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Detection and recovery of endangered variables caused by instruction scheduling

Authors:

Ali-Reza Adl-Tabatabai,

Thomas GrossAuthors Info & Claims

PLDI '93: Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation

Pages 13 - 25

https://doi.org/10.1145/155090.155092

Published: 01 June 1993 Publication History

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Abstract

Instruction scheduling re-orders and interleaves instruction sequences from different source statements. This impacts the task of a symbolic debugger, which attempts to present the user a picture of program execution that matches the source program. At a breakpoint B, if the value in the run-time location of a variable V may not correspond to the value the user expects V to have, then this variable is endangered at B. This paper describes an approach to detecting and recovering endangered variables caused by instruction scheduling. We measure the effects of instruction scheduling on a symbolic debugger's ability to recover source values at a breakpoint. This paper reports measurements for three C programs from the SPEC suite and a collection of programs from the Numerical Recipes, which have been compiled with a variant of a commercial C compiler.

References

[1]

A. Adl-Tabatabai and T. Gross. Evicted variables and symbolic debugging of optimized code. In Proc. 20th POPL Conf., pages 371 - 383. ACM, January 1993.

Digital Library

Google Scholar

[2]

Ali-Reza Adl-Tabatabai. Nonresident and endangered variables: The effects of code generation optimizations on symbolic debugging. Technical Report CMU-CS-92-221, CMU, December 1992.

Digital Library

Google Scholar

[3]

S. Borkar, R. Cohn, G. Cox, S. Gleason, T. Gross, H. T. Kung, M. Lam, B. Moore, C. Peterson, J. Pieper, L. Rankin, P. S. Tseng, J. Sutton, J. Urbanski, and J. Webb. iwarp: An integrated solution to high-speed parallel computing. In Proceedings of Supercomputing '88, pages 330-339, Orlando, Florida, November 1988. IEEE Computer Society and ACM SIGARCH.

Digital Library

Google Scholar

[4]

G. Brooks, G. Hansen, and S. Simmons. A new approach to debugging optimized code. in Proc. SIG- PLAN'92 Conf. on PLDi, pages 1-11. ACM SIG- PLAN, June 1992.

Digital Library

Google Scholar

[5]

M. Copperman. Debugging optimized code without being misled. Technical Report 92-01, UC Santa Cruz, May 1992.

Digital Library

Google Scholar

[6]

M. Copperman. Personal communication. 1992.

Google Scholar

[7]

D. S. Coutant, S. Meloy, and M. Ruscetta. Doc: A practical approach to source-level debugging of globally optimized code. In Proc. SiGPLAN 1988 Conf. on PLDI, pages 125-134. ACM, June 1988.

Digital Library

Google Scholar

[8]

J. L. Hennessy. Symbolic debugging of optimized code. A CM Trans. on Programming Languages and Systems, 4(3):323 - 344, July 1982.

Digital Library

Google Scholar

[9]

B. W. Kernighan and D. M. Ritchie. The C Programming Language. Prentice-Hall, Inc., Englewood Cliffs, New Jersey, 1978.

Digital Library

Google Scholar

[10]

P. Kessler. Fast breakpoints: Design and implementation, in Proc. A CM SiGPLAN'90 Conf. on PLDL pages 78-84. ACM, June 1990.

Digital Library

Google Scholar

[11]

W. H. Press, B. P. Flannery, S. A Teukolsky, and W. T. Vetterling. Numerical Recipes in C. Cambridge University Press, 1991.

Google Scholar

[12]

J. Uniejewski. Spec benchmark suite: Designed for today's advanced systems. SPEC Newsletter, 1(1), Fall 1989.

Google Scholar

[13]

R. Wahbe. Efficient data breakpoints. In Proc. Fifth Intl. Conf. on Architectural Support for Programruing Languages and Operating Systems (ASPLOS V), pages 200- 212, Boston, October 1992. ACM/IEEE.

Digital Library

Google Scholar

[14]

P. Zellweger. An interactive high-level debugger for control-flow optimized programs. In Proc. of the A CM SiGSOFT/SIGPLAN Software Engineering Symposium on High-Level Debugging, pages 159- 171. ACM, 1983.

Digital Library

Google Scholar

Cited By

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Assaiante CD'Elia DDi Luna GQuerzoni LAamodt TJerger NSwift M(2023)Where Did My Variable Go? Poking Holes in Incomplete Debug InformationProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 210.1145/3575693.3575720(935-947)Online publication date: 27-Jan-2023
https://dl.acm.org/doi/10.1145/3575693.3575720
Chen NComden JLiu ZGandhi AWierman A(2016)Using Predictions in Online OptimizationACM SIGMETRICS Performance Evaluation Review10.1145/2964791.290146444:1(193-206)Online publication date: 14-Jun-2016
https://dl.acm.org/doi/10.1145/2964791.2901464
Gabielkov MRamachandran AChaintreau ALegout A(2016)Social ClicksACM SIGMETRICS Performance Evaluation Review10.1145/2964791.290146244:1(179-192)Online publication date: 14-Jun-2016
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Index Terms

Detection and recovery of endangered variables caused by instruction scheduling
1. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Error handling and recovery
    2. Software verification and validation
      1. Software defect analysis
        Software testing and debugging
  2. Software notations and tools
    1. Compilers

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Detection and recovery of endangered variables caused by instruction scheduling

Instruction scheduling re-orders and interleaves instruction sequences from different source statements. This impacts the task of a symbolic debugger, which attempts to present the user a picture of program execution that matches the source program. At ...
Effective instruction scheduling with limited registers
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Published In

PLDI '93: Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation

August 1993

313 pages

ISBN:0897915984

DOI:10.1145/155090

Editor:
Robert Cartwright
Rice Univ., Houston, TX

ACM SIGPLAN Notices Volume 28, Issue 6
June 1993
313 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/173262
Editor:
Richard Wexelblat
IDA/CSED, Alexandria, VA
Issue’s Table of Contents

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

New York, NY, United States

Publication History

Published: 01 June 1993

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SIGPLAN

PLDI93: ACM SIGPLAN Conference on Programming Languages Design and Implementation

June 21 - 25, 1993

New Mexico, Albuquerque, USA

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Cited By

View all

Assaiante CD'Elia DDi Luna GQuerzoni LAamodt TJerger NSwift M(2023)Where Did My Variable Go? Poking Holes in Incomplete Debug InformationProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 210.1145/3575693.3575720(935-947)Online publication date: 27-Jan-2023
https://dl.acm.org/doi/10.1145/3575693.3575720
Chen NComden JLiu ZGandhi AWierman A(2016)Using Predictions in Online OptimizationACM SIGMETRICS Performance Evaluation Review10.1145/2964791.290146444:1(193-206)Online publication date: 14-Jun-2016
https://dl.acm.org/doi/10.1145/2964791.2901464
Gabielkov MRamachandran AChaintreau ALegout A(2016)Social ClicksACM SIGMETRICS Performance Evaluation Review10.1145/2964791.290146244:1(179-192)Online publication date: 14-Jun-2016
https://dl.acm.org/doi/10.1145/2964791.2901462
Wang WYing LZhang J(2016)The Value of PrivacyACM SIGMETRICS Performance Evaluation Review10.1145/2964791.290146144:1(249-260)Online publication date: 14-Jun-2016
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Perlich CMelville PLiu YŚwirszcz GLawrence RRosset S(2008)Breast cancer identificationACM SIGKDD Explorations Newsletter10.1145/1540276.154028910:2(39-42)Online publication date: 20-Dec-2008
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Detection and recovery of endangered variables caused by instruction scheduling

Effective instruction scheduling with limited registers

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