Extraction-Based Regression Test Selection

Jesper Öqvist; Görel Hedin; Boris Magnusson

doi:10.1145/2972206.2972224

Extraction-Based Regression Test Selection

Jesper Öqvist, Görel Hedin, Boris Magnusson

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

Abstract

Frequent regression testing is a core activity in agile software development, but large test suites can lead to long test running times, hampering agility. By safe RTS (Regression Test Selection) techniques, a subset of the tests can be identified that cover all tests that can change result since the last run. To pay off in practice, the RTS overhead must be low. Most existing RTS techniques are based on dynamic coverage analysis, making the overhead related to the tests run. We present Extraction-Based RTS, a new safe RTS technique which uses a fast static analysis with very low overhead, related to the size of the modification rather than to the tests run. The method is suitable for program-driven testing, commonly used in agile development, where each test is a piece of code that uses parts of the system under test. We have implemented the method for Java, and bench-marked it on a number of open source projects, showing that it pays off substantially in practice.

Original language	English
Title of host publication	Proceedings of the 13th International Conference on Principles and Practices of Programming on the Java Platform
Subtitle of host publication	Virtual Machines, Languages, and Tools
Publisher	Association for Computing Machinery (ACM)
ISBN (Electronic)	978-1-4503-4135-6
DOIs	https://doi.org/10.1145/2972206.2972224
Publication status	Published - 2016 Aug 29
Event	13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools, PPJ '16 - Lugano, Switzerland Duration: 2016 Aug 29 → 2016 Sept 2

Conference

Conference	13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools, PPJ '16
Country/Territory	Switzerland
City	Lugano
Period	2016/08/29 → 2016/09/02

Subject classification (UKÄ)

Computer Sciences

Access to Document

10.1145/2972206.2972224

1 Doctoral Thesis (compilation)

Contributions to Declarative Implementation of Static Program Analysis
Öqvist, J., 2018 Dec 19, Lund: Department of Computer Science, Lund University. 197 p.
Research output: Thesis › Doctoral Thesis (compilation)

Open Access
File

2 Finished

ELLIIT LU P05: Scalable Language Tools for Cyber-Physical Systems
Hedin, G. (PI), Fors, N. (Researcher) & Öqvist, J. (Researcher)
2016/01/01 → 2020/12/31
Project: Research
Contributions to Declarative Implementation of Static Program Analysis
Öqvist, J. (Researcher), Hedin, G. (Supervisor), Magnusson, B. (Assistant supervisor) & Söderberg, E. (Assistant supervisor)
Swedish Research Council
2013/02/01 → 2019/01/31
Project: Dissertation

Cite this

@inproceedings{182aae2b336d4340941efafddf652981,

title = "Extraction-Based Regression Test Selection",

abstract = "Frequent regression testing is a core activity in agile software development, but large test suites can lead to long test running times, hampering agility. By safe RTS (Regression Test Selection) techniques, a subset of the tests can be identified that cover all tests that can change result since the last run. To pay off in practice, the RTS overhead must be low. Most existing RTS techniques are based on dynamic coverage analysis, making the overhead related to the tests run. We present Extraction-Based RTS, a new safe RTS technique which uses a fast static analysis with very low overhead, related to the size of the modification rather than to the tests run. The method is suitable for program-driven testing, commonly used in agile development, where each test is a piece of code that uses parts of the system under test. We have implemented the method for Java, and bench-marked it on a number of open source projects, showing that it pays off substantially in practice.",

author = "Jesper {\"O}qvist and G{\"o}rel Hedin and Boris Magnusson",

year = "2016",

month = aug,

day = "29",

doi = "10.1145/2972206.2972224",

language = "English",

booktitle = "Proceedings of the 13th International Conference on Principles and Practices of Programming on the Java Platform",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools, PPJ '16 ; Conference date: 29-08-2016 Through 02-09-2016",

}

Öqvist, J, Hedin, G & Magnusson, B 2016, Extraction-Based Regression Test Selection. in Proceedings of the 13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools., 5, Association for Computing Machinery (ACM), 13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools, PPJ '16 , Lugano, Switzerland, 2016/08/29. https://doi.org/10.1145/2972206.2972224

Extraction-Based Regression Test Selection. / Öqvist, Jesper; Hedin, Görel ; Magnusson, Boris.
Proceedings of the 13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools. Association for Computing Machinery (ACM), 2016. 5.

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

TY - GEN

T1 - Extraction-Based Regression Test Selection

AU - Öqvist, Jesper

AU - Hedin, Görel

AU - Magnusson, Boris

PY - 2016/8/29

Y1 - 2016/8/29

N2 - Frequent regression testing is a core activity in agile software development, but large test suites can lead to long test running times, hampering agility. By safe RTS (Regression Test Selection) techniques, a subset of the tests can be identified that cover all tests that can change result since the last run. To pay off in practice, the RTS overhead must be low. Most existing RTS techniques are based on dynamic coverage analysis, making the overhead related to the tests run. We present Extraction-Based RTS, a new safe RTS technique which uses a fast static analysis with very low overhead, related to the size of the modification rather than to the tests run. The method is suitable for program-driven testing, commonly used in agile development, where each test is a piece of code that uses parts of the system under test. We have implemented the method for Java, and bench-marked it on a number of open source projects, showing that it pays off substantially in practice.

AB - Frequent regression testing is a core activity in agile software development, but large test suites can lead to long test running times, hampering agility. By safe RTS (Regression Test Selection) techniques, a subset of the tests can be identified that cover all tests that can change result since the last run. To pay off in practice, the RTS overhead must be low. Most existing RTS techniques are based on dynamic coverage analysis, making the overhead related to the tests run. We present Extraction-Based RTS, a new safe RTS technique which uses a fast static analysis with very low overhead, related to the size of the modification rather than to the tests run. The method is suitable for program-driven testing, commonly used in agile development, where each test is a piece of code that uses parts of the system under test. We have implemented the method for Java, and bench-marked it on a number of open source projects, showing that it pays off substantially in practice.

U2 - 10.1145/2972206.2972224

DO - 10.1145/2972206.2972224

M3 - Paper in conference proceeding

BT - Proceedings of the 13th International Conference on Principles and Practices of Programming on the Java Platform

PB - Association for Computing Machinery (ACM)

T2 - 13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools, PPJ '16

Y2 - 29 August 2016 through 2 September 2016

ER -

Extraction-Based Regression Test Selection

Abstract

Conference

Subject classification (UKÄ)

Access to Document

Fingerprint

Research output

Contributions to Declarative Implementation of Static Program Analysis

Projects

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

Contributions to Declarative Implementation of Static Program Analysis

Cite this