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From Concrete Examples to Heap Manipulating Programs

  • Subhajit Roy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7935)

Abstract

Data-structure manipulation is not just a perplexing ordeal for newbies, but also a tedious errand for seasoned programmers. Even after a programmer gets the "hang of things", programming complex pointer manipulations (like reversing a linked list) still makes one reach for a notebook to draw some box-and-arrow diagrams to work out the low-level pointer jugglery. These diagrams are, not surprisingly, used as a basic tool to introduce heap manipulations in introductory programming courses.

We propose a synthesis technology to automatically create programs that manipulate heap data-structures from such diagrams. The programmer is needed to provide a set of concrete examples of her high-level strategy for the low-level manipulations to be discharged automatically. We plan the synthesis task as a sequence of "fast" stages, making it usable in an integrated development environment. We envisage that such a tool will be useful to programmers as a code-assist comfortably tucked away in their favorite integrated development environment.

Keywords

Recursive Call Program Point Recursive Program Tree Traversal Candidate Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Singh, R., Solar-Lezama, A.: Synthesizing data structure manipulations from storyboards. In: ESEC/FSE 2011, pp. 289–299. ACM, New York (2011)Google Scholar
  2. 2.
    Singh, R., Solar-Lezama, A.: SPT: Storyboard programming tool. In: Madhusudan, P., Seshia, S.A. (eds.) CAV 2012. LNCS, vol. 7358, pp. 738–743. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Solar Lezama, A.: Program Synthesis By Sketching. PhD thesis, EECS Department, University of California, Berkeley (December 2008)Google Scholar
  4. 4.
    Solar-Lezama, A.: The sketching approach to program synthesis. In: Hu, Z. (ed.) APLAS 2009. LNCS, vol. 5904, pp. 4–13. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    De Moura, L., Bjørner, N.: Z3: an efficient SMT solver. In: Ramakrishnan, C.R., Rehof, J. (eds.) TACAS 2008. LNCS, vol. 4963, pp. 337–340. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  6. 6.
    Gulwani, S.: Automating string processing in spreadsheets using input-output examples. In: POPL 2011, pp. 317–330. ACM, New York (2011)Google Scholar
  7. 7.
    Gulwani, S., Harris, W.R., Singh, R.: Spreadsheet data manipulation using examples. Communications of the ACM (2012)Google Scholar
  8. 8.
    Harris, W.R., Gulwani, S.: Spreadsheet table transformations from examples. In: PLDI 2011, pp. 317–328. ACM, New York (2011)Google Scholar
  9. 9.
    Singh, R., Gulwani, S.: Learning semantic string transformations from examples. Proc. VLDB Endow. 5(8), 740–751 (2012)Google Scholar
  10. 10.
    Biermann, A.W., Baum, R.I., Petry, F.E.: Speeding up the synthesis of programs from traces. IEEE Trans. Comput. 24(2), 122–136 (1975)zbMATHCrossRefGoogle Scholar
  11. 11.
    Cypher, A., Halbert, D.C., Kurlander, D., Lieberman, H., Maulsby, D., Myers, B.A., Turransky, A.: Watch what I do: programming by demonstration. MIT Press, Cambridge (1993)Google Scholar
  12. 12.
    Lau, T., Domingos, P., Weld, D.S.: Learning programs from traces using version space algebra. In: K-CAP 2003, pp. 36–43. ACM, New York (2003)Google Scholar
  13. 13.
    Solar-Lezama, A., Rabbah, R., Bodík, R., Ebcioğlu, K.: Programming by sketching for bit-streaming programs. In: PLDI 2005, pp. 281–294. ACM, New York (2005)Google Scholar
  14. 14.
    Solar-Lezama, A., Tancau, L., Bodik, R., Seshia, S., Saraswat, V.: Combinatorial sketching for finite programs. In: ASPLOS-XII, pp. 404–415. ACM, New York (2006)CrossRefGoogle Scholar
  15. 15.
    Gulwani, S., Jha, S., Tiwari, A., Venkatesan, R.: Synthesis of loop-free programs. In: PLDI 2011, pp. 62–73. ACM, New York (2011)Google Scholar
  16. 16.
    Jha, S., Gulwani, S., Seshia, S.A., Tiwari, A.: Oracle-guided component-based program synthesis. In: ICSE 2010, pp. 215–224. ACM, New York (2010)Google Scholar
  17. 17.
    Srivastava, S., Gulwani, S., Foster, J.S.: From program verification to program synthesis. In: POPL 2010, pp. 313–326. ACM, New York (2010)Google Scholar
  18. 18.
    Armando, A., Smaill, A., Green, I.: Automatic synthesis of recursive programs: The proof-planning paradigm. Automated Software Engg. 6(4), 329–356 (1999)CrossRefGoogle Scholar
  19. 19.
    Banerjee, D.: A methodology for synthesis of recursive functional programs. ACM Trans. Program. Lang. Syst. 9(3), 441–462 (1987)zbMATHCrossRefGoogle Scholar
  20. 20.
    Sen, K., Marinov, D., Agha, G.: CUTE: a concolic unit testing engine for C. In: ESEC/FSE-13, pp. 263–272. ACM, New York (2005)CrossRefGoogle Scholar
  21. 21.
    Bansal, S., Aiken, A.: Automatic generation of peephole superoptimizers. In: ASPLOS-XII, pp. 394–403. ACM, New York (2006)CrossRefGoogle Scholar
  22. 22.
    Bansal, S., Aiken, A.: Binary translation using peephole superoptimizers. In: OSDI 2008, pp. 177–192. USENIX Association, Berkeley (2008)Google Scholar
  23. 23.
    Massalin, H.: Superoptimizer: a look at the smallest program. In: ASPLOS-II, pp. 122–126. IEEE Computer Society Press, Los Alamitos (1987)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Subhajit Roy
    • 1
  1. 1.Computer Science and Engineering DepartmentIndian Institute of Technology KanpurIndia

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