research-article

Automated feature localization for hardware designs using coverage metrics

Authors:

Alexander Finder,

Görschwin FeyAuthors Info & Claims

DAC '12: Proceedings of the 49th Annual Design Automation Conference

Pages 941 - 946

https://doi.org/10.1145/2228360.2228529

Published: 03 June 2012 Publication History

Abstract

Due to the increasing complexity modern System on Chip designs are developed by large design teams. In addition, existing design blocks are re-used such that the knowledge about these parts of the design entirely depends on the quality of the documentation. For a single designer it is almost impossible to have detailed knowledge about all blocks and their interaction.

We introduce a simulation-based automation technique to support design understanding. Based on use cases provided by the designer and on their coverage information, the proposed technique identifies parts of the source code that are relevant for a certain functional feature. In two case studies the technique is shown to be at least as exact as reading the documentation with two important advantages: the automated approach is fast and more precise than the existing documentation for the inspected designs.

References

[1]

R. Abreu, P. Zoeteweij, and A. J. C. van Gemund. An evaluation of similarity coefficients for software fault localization. In Pacific Rim International Symposium on Dependable Computing, pages 39--46, 2006.

Digital Library

[2]

R. Abreu, P. Zoeteweij, and A. J. C. van Gemund. On the accuracy of spectrum-based fault localization. In Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION, pages 89--98, 2007.

Digital Library

[3]

E. Clarke, M. Fujita, S. Rajan, T. Reps, S. Shankar, and T. Teitelbaum. Program slicing of hardware description languages. In Correct Hardware Design and Verification Methods, volume 1703 of Lecture Notes in Computer Science, pages 72--72. 1999.

Digital Library

[4]

A. DeOrio, A. Bauserman, V. Bertacco, and B. Isaksen. Inferno: Streamlining verification with inferred semantics. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 28(5):728--741, 2009.

Digital Library

[5]

T. Eisenbarth, R. Koschke, and D. Simon. Locating features in source code. IEEE Transactions on Software Engineering, 29:210--224, 2003.

Digital Library

[6]

A. Fantozzi. Locating Features in Vim: A Software Reconnaissance Case Study. Technical report, 2002.

[7]

G. Fey and R. Drechsler. Improving simulation-based verification by means of formal methods. In Asia and South Pacific Design Automation Conference, pages 640--643, 2004.

Digital Library

[8]

IEEE 1364 Working Group. IEEE Standard for Verilog Hardware Description Language. IEEE Std 1364--2005 (Revision of IEEE Std 1364--2001), 2006.

[9]

ITRS Working Group. International technology roadmap for semiconductors 2009 update system drivers, 2009.

[10]

J. A. Jones, M. J. Harrold, and J. T. Stasko. Visualization for fault localization. In Proceedings of the Workshop on Software Visualization, pages 71--75, 2001.

[11]

W. Li, A. Forin, and S. A. Seshia. Scalable specification mining for verification and diagnosis. In Design Automation Conference, pages 755--760, 2010.

Digital Library

[12]

R. Santelices, J. A. Jones, Y. Yu, and M. J. Harrold. Lightweight fault-localization using multiple coverage types. In International Conference on Software Engineering, pages 56--66, 2009.

Digital Library

[13]

A. Sinha, P. Dasgupta, B. Pal, S. Das, P. Basu, and P. P. Chakrabarti. Design intent coverage revisited. ACM Transactions on Design Automation of Electronic Systems, 14:9:1--9:32, 2009.

Digital Library

[14]

S. Tasiran and K. Keutzer. Coverage metrics for functional validation of hardware designs. IEEE Design Test of Computers, 18(4):36--45, 2001.

Digital Library

[15]

N. Wilde and C. Casey. Early field experience with the software reconnaissance technique for program comprehension. In Working Conference on Reverse Engineering, pages 270--276, 1996.

Digital Library

[16]

N. Wilde and M. C. Scully. Software reconnaissance: Mapping program features to code. Journal of Software Maintenance: Research and Practice, 7(1):49--62, 1995.

Digital Library

Cited By

Stoppe JWille RDrechsler RNebel WAtienza D(2015)Automated feature localization for dynamically generated SystemC designsProceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition10.5555/2755753.2755814(277-280)Online publication date: 9-Mar-2015
https://dl.acm.org/doi/10.5555/2755753.2755814
Malburg JFinder AFey G(2014)A Simulation-Based Approach for Automated Feature LocalizationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2014.236046233:12(1886-1899)Online publication date: Dec-2014
https://doi.org/10.1109/TCAD.2014.2360462
Malburg JEncrenaz-Tiphene EFey G(2014)Mutation Based Feature LocalizationProceedings of the 2014 15th International Microprocessor Test and Verification Workshop10.1109/MTV.2014.14(49-54)Online publication date: 15-Dec-2014
https://dl.acm.org/doi/10.1109/MTV.2014.14
Show More Cited By

Index Terms

Automated feature localization for hardware designs using coverage metrics
1. Hardware
  1. Electronic design automation
    1. Physical design (EDA)

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Information & Contributors

Information

Published In

cover image ACM Conferences

DAC '12: Proceedings of the 49th Annual Design Automation Conference

June 2012

1357 pages

ISBN:9781450311991

DOI:10.1145/2228360

General Chair:
Patrick Groeneveld
Magma Design Automation, Inc., San Jose, CA
,
Program Chairs:
Donatella Sciuto
Politecnico di Milano, Milano, Italy
,
Soha Hassoun
Tufts Univ., Medford, MA

Copyright © 2012 ACM.

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]

Sponsors

EDAC: Electronic Design Automation Consortium
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CEDA

In-Cooperation

SIGBED: ACM Special Interest Group on Embedded Systems

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 June 2012

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Research-article

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Deutsche Forschungsgemeinschaft

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DAC '12

Sponsor:

EDAC
SIGDA

DAC '12: The 49th Annual Design Automation Conference 2012

June 3 - 7, 2012

California, San Francisco

Acceptance Rates

Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

Upcoming Conference

DAC '25

Sponsor:
sigda

62nd ACM/IEEE Design Automation Conference

June 22 - 26, 2025

San Francisco , CA , USA

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Cited By

Stoppe JWille RDrechsler RNebel WAtienza D(2015)Automated feature localization for dynamically generated SystemC designsProceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition10.5555/2755753.2755814(277-280)Online publication date: 9-Mar-2015
https://dl.acm.org/doi/10.5555/2755753.2755814
Malburg JFinder AFey G(2014)A Simulation-Based Approach for Automated Feature LocalizationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2014.236046233:12(1886-1899)Online publication date: Dec-2014
https://doi.org/10.1109/TCAD.2014.2360462
Malburg JEncrenaz-Tiphene EFey G(2014)Mutation Based Feature LocalizationProceedings of the 2014 15th International Microprocessor Test and Verification Workshop10.1109/MTV.2014.14(49-54)Online publication date: 15-Dec-2014
https://dl.acm.org/doi/10.1109/MTV.2014.14
Malburg JFinder AFey GMacii E(2013)Tuning dynamic data flow analysis to support design understandingProceedings of the Conference on Design, Automation and Test in Europe10.5555/2485288.2485572(1179-1184)Online publication date: 18-Mar-2013
https://dl.acm.org/doi/10.5555/2485288.2485572

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