU - Briand, Lionel C.

AU - Labiche, Yvan

AU - Shousha, Marwa

PY - 2005

Y1 - 2005

N2 - Reactive real-time systems have to react to external events within time constraints: Triggered tasks must execute within deadlines. The goal of this article is to automate, based on the system task architecture, the derivation of test cases that maximize the chances of critical deadline misses within the system. We refer to that testing activity as stress testing. We have developed a method based on genetic algorithms and implemented it in a tool. Case studies were run and results show that the tool may actually help testers identify test cases that will likely stress the system to such an extent that some tasks may miss deadlines.

AB - Reactive real-time systems have to react to external events within time constraints: Triggered tasks must execute within deadlines. The goal of this article is to automate, based on the system task architecture, the derivation of test cases that maximize the chances of critical deadline misses within the system. We refer to that testing activity as stress testing. We have developed a method based on genetic algorithms and implemented it in a tool. Case studies were run and results show that the tool may actually help testers identify test cases that will likely stress the system to such an extent that some tasks may miss deadlines.

KW - Genetic algorithms

KW - Schedulability theory

UR - http://www.scopus.com/inward/record.url?scp=32444445648&partnerID=8YFLogxK

U2 - 10.1145/1068009.1068183

DO - 10.1145/1068009.1068183

M3 - Conference contribution

AN - SCOPUS:32444445648

SN - 1595930108

T3 - GECCO 2005 - Genetic and Evolutionary Computation Conference

SP - 1021

EP - 1028

BT - GECCO 2005 - Genetic and Evolutionary Computation Conference

A2 - Beyer, H.G.

A2 - O'Reilly, U.M.

A2 - Arnold, D.

A2 - Banzhaf, W.

A2 - Blum, C.

A2 - Bonabeau, E.W.

A2 - Cantu-Paz, E.

A2 - Dasgupta, D.

A2 - Deb, K.

A2 - et al, al

T2 - GECCO 2005 - Genetic and Evolutionary Computation Conference

Y2 - 25 June 2005 through 29 June 2005

ER -

Briand LC, Labiche Y, Shousha M. Stress testing real-time systems with genetic algorithms. In Beyer HG, O'Reilly UM, Arnold D, Banzhaf W, Blum C, Bonabeau EW, Cantu-Paz E, Dasgupta D, Deb K, et al A, editors, GECCO 2005 - Genetic and Evolutionary Computation Conference. 2005. p. 1021-1028. (GECCO 2005 - Genetic and Evolutionary Computation Conference). doi: 10.1145/1068009.1068183

Stress testing real-time systems with genetic algorithms

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this