skip to main content
article

The causes of bloat, the limits of health

Published:21 October 2007Publication History
Skip Abstract Section

Abstract

Applications often have large runtime memory requirements. In some cases, large memory footprint helps accomplish an important functional, performance, or engineering requirement. A large cache,for example, may ameliorate a pernicious performance problem. In general, however, finding a good balance between memory consumption and other requirements is quite challenging. To do so, the development team must distinguish effective from excessive use of memory.

We introduce health signatures to enable these distinctions. Using data from dozens of applications and benchmarks, we show that they provide concise and application-neutral summaries of footprint. We show how to use them to form value judgments about whether a design or implementation choice is good or bad. We show how being independent ofany application eases comparison across disparate implementations. We demonstrate the asymptotic nature of memory health: certain designsare limited in the health they can achieve, no matter how much the data size scales up. Finally, we show how to use health signatures to automatically generate formulas that predict this asymptotic behavior, and show how they enable powerful limit studies on memory health.

References

  1. G. Ammons, T. Ball, and J. R. Larus. Exploiting hardware performance counters with flow and context sensitive profiling. In Programming Language Design and Implementation, pages 85--96, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J. Berdine, C. Calcagno, B. Cook, DDistefano, P. W. O'Hearn, T. Wies, and H. Yang. Shape analysis for composite data structures. Technical Report MSR--TR-2007-13, Microsoft Research, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  3. S. M. Blackburn and et. al. The DaCapo benchmarks: Java benchmarking development and analysis. In OOPSLA '06: Proceedings of the 21st annual ACM SIGPLAN conference on Object-Oriented Programing, Systems, Languages, and Applications, New York, NY, USA, Oct. 2006. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. D. Bond and K. S. McKinley. Bell: Bit-encoding online memory leak detection. In Architectural Support for Programming Languages and Operating Systems, pages 61--72, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. A. B. Brown, A. Keller, and J. L. Hellerstein. A model of configuration complexity and its application to a change management system. In Integrated Management, 2005.Google ScholarGoogle Scholar
  6. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms. MIT Press and McGraw-Hill, second edition, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. P. N. de Souza, R. J. Fateman, J. Moses, and C. Yapp. The Maxima Book, 2004. http://maxima.sourceforge.net.Google ScholarGoogle Scholar
  8. B. Dufour, K. Driesen, L. J. Hendren, and C. Verbrugge. Dynamic metrics for java. In Object-oriented Programming, Systems, Languages, and Applications, pages 149--168, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. GNU Trove: High performance collections for Java. http://trove4j.sourceforge.net.Google ScholarGoogle Scholar
  10. M. J. Harrold, G. Rothermel, R. Wu, and L. Yi. An empirical investigation of program spectra. In SIGPLAN/SIGSOFT Workshop on Program Analysis For Software Tools and Engineering, pages 83--90, Montreal, Canada, June 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. R. Hastings and B. Joynce. Purify-fast detection of memory leaks and access errors. In USENIX Proceedings, pages 125--136, 1992.Google ScholarGoogle Scholar
  12. S. Holzner. Eclipse. O'Reilly Media, Inc., first edition, Apr. 2004.Google ScholarGoogle Scholar
  13. M. Jump and K. S. McKinley. Cork: dynamic memory leak detection for garbage-collected languages. In Symposium on Principles of Programming Languages, pages 31--38, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. M. R. Lyu, editor. Handbook of Software Reliability Engineering, chapter 9 (Orthogonal Defect Classification). IEEE Computer Society Press, 1995.Google ScholarGoogle Scholar
  15. N. Mitchell. The runtime structure of object ownership. In The European Conference on Object-Oriented Programming, volume 4067 of Lecture Notes in Computer Science, pages 74--98. Springer-Verlag, July 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. N. Mitchell and G. Sevitsky. Leakbot: An automated and lightweight tool for diagnosing memory leaks in large Java applications. In The European Conference on Object-Oriented Programming, volume 2743 of Lecture Notes in Computer Science, pages 351--377. Springer-Verlag, July 2003.Google ScholarGoogle ScholarCross RefCross Ref
  17. N. Mitchell, G. Sevitsky, P. Kumanan, and E. Schonberg. Data structure health. In International Workshop on Dynamic Analysis, Minneapolis, Minnesota, United States, May 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. N. Mitchell, G. Sevitsky, and H. Srinivasan. Modeling runtime behavior in framework-based applications. In The European Conference on Object-Oriented Programming, volume 4067 of Lecture Notes in Computer Science, pages 429--451. Springer-Verlag, July 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. S. Pheng and C. Verbrugge. Dynamic data structure analysis for java programs. In International Conference on Program Comprehension, June 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. D. Rayside, L. Mendel, and D. Jackson. A dynamic analysis for revealing object ownership and sharing. In Workshop on Dynamic Analysis, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. R. Shaham, E. K. Kolodner, and M. Sagiv. Automatic removal of array memory leaks in java. In Computational Complexity, pages 50--66, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Java 2 Platform, Enterprise Edition. http://java.sun.com/j2ee.Google ScholarGoogle Scholar
  23. Quest Software. JProbe® Memory Debugger. http://www.quest.com/jprobe, 2005.Google ScholarGoogle Scholar
  24. SPEC Corporation. The SPEC JVM Client98 benchmark suite. http://www.spec.org/osg/jvm98, 1998.Google ScholarGoogle Scholar
  25. Yourkit LLC. Yourkit profiler. http://www.yourkit.com.Google ScholarGoogle Scholar
  26. T. Xie and D. Notkin. Checking inside the black box: Regression testing based on value spectra differences. In International Conference on Software Maintenance, pages 28--37, Chicago, Illinois, Sept. 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. T. Yang, M. Hertz, ED. Berger, S. F. Kaplan, and J. E. B. Moss. Automatic heap sizing: Taking real memory into account. In International Symposium on Memory Management, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. The causes of bloat, the limits of health

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in

        Full Access

        • Published in

          cover image ACM SIGPLAN Notices
          ACM SIGPLAN Notices  Volume 42, Issue 10
          Proceedings of the 2007 OOPSLA conference
          October 2007
          686 pages
          ISSN:0362-1340
          EISSN:1558-1160
          DOI:10.1145/1297105
          Issue’s Table of Contents
          • cover image ACM Conferences
            OOPSLA '07: Proceedings of the 22nd annual ACM SIGPLAN conference on Object-oriented programming systems, languages and applications
            October 2007
            728 pages
            ISBN:9781595937865
            DOI:10.1145/1297027

          Copyright © 2007 ACM

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 21 October 2007

          Check for updates

          Qualifiers

          • article

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader
        About Cookies On This Site

        We use cookies to ensure that we give you the best experience on our website.

        Learn more

        Got it!