Detection of Polluting Test Objectives for Dataflow Criteria

Thibault Martin; Nikolai Kosmatov; Virgile Prevosto; Matthieu Lemerre

doi:10.1007/978-3-030-63461-2_18

Detection of Polluting Test Objectives for Dataflow Criteria

Thibault Martin
, Nikolai Kosmatov
, Virgile Prevosto
, Matthieu Lemerre

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

Abstract

Dataflow test coverage criteria, such as all-defs and all-uses, belong to the most advanced coverage criteria. These criteria are defined by complex artifacts combining variable definitions, uses and program paths. Detection of polluting (i.e. inapplicable, infeasible and equivalent) test objectives for such criteria is a particularly challenging task. This short paper evaluates three detection approaches involving dataflow analysis, value analysis and weakest precondition calculus. We implement and compare these approaches, analyze their detection capacities and propose a methodology for their efficient combination. Initial experiments illustrate the benefits of the proposed approach.

Original language	English
Title of host publication	Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings
Editors	Brijesh Dongol, Elena Troubitsyna
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	337-345
Number of pages	9
ISBN (Print)	9783030634605
DOIs	https://doi.org/10.1007/978-3-030-63461-2_18
Publication status	Published - 1 Jan 2020
Externally published	Yes
Event	16th International Conference on Integrated Formal Methods, IFM 2020 - Lugano, Switzerland Duration: 16 Nov 2020 → 20 Nov 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12546 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Integrated Formal Methods, IFM 2020
Country/Territory	Switzerland
City	Lugano
Period	16/11/20 → 20/11/20

Access to Document

10.1007/978-3-030-63461-2_18

Cite this

Martin, T., Kosmatov, N., Prevosto, V., & Lemerre, M. (2020). Detection of Polluting Test Objectives for Dataflow Criteria. In B. Dongol, & E. Troubitsyna (Eds.), Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings (pp. 337-345). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12546 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-63461-2_18

Martin, Thibault ; Kosmatov, Nikolai ; Prevosto, Virgile et al. / Detection of Polluting Test Objectives for Dataflow Criteria. Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings. editor / Brijesh Dongol ; Elena Troubitsyna. Springer Science and Business Media Deutschland GmbH, 2020. pp. 337-345 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c06645f21781439091a978eb374db7bf,

title = "Detection of Polluting Test Objectives for Dataflow Criteria",

abstract = "Dataflow test coverage criteria, such as all-defs and all-uses, belong to the most advanced coverage criteria. These criteria are defined by complex artifacts combining variable definitions, uses and program paths. Detection of polluting (i.e. inapplicable, infeasible and equivalent) test objectives for such criteria is a particularly challenging task. This short paper evaluates three detection approaches involving dataflow analysis, value analysis and weakest precondition calculus. We implement and compare these approaches, analyze their detection capacities and propose a methodology for their efficient combination. Initial experiments illustrate the benefits of the proposed approach.",

author = "Thibault Martin and Nikolai Kosmatov and Virgile Prevosto and Matthieu Lemerre",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 16th International Conference on Integrated Formal Methods, IFM 2020 ; Conference date: 16-11-2020 Through 20-11-2020",

year = "2020",

month = jan,

day = "1",

doi = "10.1007/978-3-030-63461-2\_18",

language = "English",

isbn = "9783030634605",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "337--345",

editor = "Brijesh Dongol and Elena Troubitsyna",

booktitle = "Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings",

}

Martin, T, Kosmatov, N, Prevosto, V & Lemerre, M 2020, Detection of Polluting Test Objectives for Dataflow Criteria. in B Dongol & E Troubitsyna (eds), Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12546 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 337-345, 16th International Conference on Integrated Formal Methods, IFM 2020, Lugano, Switzerland, 16/11/20. https://doi.org/10.1007/978-3-030-63461-2_18

Detection of Polluting Test Objectives for Dataflow Criteria. / Martin, Thibault; Kosmatov, Nikolai; Prevosto, Virgile et al.
Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings. ed. / Brijesh Dongol; Elena Troubitsyna. Springer Science and Business Media Deutschland GmbH, 2020. p. 337-345 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12546 LNCS).

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

TY - GEN

T1 - Detection of Polluting Test Objectives for Dataflow Criteria

AU - Martin, Thibault

AU - Kosmatov, Nikolai

AU - Prevosto, Virgile

AU - Lemerre, Matthieu

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Dataflow test coverage criteria, such as all-defs and all-uses, belong to the most advanced coverage criteria. These criteria are defined by complex artifacts combining variable definitions, uses and program paths. Detection of polluting (i.e. inapplicable, infeasible and equivalent) test objectives for such criteria is a particularly challenging task. This short paper evaluates three detection approaches involving dataflow analysis, value analysis and weakest precondition calculus. We implement and compare these approaches, analyze their detection capacities and propose a methodology for their efficient combination. Initial experiments illustrate the benefits of the proposed approach.

AB - Dataflow test coverage criteria, such as all-defs and all-uses, belong to the most advanced coverage criteria. These criteria are defined by complex artifacts combining variable definitions, uses and program paths. Detection of polluting (i.e. inapplicable, infeasible and equivalent) test objectives for such criteria is a particularly challenging task. This short paper evaluates three detection approaches involving dataflow analysis, value analysis and weakest precondition calculus. We implement and compare these approaches, analyze their detection capacities and propose a methodology for their efficient combination. Initial experiments illustrate the benefits of the proposed approach.

UR - https://www.scopus.com/pages/publications/85097430927

U2 - 10.1007/978-3-030-63461-2_18

DO - 10.1007/978-3-030-63461-2_18

M3 - Conference contribution

AN - SCOPUS:85097430927

SN - 9783030634605

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 337

EP - 345

BT - Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings

A2 - Dongol, Brijesh

A2 - Troubitsyna, Elena

PB - Springer Science and Business Media Deutschland GmbH

T2 - 16th International Conference on Integrated Formal Methods, IFM 2020

Y2 - 16 November 2020 through 20 November 2020

ER -

Martin T, Kosmatov N, Prevosto V, Lemerre M. Detection of Polluting Test Objectives for Dataflow Criteria. In Dongol B, Troubitsyna E, editors, Integrated Formal Methods - 16th International Conference, IFM 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 337-345. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-63461-2_18

Detection of Polluting Test Objectives for Dataflow Criteria

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this