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Tailored generation of concurrent benchmarks.

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Title: Tailored generation of concurrent benchmarks.
Authors: Steffen, Bernhard1 steffen@cs.tu-dortmund.de, Howar, Falk2 howar@cmu.edu, Isberner, Malte1 malte.isberner@cs.tu-dortmund.de, Naujokat, Stefan1 stefan.naujokat@cs.tu-dortmund.de, Margaria, Tiziana3 margaria@cs.uni-potsdam.de
Source: International Journal on Software Tools for Technology Transfer. Oct2014, Vol. 16 Issue 5, p543-558. 16p.
Subjects: Software validation, Benchmark testing (Engineering), Concurrent engineering, Statistical models, Computer software testing
Abstract: In this paper, we show how to extend our approach to property-driven benchmark generation (PDBG) to support concurrency in the benchmarks: we systematically produce multi-process PROMELA code of known and tailored complexity that can then serve as benchmark for the evaluation of analysis and verification tools for concurrent software systems. Key to this extension is the way in which we control the corresponding property profiles, i.e., the statements about the validity of a predefined set of LTL properties, along the PDBG tool chain. It is based on the idea to introduce intricate structural elements like synchronization and interference at a local and therefore controllable level, only concerning a few parallel components, and subsequently obfuscating the locality of these structures at the global level via property-preserving transformations of both the system components and the properties. This leads to a scalable approach which we illustrate along some concrete examples. [ABSTRACT FROM AUTHOR]
Copyright of International Journal on Software Tools for Technology Transfer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: <searchLink fieldCode="DE" term="%22Software+validation%22">Software validation</searchLink><br /><searchLink fieldCode="DE" term="%22Benchmark+testing+%28Engineering%29%22">Benchmark testing (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Concurrent+engineering%22">Concurrent engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+testing%22">Computer software testing</searchLink>
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  Data: In this paper, we show how to extend our approach to property-driven benchmark generation (PDBG) to support concurrency in the benchmarks: we systematically produce multi-process PROMELA code of known and tailored complexity that can then serve as benchmark for the evaluation of analysis and verification tools for concurrent software systems. Key to this extension is the way in which we control the corresponding property profiles, i.e., the statements about the validity of a predefined set of LTL properties, along the PDBG tool chain. It is based on the idea to introduce intricate structural elements like synchronization and interference at a local and therefore controllable level, only concerning a few parallel components, and subsequently obfuscating the locality of these structures at the global level via property-preserving transformations of both the system components and the properties. This leads to a scalable approach which we illustrate along some concrete examples. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal on Software Tools for Technology Transfer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10009-014-0339-9
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              Text: Oct2014
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