Mining branching-time scenarios

Dirk Fahland; David Lo; Shahar Maoz

doi:10.1109/ASE.2013.6693102

Mining branching-time scenarios

Dirk Fahland
, David Lo
, Shahar Maoz

School of Computer Science and AI

Tel Aviv University

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

Abstract

Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows the unique contribution of mining branching-time scenarios to the state-of-the-art in specification mining.

Original language	English
Title of host publication	2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings
Publisher	IEEE Computer Society
Pages	443-453
Number of pages	11
ISBN (Print)	9781479902156
DOIs	https://doi.org/10.1109/ASE.2013.6693102
State	Published - 2013
Event	28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Palo Alto, CA, United States Duration: 11 Nov 2013 → 15 Nov 2013

Publication series

Name	2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings

Conference

Conference	28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013
Country/Territory	United States
City	Palo Alto, CA
Period	11/11/13 → 15/11/13

ASJC Scopus subject areas

Software

Access to Document

10.1109/ASE.2013.6693102

Cite this

Fahland, D., Lo, D., & Maoz, S. (2013). Mining branching-time scenarios. In 2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings (pp. 443-453). Article 6693102 (2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings). IEEE Computer Society. https://doi.org/10.1109/ASE.2013.6693102

@inproceedings{0a14fb1b8b5b4a4b8b3ed49ea670166e,

title = "Mining branching-time scenarios",

abstract = "Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows the unique contribution of mining branching-time scenarios to the state-of-the-art in specification mining.",

author = "Dirk Fahland and David Lo and Shahar Maoz",

year = "2013",

doi = "10.1109/ASE.2013.6693102",

language = "English",

isbn = "9781479902156",

series = "2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings",

publisher = "IEEE Computer Society",

pages = "443--453",

booktitle = "2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings",

address = "United States",

note = "28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 ; Conference date: 11-11-2013 Through 15-11-2013",

}

Fahland, D, Lo, D & Maoz, S 2013, Mining branching-time scenarios. in 2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings., 6693102, 2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings, IEEE Computer Society, pp. 443-453, 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013, Palo Alto, CA, United States, 11/11/13. https://doi.org/10.1109/ASE.2013.6693102

Mining branching-time scenarios. / Fahland, Dirk; Lo, David; Maoz, Shahar.
2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings. IEEE Computer Society, 2013. p. 443-453 6693102 (2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings).

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

TY - GEN

T1 - Mining branching-time scenarios

AU - Fahland, Dirk

AU - Lo, David

AU - Maoz, Shahar

PY - 2013

Y1 - 2013

N2 - Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows the unique contribution of mining branching-time scenarios to the state-of-the-art in specification mining.

AB - Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows the unique contribution of mining branching-time scenarios to the state-of-the-art in specification mining.

UR - https://www.scopus.com/pages/publications/84893536557

U2 - 10.1109/ASE.2013.6693102

DO - 10.1109/ASE.2013.6693102

M3 - Conference contribution

SN - 9781479902156

T3 - 2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings

SP - 443

EP - 453

BT - 2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings

PB - IEEE Computer Society

T2 - 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013

Y2 - 11 November 2013 through 15 November 2013

ER -

Mining branching-time scenarios

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this