Optimizing the SPARK TM Program Slicer

1. Optimizing the SPARKTM Program Slicer Ricky E. Sward and Leemon C. Baird III Dept of Computer Science USAF Academy ricky.sward@usafa.af.mil leemon.baird@usafa.af.mil

2. Overview • Background on program slicing • SPARK program slicer • Glue code • Useful SPARK features • Proving functional equivalence • Optimizations

3. Previous Work • Weiser [1] first defined program slicing • Slicers exist for C and Java • AdaSlicer has been built using ASIS [2] • Program slicing is used in • Reengineering [3] • Program understanding • Testing and debugging

4. Program Slicing Foo D A B E Foo_D C D A B Foo_E A E C

5. Functional Equivalence • Must preserve functionality during slicing • Avoid huge test suites • Prove mathematically that functionality of original procedure is equivalent to functionality of collection of slices • We need some way to “glue” slices back together to prove functional equivalence

6. SPARK Program Slicer Gather_Summary_Info Lowest_Min Num_Students Min_Choice Highest_Max Max_Choice Increment Increment Gather_Summary_Info_Lowest_Min Gather_Summary_Info_Highest_Max Gather_Summary_Info_Increment Increment_Local : Integer := Increment_In; begin Increment_Local := Increment_Local + 1; Increment_Out := Increment_Local; end Gather_Summary_Info_Increment; Increment_Out Increment_In

7. Glue Code Gather_Summary_Info_Glue Increment_Local : Integer := Increment; begin Gather_Summary_Info_Highest_Max( Num_Students, Max_Choice, Highest_Max); Gather_Summary_Info_Lowest_Min( Num_Students, Min_Choice, Lowest_Min); Gather_Summary_Info_Increment( Increment_Local, Increment); end Gather_Summary_Info_Glue; Lowest_Min Num_Students Min_Choice Highest_Max Max_Choice Increment Increment

8. Useful SPARK Features • Dynamic storage allocations not allowed • No pointers or dynamic allocation of memory • Can determine which variables are given values in the procedure for slicing • No aliasing of variables or parameters • Inputs and outputs of procedures are clearly defined

9. Useful SPARK Features • No recursive procedures • Slicing algorithms for recursive procedures is not defined • Build our proof for non-recursive procedures • Limiting statements such as goto... • No tasking... • No exceptions... • No generics...

10. Proving Functional Equivalence P’ is P with any in/out parameter, X, replaced with X_in and X_out. P0 is glue procedure Slices called in arbitrary order. X_local := X when declared in P’. X_local replaces X in P’. X_out := X_local at end of P’. X_local := X when declared in P0. X_local passed to X_in params. X passed to X_out params.

11. Proving Functional Equivalence Theorem: P0 is functionally equivalent to P Proof • P and P’ will return same outputs given same inputs since SPARK does not allow aliasing. • Assume slicing produces correct projection of behavior to produce the output parameter • For P’ and P0 consider the three types of parameters...

12. Proving Functional Equivalence • The “in” parameters are the same in P’ and P0 • Each “out” parameter is changed by only one of the slices, thus the same in P’ and P0 • For “in out” parameters, glue code: • First copies parameter X to a local variable, X_local • X_local is passed as “in” parameter when needed • Original “in out” parameter, X, passed as “out” • Only one of the slices will change X • Thus, P and P0 are functionally equivalent QED

13. Proving Functional Equivalence In English please... • P’ and P0 designed to prevent slices from interfering when called in arbitrary order • Not a problem for “in” or “out” parameters • P0 provides original “in” value as needed for any “in out” parameters • This means it doesn’t matter when a slice changes the value of an “in out” parameter

14. Optimizations • Examine REF and DEF sets for slices • Use copy-in and copy-out only when needed • Much more efficient for arrays and records • Build hash table of changes • Roll back changes between slices

15. Glue Code Gather_Summary_Info_Glue Increment_Local : Integer := Increment; begin Gather_Summary_Info_Highest_Max( Num_Students, Max_Choice, Highest_Max); Gather_Summary_Info_Lowest_Min( Num_Students, Min_Choice, Lowest_Min); Gather_Summary_Info_Increment( Increment_Local, Increment); end Gather_Summary_Info_Glue; Lowest_Min Num_Students Min_Choice Highest_Max Max_Choice Increment Increment Increment is needed only in one slice, so no need to copy in & copy out

16. Proving Functional Equivalence P0 is glue procedure Slices called in arbitrary order. No need to copy in/out parameters. May need to track changes.

17. Proving Functional Equivalence In English please... • P’ and P0 designed to prevent slices from interfering when called in arbitrary order • Not a problem for “in” or “out” parameters • With REF/DEF analysis, determine overlap of slice parameters • Track changes in hash table if needed • This means it doesn’t matter when a slice changes the value of an “in out” parameter

18. Future Work • Possibly slice the SPARK annotations • Rewrite SPARKSlicer in SPARK

19. Conclusions • SPARK features quite useful • Proved functional equivalence • Proof technique may be useful to other transformations • ASIS very useful

20. Questions?

21. References • [1] Weiser, M. Program slicing. IEEE Transactions on Software Engineering, SE-10(4):352-357, July 1984. • [2] Sward, R.E. and Chamillard, A. T. AdaSlicer: A Program Slicer for Ada. Proceedings of the ACM International SIGAda 03 Conference, Dec 2003, San Diego, CA. • [3] The Wisconsin Program-Slicing Tool, Version 1.1. Retrieved June 4, 2003, from www.cs.wisc.edu/wpis/slicing_tool/, 2000.