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Aspect oriented programming with hidden markov models to verify design use cases

Authors:

German Florez-Larrahondo,

Walker HaddockAuthors Info & Claims

AOSD '09: Proceedings of the 8th ACM international conference on Aspect-oriented software development

Pages 223 - 228

https://doi.org/10.1145/1509239.1509269

Published: 02 March 2009 Publication History

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Abstract

The goal of this research is to formulate a framework to determine whether the usage of an application in production environments is consistent with the test cases used to verify it before the application was released. Aspect-Oriented Programming (AOP) techniques are used to apply the instrumentation required for the measuring process so that the program is oblivious to the instrumentation and Hidden Markov Models (HMMs) are used to create signatures of the program. This paper presents the preliminary findings on the use of such mathematical models to measure the completeness of use cases driving the quality assurance testing.

To demonstrate the technique, the Web Service API of a commercial product is used. SOAP calls executed through different client applications are used to create test data for the experiments. The HMMs signatures created from collecting method calls can be used to determine whether the application is used according to the uses cases that have been verified. If the likelihood that the stochastic model obtained during testing can generate the sequences of calls collected from the production environment (via AOP techniques) is low, then it suggests that the program is being used in a way that has not been formally tested. These experiments will show that observable differences of the measurements using log likelihood graphs can detect such anomalies.

References

[1]

J. Bilmes. What HMMs can do. Technical Report UWEETR--2002--0003, Department of Electrical Engineering, University of Washington, January 2002.

Google Scholar

[2]

E. Bodden and K. Havelund. Racer: Effective race detection using Aspectj. In ISSTA '08: Proceedings of the 2008 international symposium on Software testing and analysis, pages 155--166, New York, NY, USA, 2008. ACM.

Digital Library

Google Scholar

[3]

F. P. Brooks. No silver bullet -- essence and accidents of software engineering. Information Processing, 86:1069--1076, 1986.

Google Scholar

[4]

G. Florez, Z. Liu, S. Bridges, A. Skjellum, and R. Vaughn. Detecting anomalies in high-performance parallel programs. Journal of Digital Information Management, 2(2):44--47, June 2004.

Google Scholar

[5]

G. Florez-Larrahondo, S. Bridges, and E. A. Hansen. Incremental estimation of discrete hidden Markov models based on a new backward procedure. In Proceedings of the AAAI, pages 758--763. AAAI, 2005.

Digital Library

Google Scholar

[6]

G. Kiczales, E. Hilsdale, J. Hugunin, M. Kersten, J. Palm, and W. Griswold. Getting started with AspectJ. Commun. ACM, 44(10):59--65, 2001.

Digital Library

Google Scholar

[7]

G. Kiczales, E. Hilsdale, J. Hugunin, M. Kersten, J. Palm, and W. Griswold. An overview of AspectJ. In Proceedings of ECOOP, volume 44, pages 327--353, 2001.

Digital Library

Google Scholar

[8]

G. Kniesel and M. Austermann. CC4J -- Code Coverage for Java -- A Load-Time Adaptation Success Story. In In Proceedings of the 1 st IFIP ACM Working Conference on Component Deployment, number 2370 in LNCS, pages 155--169. Springer, 2002.

Digital Library

Google Scholar

[9]

J. Langford. Optimizing hidden Markov model learning. Technical report, Toyota Technological Institute at Chicago, Providence, RI 02912, 2003.

Google Scholar

[10]

I. MacDonald and W. Zucchini. Hidden Markov and Other Models for Discrete-valued Time Series. Monographs on Statistics and Applied Probability. Chapman and HALL/CRC, 1997.

Google Scholar

[11]

L. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. In Proceedings of the IEEE, volume 77 of 2, pages 257--286, February 1989.

Google Scholar

[12]

A. Rahimim. An erratum for: A tutorial on hidden Markov models and selected applications in speech recognition. World Wide Web. http://xenia.media.mit.edu/ rahimi/rabiner/rabiner- errata/rabiner-errata.html.

Google Scholar

[13]

G. Sun, H. Chen, Y. Lee, and C. Giles. Recurrent neural networks, hidden Markov models and stochastic grammars. In Proceedings of International Joint Conference on Neural Networks, pages 729--734, San Diego,CA, 1990.

Crossref

Google Scholar

[14]

Verari Systems Inc. Verari Systems Inc, Verari Command Center (VCC). World Wide Web, 2008. http://www.verari.com.

Google Scholar

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Rocha BConti MEtalle SCrispo B(2013)Hybrid Static-Runtime Information Flow and Declassification EnforcementIEEE Transactions on Information Forensics and Security10.1109/TIFS.2013.22677988:8(1294-1305)Online publication date: 1-Aug-2013
https://dl.acm.org/doi/10.1109/TIFS.2013.2267798

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Aspect oriented programming with hidden markov models to verify design use cases

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Published In

AOSD '09: Proceedings of the 8th ACM international conference on Aspect-oriented software development

March 2009

278 pages

ISBN:9781605584423

DOI:10.1145/1509239

General Chair:
Kevin Sullivan
University of Virginia, USA
,
Organizing Chair:
Jeff Gray
Univ. of Alabama at Birmingham, USA
,
Program Chairs:
Ana Moreira
Universidade Nova de Lisboa, Portugal
,
Christa Schwanninger
Siemens AG, Germany
,
Robert Baillargeon
Panasonic Automotive Systems, USA
,
Mark Grechanik
Accenture, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 02 March 2009

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AOSD '09: Eighth International Conference on Aspect-Oriented Software Development

March 2 - 6, 2009

Virginia, Charlottesville, USA

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Rocha BConti MEtalle SCrispo B(2013)Hybrid Static-Runtime Information Flow and Declassification EnforcementIEEE Transactions on Information Forensics and Security10.1109/TIFS.2013.22677988:8(1294-1305)Online publication date: 1-Aug-2013
https://dl.acm.org/doi/10.1109/TIFS.2013.2267798

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Abstract

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Coding with partially hidden Markov models

Structural hidden Markov models: An application to handwritten numeral recognition

Hidden semi-Markov models

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