Skip to main content
SpringerLink
Log in

Finding Suitable Variability Abstractions for Family-Based Analysis

  • Conference paper
  • First Online:
FM 2016: Formal Methods (FM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9995))

Included in the following conference series:

Abstract

For program families (Software Product Lines), specially designed variability-aware static (dataflow) analyses allow analyzing all variants (products) of the family, simultaneously, in a single run without generating any of the variants explicitly. They are also known as lifted or family-based analyses. The variability-aware analyses may be too costly or even infeasible for families with a large number of variants. In order to make them computationally cheaper, we can apply variability abstractions which aim to tame the combinatorial explosion of the number of variants (configurations) and reduce it to something more tractable. However, the number of possible abstractions is still intractably large to search naively, with most abstractions being too imprecise or too costly.

In this work, we propose a technique to efficiently find suitable variability abstractions from a large family of abstractions for a variability-aware static analysis. The idea is to use a pre-analysis to estimate the impact of variability-specific parts of the program family on the analysis’s precision. Then we use the pre-analysis results to find out when and where the analysis should turn off or on its variability-awareness. We demonstrate the practicality of this approach on several Java benchmarks.

Supported by The Danish Council for Independent Research under a Sapere Aude project, VARIETE.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    is a Galois connection between lattices L and M iff \(\alpha \) and \(\gamma \) are total functions that satisfy: \(\alpha (l) \le _M m \iff l \le _L \gamma (m)\) for all \(l \in L, m \in M\).

References

  1. Apel, S., von Rhein, A., Wendler, P., Größlinger, A., Beyer, D.: Strategies for product-line verification: case studies and experiments. In: 35th International Conference on Software Engineering, ICSE 2013, pp. 482–491 (2013)

    Google Scholar 

  2. Bodden, E., Tolêdo, T., Ribeiro, M., Brabrand, C., Borba, P., Mezini, M.: Spl\({}^{\text{lift}}\): statically analyzing software product lines in minutes instead of years. In: ACM SIGPLAN Conference on PLDI 2013, pp. 355–364 (2013)

    Google Scholar 

  3. Brabrand, C., Ribeiro, M., Tolêdo, T., Winther, J., Borba, P.: Intraprocedural dataflow analysis for software product lines. In: Leavens, G.T., Chiba, S., Tanter, É. (eds.) Transactions on Aspect-Oriented Software Development X. LNCS, vol. 7800, pp. 73–108. Springer, Heidelberg (2013). doi:10.1007/978-3-642-36964-3_3

    Chapter  Google Scholar 

  4. Chen, S., Erwig, M., Walkingshaw, E.: An error-tolerant type system for variational lambda calculus. In: ACM SIGPLAN International Conference on Functional Programming, ICFP 2012, pp. 29–40 (2012)

    Google Scholar 

  5. Classen, A., Cordy, M., Heymans, P., Legay, A., Schobbens, P.-Y.: Model checking software product lines with SNIP. STTT 14(5), 589–612 (2012)

    Article  Google Scholar 

  6. Classen, A., Heymans, P., Schobbens, P.-Y., Legay, A., Raskin, J.-F.: Model checking lots of systems: efficient verification of temporal properties in software product lines. In: Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering, ICSE 2010, vol. 1, pp. 335–344 (2010)

    Google Scholar 

  7. Clements, P., Northrop, L., Lines, S.P.: Practices and Patterns. Addison-Wesley, Reading (2001)

    Google Scholar 

  8. Cousot, P.: The calculational design of a generic abstract interpreter. In: Broy, M., Steinbrüggen, R. (eds.) Calculational System Design. NATO ASI Series. F. IOS Press, Amsterdam (1999)

    Google Scholar 

  9. Cousot, P., Cousot, R., Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints. In: Sethi, R. (ed.) POPL 1977, Los Angeles, California, pp. 238–252, January 1977

    Google Scholar 

  10. Dimovski, A.S.: Program verification using symbolic game semantics. Theor. Comput. Sci. 560, 364–379 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  11. Dimovski, A.S.: Symbolic game semantics for model checking program families. In: Bošnački, D., Wijs, A. (eds.) SPIN 2016. LNCS, vol. 9641, pp. 19–37. Springer, Heidelberg (2016). doi:10.1007/978-3-319-32582-8_2

    Chapter  Google Scholar 

  12. Dimovski, A.S., Al-Sibahi, A.S., Brabrand, C., Wąsowski, A.: Family-based model checking without a family-based model checker. In: Fischer, B., Geldenhuys, J. (eds.) SPIN 2015. LNCS, vol. 9232, pp. 282–299. Springer, Heidelberg (2015). doi:10.1007/978-3-319-23404-5_18

    Chapter  Google Scholar 

  13. Dimovski, A.S., Al-Sibahi, A.S., Brabrand, C., Wasowski, A.: Efficient family-based model checking via variability abstractions. STTT (2016). doi:10.1007/s10009-016-0425-2

