Scenario-Based and Value-Based Specification Mining: Better Together

Specification mining takes execution traces as input and extracts likely program invariants, which can be used for comprehension, verification, and evolution related tasks. In this work we integrate scenario-based specification mining, which uses a data-mining algorithm to suggest ordering constrain...

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Main Authors: LO, David, MAOZ, Shahar
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Language:English
Published: Institutional Knowledge at Singapore Management University 2012
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Online Access:https://ink.library.smu.edu.sg/sis_research/1558
https://ink.library.smu.edu.sg/context/sis_research/article/2557/viewcontent/Scenario_based_value_based_specification_mining_better_av_2012.pdf
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spelling sg-smu-ink.sis_research-25572020-04-24T06:29:38Z Scenario-Based and Value-Based Specification Mining: Better Together LO, David MAOZ, Shahar Specification mining takes execution traces as input and extracts likely program invariants, which can be used for comprehension, verification, and evolution related tasks. In this work we integrate scenario-based specification mining, which uses a data-mining algorithm to suggest ordering constraints in the form of live sequence charts, an inter-object, visual, modal, scenario-based specification language, with mining of value-based invariants, which detects likely invariants holding at specific program points. The key to the integration is a technique we call scenario-based slicing, running on top of the mining algorithms to distinguish the scenario-specific invariants from the general ones. The resulting suggested specifications are rich, consisting of modal scenarios annotated with scenario-specific value-based invariants, referring to event parameters and participating object properties. We have implemented the mining algorithm and the visual presentation of the mined scenarios within a standard development environment. An evaluation of our work over a number of case studies shows promising results in extracting expressive specifications from real programs, which could not be extracted previously. The more expressive the mined specifications, the higher their potential to support program comprehension and testing. 2012-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1558 info:doi/10.1007/s10515-012-0103-x https://ink.library.smu.edu.sg/context/sis_research/article/2557/viewcontent/Scenario_based_value_based_specification_mining_better_av_2012.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 Specification mining Dynamic analysis Live sequence charts Value-based invariants Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Specification mining
Dynamic analysis
Live sequence charts
Value-based invariants
Software Engineering
spellingShingle Specification mining
Dynamic analysis
Live sequence charts
Value-based invariants
Software Engineering
LO, David
MAOZ, Shahar
Scenario-Based and Value-Based Specification Mining: Better Together
description Specification mining takes execution traces as input and extracts likely program invariants, which can be used for comprehension, verification, and evolution related tasks. In this work we integrate scenario-based specification mining, which uses a data-mining algorithm to suggest ordering constraints in the form of live sequence charts, an inter-object, visual, modal, scenario-based specification language, with mining of value-based invariants, which detects likely invariants holding at specific program points. The key to the integration is a technique we call scenario-based slicing, running on top of the mining algorithms to distinguish the scenario-specific invariants from the general ones. The resulting suggested specifications are rich, consisting of modal scenarios annotated with scenario-specific value-based invariants, referring to event parameters and participating object properties. We have implemented the mining algorithm and the visual presentation of the mined scenarios within a standard development environment. An evaluation of our work over a number of case studies shows promising results in extracting expressive specifications from real programs, which could not be extracted previously. The more expressive the mined specifications, the higher their potential to support program comprehension and testing.
format text
author LO, David
MAOZ, Shahar
author_facet LO, David
MAOZ, Shahar
author_sort LO, David
title Scenario-Based and Value-Based Specification Mining: Better Together
title_short Scenario-Based and Value-Based Specification Mining: Better Together
title_full Scenario-Based and Value-Based Specification Mining: Better Together
title_fullStr Scenario-Based and Value-Based Specification Mining: Better Together
title_full_unstemmed Scenario-Based and Value-Based Specification Mining: Better Together
title_sort scenario-based and value-based specification mining: better together
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/sis_research/1558
https://ink.library.smu.edu.sg/context/sis_research/article/2557/viewcontent/Scenario_based_value_based_specification_mining_better_av_2012.pdf
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