Standard

A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations. / De Bleser, Jonas; Di Nucci, Dario; De Roover, Coen.

Proceedings of the 1st International Conference on Automated Software Testing (AST2020). 2020.

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

Harvard

De Bleser, J, Di Nucci, D & De Roover, C 2020, A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations. in Proceedings of the 1st International Conference on Automated Software Testing (AST2020). IEEE/ACM International Conference on Automation of Software Testing, Seoul, 25/05/20.

APA

De Bleser, J., Di Nucci, D., & De Roover, C. (Accepted/In press). A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations. In Proceedings of the 1st International Conference on Automated Software Testing (AST2020)

Vancouver

De Bleser J, Di Nucci D, De Roover C. A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations. In Proceedings of the 1st International Conference on Automated Software Testing (AST2020). 2020

Author

BibTeX

@inproceedings{0bae763ca2864ea1af2a7cc06dcdec26,
title = "A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations",
abstract = "Among distributed applications, the actor model is increasingly prevalent. This programming model organises applications into fully-isolated processes that communicate through asynchronous messaging. Supported by frameworks such as Akka and Orleans, it is believed to facilitate realising responsive, elastic and resilient distributed applications. While these frameworks do provide abstractions for implementing resilience, it remains up to developers to use them correctly and to test that their implementation actually recovers from anticipated failures. As manually exploring the reaction to every possible failure scenario is infeasible, there is a need for automated means of testing the resilience of a distributed application.We present the first automated approach to testing the resilience of actor programs. Our approach perturbs the execution of existing test cases and leverages delta debugging to explore all failure scenarios more efficiently. Moreover, we present a further optimisation that uses causality to prune away redundant perturbations and speed up the exploration. However, its effectiveness is sensitive to the program’s organisation and to the actual location of the fault.Our experimental evaluation shows that our approach can speed up resilience testing by four times compared to random exploration.",
keywords = "automated testing, software resilience, distributed systems, fault injection, test amplification, delta debugging",
author = "{De Bleser}, Jonas and {Di Nucci}, Dario and {De Roover}, Coen",
year = "2020",
language = "English",
booktitle = "Proceedings of the 1st International Conference on Automated Software Testing (AST2020)",

}

RIS

TY - GEN

T1 - A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations

AU - De Bleser, Jonas

AU - Di Nucci, Dario

AU - De Roover, Coen

PY - 2020

Y1 - 2020

N2 - Among distributed applications, the actor model is increasingly prevalent. This programming model organises applications into fully-isolated processes that communicate through asynchronous messaging. Supported by frameworks such as Akka and Orleans, it is believed to facilitate realising responsive, elastic and resilient distributed applications. While these frameworks do provide abstractions for implementing resilience, it remains up to developers to use them correctly and to test that their implementation actually recovers from anticipated failures. As manually exploring the reaction to every possible failure scenario is infeasible, there is a need for automated means of testing the resilience of a distributed application.We present the first automated approach to testing the resilience of actor programs. Our approach perturbs the execution of existing test cases and leverages delta debugging to explore all failure scenarios more efficiently. Moreover, we present a further optimisation that uses causality to prune away redundant perturbations and speed up the exploration. However, its effectiveness is sensitive to the program’s organisation and to the actual location of the fault.Our experimental evaluation shows that our approach can speed up resilience testing by four times compared to random exploration.

AB - Among distributed applications, the actor model is increasingly prevalent. This programming model organises applications into fully-isolated processes that communicate through asynchronous messaging. Supported by frameworks such as Akka and Orleans, it is believed to facilitate realising responsive, elastic and resilient distributed applications. While these frameworks do provide abstractions for implementing resilience, it remains up to developers to use them correctly and to test that their implementation actually recovers from anticipated failures. As manually exploring the reaction to every possible failure scenario is infeasible, there is a need for automated means of testing the resilience of a distributed application.We present the first automated approach to testing the resilience of actor programs. Our approach perturbs the execution of existing test cases and leverages delta debugging to explore all failure scenarios more efficiently. Moreover, we present a further optimisation that uses causality to prune away redundant perturbations and speed up the exploration. However, its effectiveness is sensitive to the program’s organisation and to the actual location of the fault.Our experimental evaluation shows that our approach can speed up resilience testing by four times compared to random exploration.

KW - automated testing

KW - software resilience

KW - distributed systems

KW - fault injection

KW - test amplification

KW - delta debugging

M3 - Conference paper

BT - Proceedings of the 1st International Conference on Automated Software Testing (AST2020)

ER -

ID: 49563760