Mining Branching-Time Scenarios
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...
Saved in:
Main Authors: | , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2013
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/2029 https://ink.library.smu.edu.sg/context/sis_research/article/3028/viewcontent/FahlandLM_2013_ase_branching_mining.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.sis_research-3028 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.sis_research-30282015-12-12T09:09:31Z Mining Branching-Time Scenarios FAHLAND, Dirk LO, David MAOZ, Shahar 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. 2013-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2029 info:doi/10.1109/ASE.2013.6693102 https://ink.library.smu.edu.sg/context/sis_research/article/3028/viewcontent/FahlandLM_2013_ase_branching_mining.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University data mining formal verification program testing statistical analysis Software Engineering |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
data mining formal verification program testing statistical analysis Software Engineering |
spellingShingle |
data mining formal verification program testing statistical analysis Software Engineering FAHLAND, Dirk LO, David MAOZ, Shahar Mining Branching-Time Scenarios |
description |
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. |
format |
text |
author |
FAHLAND, Dirk LO, David MAOZ, Shahar |
author_facet |
FAHLAND, Dirk LO, David MAOZ, Shahar |
author_sort |
FAHLAND, Dirk |
title |
Mining Branching-Time Scenarios |
title_short |
Mining Branching-Time Scenarios |
title_full |
Mining Branching-Time Scenarios |
title_fullStr |
Mining Branching-Time Scenarios |
title_full_unstemmed |
Mining Branching-Time Scenarios |
title_sort |
mining branching-time scenarios |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2013 |
url |
https://ink.library.smu.edu.sg/sis_research/2029 https://ink.library.smu.edu.sg/context/sis_research/article/3028/viewcontent/FahlandLM_2013_ase_branching_mining.pdf |
_version_ |
1770571776396361728 |