Mining Modal Scenarios from Execution Traces

Specification mining is a dynamic analysis process aimed at automatically inferring suggested specifications of a program from its execution traces. We describe a method, a framework, and a tool, for mining inter-object scenario-based specifications in the form of a UML2-compliant variant of Damm an...

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Main Authors: LO, David, MAOZ, Shahar, KHOO, Siau-Cheng
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Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/944
https://ink.library.smu.edu.sg/context/sis_research/article/1943/viewcontent/Mining_modal_scenarios_from_execution_traces.pdf
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spelling sg-smu-ink.sis_research-19432018-08-16T01:06:23Z Mining Modal Scenarios from Execution Traces LO, David MAOZ, Shahar KHOO, Siau-Cheng Specification mining is a dynamic analysis process aimed at automatically inferring suggested specifications of a program from its execution traces. We describe a method, a framework, and a tool, for mining inter-object scenario-based specifications in the form of a UML2-compliant variant of Damm and Harel's Live Sequence Charts (LSC), which extends the classical partial order semantics of sequence diagrams with temporal liveness and symbolic class level lifelines, in order to generate compact and expressive specifications. Moreover, we use previous research work and tools developed for LSC to visualize, analyze, manipulate, test, and thus evaluate the scenario-based specifications we mine. Our mining framework is supported by statistically sound metrics. Its effectiveness and the usefulness of the mined scenarios are further improved by an array of extensions to the basic mining algorithm, which include various user-guided filters and abstraction mechanisms. We demonstrate and evaluate our work using a case study. 2007-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/944 info:doi/10.1145/1297846.1297883 https://ink.library.smu.edu.sg/context/sis_research/article/1943/viewcontent/Mining_modal_scenarios_from_execution_traces.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 Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Software Engineering
spellingShingle Software Engineering
LO, David
MAOZ, Shahar
KHOO, Siau-Cheng
Mining Modal Scenarios from Execution Traces
description Specification mining is a dynamic analysis process aimed at automatically inferring suggested specifications of a program from its execution traces. We describe a method, a framework, and a tool, for mining inter-object scenario-based specifications in the form of a UML2-compliant variant of Damm and Harel's Live Sequence Charts (LSC), which extends the classical partial order semantics of sequence diagrams with temporal liveness and symbolic class level lifelines, in order to generate compact and expressive specifications. Moreover, we use previous research work and tools developed for LSC to visualize, analyze, manipulate, test, and thus evaluate the scenario-based specifications we mine. Our mining framework is supported by statistically sound metrics. Its effectiveness and the usefulness of the mined scenarios are further improved by an array of extensions to the basic mining algorithm, which include various user-guided filters and abstraction mechanisms. We demonstrate and evaluate our work using a case study.
format text
author LO, David
MAOZ, Shahar
KHOO, Siau-Cheng
author_facet LO, David
MAOZ, Shahar
KHOO, Siau-Cheng
author_sort LO, David
title Mining Modal Scenarios from Execution Traces
title_short Mining Modal Scenarios from Execution Traces
title_full Mining Modal Scenarios from Execution Traces
title_fullStr Mining Modal Scenarios from Execution Traces
title_full_unstemmed Mining Modal Scenarios from Execution Traces
title_sort mining modal scenarios from execution traces
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/944
https://ink.library.smu.edu.sg/context/sis_research/article/1943/viewcontent/Mining_modal_scenarios_from_execution_traces.pdf
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