A Safe Regression Test Selection Technique for Modelica

Niklas Fors; Jon Sten; Markus Olsson; Filip Stenström

A Safe Regression Test Selection Technique for Modelica

Niklas Fors, Jon Sten, Markus Olsson, Filip Stenström

Modelon AB

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

232 Nedladdningar (Pure)

Sammanfattning

Running regression tests for Modelica models usually takes a long time. This paper presents a safe regression test selection technique for Modelica based on static analysis. The technique tracks dependencies between classes to compute which tests that need to be run given a change. The dependency rules have been verified using mutation testing. The technique has been evaluated on the Modelica Standard Library and another library with promising results.

Originalspråk	engelska
Titel på värdpublikation	Proceedings of the American Modelica Conference
Status	Published - 2018 okt.
Evenemang	American Modelica Conference - Boston, USA Varaktighet: 2018 okt. 9 → 2018 okt. 10 https://modelica.org/events/modelica2018Americas

Konferens

Konferens	American Modelica Conference
Land/Territorium	USA
Ort	Boston
Period	2018/10/09 → 2018/10/10
Internetadress	https://modelica.org/events/modelica2018Americas

Ämnesklassifikation (UKÄ)

Datavetenskap (Datalogi)

Tillgång till dokument

modelica-test-selectionPublicerad version, 876 KBLicens: Ospecificerad

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Hedin, G. (PI), Fors, N. (Forskare) & Andersson, C. (Administratör)
Swedish Government Agency for Innovation Systems (Vinnova)
2017/09/01 → 2020/08/31
Projekt: Forskning
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2016/01/01 → 2020/12/31
Projekt: Forskning

Citera det här

@inproceedings{bbd9fe8a0f9d462388c3cf5f4552642c,

title = "A Safe Regression Test Selection Technique for Modelica",

abstract = "Running regression tests for Modelica models usually takes a long time. This paper presents a safe regression test selection technique for Modelica based on static analysis. The technique tracks dependencies between classes to compute which tests that need to be run given a change. The dependency rules have been verified using mutation testing. The technique has been evaluated on the Modelica Standard Library and another library with promising results.",

author = "Niklas Fors and Jon Sten and Markus Olsson and Filip Stenstr{\"o}m",

year = "2018",

month = oct,

language = "English",

booktitle = "Proceedings of the American Modelica Conference",

note = "American Modelica Conference ; Conference date: 09-10-2018 Through 10-10-2018",

url = "https://modelica.org/events/modelica2018Americas",

}

TY - GEN

T1 - A Safe Regression Test Selection Technique for Modelica

AU - Fors, Niklas

AU - Sten, Jon

AU - Olsson, Markus

AU - Stenström, Filip

PY - 2018/10

Y1 - 2018/10

N2 - Running regression tests for Modelica models usually takes a long time. This paper presents a safe regression test selection technique for Modelica based on static analysis. The technique tracks dependencies between classes to compute which tests that need to be run given a change. The dependency rules have been verified using mutation testing. The technique has been evaluated on the Modelica Standard Library and another library with promising results.

AB - Running regression tests for Modelica models usually takes a long time. This paper presents a safe regression test selection technique for Modelica based on static analysis. The technique tracks dependencies between classes to compute which tests that need to be run given a change. The dependency rules have been verified using mutation testing. The technique has been evaluated on the Modelica Standard Library and another library with promising results.

M3 - Paper in conference proceeding

BT - Proceedings of the American Modelica Conference

T2 - American Modelica Conference

Y2 - 9 October 2018 through 10 October 2018

ER -

A Safe Regression Test Selection Technique for Modelica

Sammanfattning

Konferens

Ämnesklassifikation (UKÄ)

Tillgång till dokument

Fingeravtryck

Projekt

Bloqqi - ett öppet modulärt automationsspråk

ELLIIT LU P05: Scalable Language Tools for Cyber-Physical Systems

Citera det här