    Google Scholar 

  14. Dimovski, A.S., Brabrand, C., Wasowski, A.: Variability abstractions: trading precision for speed in family-based analyses. In: 29th European Conference on Object-Oriented Programming, ECOOP 2015. LIPIcs, vol. 37, pp. 247–270. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2015)

    Google Scholar 

  15. CERN: European Organization for Nuclear Research: The colt project: open source libraries for high performance scientific and technical computing in Java. In: CERN (1999)

    Google Scholar 

  16. Iosif-Lazar, A.F., Al-Sibahi, A.S., Dimovski, A.S., Savolainen, J.E., Sierszecki, K., Wasowski, A.: Experiences from designing and validating a software modernization transformation (E). In: 30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015, pp. 597–607 (2015)

    Google Scholar 

  17. Kästner, C.: Virtual Separation of Concerns: toward Preprocessors 2.0. Ph.D. thesis, University of Magdeburg, Germany, May 2010

    Google Scholar 

  18. Kästner, C., Apel, S., Thüm, T., Saake, G.: Type checking annotation-based product lines. ACM Trans. Softw. Eng. Methodol. 21(3), 14 (2012)

    Article  Google Scholar 

  19. Kästner, C., Giarrusso, P.G., Rendel, T., Erdweg, S., Ostermann, K., Berger, T.: Variability-aware parsing in the presence of lexical macros and conditional compilation. In: Proceedings of the 26th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, OOPSLA 2011, part of SPLASH 2011, pp. 805–824 (2011)

    Google Scholar 

  20. Liang, P., Tripp, O., Naik, M.: Learning minimal abstractions. In: Proceedings of the 38th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL 2011, pp. 31–42 (2011)

    Google Scholar 

  21. Midtgaard, J., Dimovski, A.S., Brabrand, C., Wasowski, A.: Systematic derivation of correct variability-aware program analyses. Sci. Comput. Program. 105, 145–170 (2015)

    Article  Google Scholar 

  22. Nielson, F., Nielson, H.R., Hankin, C.: Principles of Program Analysis. Springer, Secaucus (1999)

    Book  MATH  Google Scholar 

  23. Oh, H., Lee, W., Heo, K., Yang, H., Yi, K.: Selective context-sensitivity guided by impact pre-analysis. In: ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2014, p. 49 (2014)

    Google Scholar 

  24. Hakjoo, O., Lee, W., Heo, K., Yang, H., Yi, K.: Selective x-sensitive analysis guided by impact pre-analysis. ACM Trans. Program. Lang. Syst. 38(2), 6 (2016)

    Google Scholar 

  25. Reps, T., Horwitz, S., Sagiv, M.: Precise interprocedural dataflow analysis via graph reachability. In: Proceedings of the 22nd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL 1995, pp. 49–61 (1995)

    Google Scholar 

  26. Thüm, T., Apel, S., Kästner, C., Schaefer, I., Saake, G.: A classification and survey of analysis strategies for software product lines. ACM Comput. Surv. 47(1), 6 (2014)

    Article  Google Scholar 

  27. Vallée-Rai, R., Co, P., Gagnon, E., Hendren, L., Lam, P., Sundaresan, V.: Soot - a Java bytecode optimization framework. In: Proceedings of the 1999 Conference of the Centre for Advanced Studies on Collaborative Research (CASCON 1999), p. 13. IBM Press (1999)

    Google Scholar 

  28. Zhang, X., Naik, M., Yang, H.: Finding optimum abstractions in parametric dataflow analysis. In: ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2013, pp. 365–376 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. IT University of Copenhagen, Copenhagen, Denmark

    Aleksandar S. Dimovski, Claus Brabrand & Andrzej Wąsowski

Authors
  1. Aleksandar S. Dimovski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Claus Brabrand
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andrzej Wąsowski
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aleksandar S. Dimovski .

Editor information

Editors and Affiliations

  1. Newcastle University, Newcastle upon Tyne, United Kingdom

    John Fitzgerald

  2. US Naval Research Laboratory, Washington, District of Columbia, USA

    Constance Heitmeyer

  3. ISTI-CNR, Pisa, Italy

    Stefania Gnesi

  4. University of Cyprus, Nicosia, Cyprus

    Anna Philippou

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Dimovski, A.S., Brabrand, C., Wąsowski, A. (2016). Finding Suitable Variability Abstractions for Family-Based Analysis. In: Fitzgerald, J., Heitmeyer, C., Gnesi, S., Philippou, A. (eds) FM 2016: Formal Methods. FM 2016. Lecture Notes in Computer Science(), vol 9995. Springer, Cham. https://doi.org/10.1007/978-3-319-48989-6_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-48989-6_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48988-9

  • Online ISBN: 978-3-319-48989-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation