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Effective Slicing Techniques in Computer Sciences

Explore the concept of effective slicing in computer sciences, focusing on dynamic slicing algorithms and fixpoint computation. Understand the challenges and potential of effective slicing for program analysis and semantic extraction.

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Effective Slicing Techniques in Computer Sciences

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  1. Effective Slicing Anne Mulhern Computer Sciences Department University of Wisconsin-Madison Madison, WI USA mulhern@cs.wisc.edu www.cs.wisc.edu/~mulhern

  2. typical ^ Two Correct Dynamic Slices ✓ ✓ Effective Slicing

  3. Union of Slices is Incorrect Effective Slicing

  4. Why is This a Problem? • Given a set of inputs that cause program failure • Want the correct slice for all failures • Given a flag that takes multiple values • Want the correct slice for whenever the flag is set, regardless of its value Effective Slicing

  5. Two Correct Relevant Slices ✓ ✓ Effective Slicing

  6. Union of Relevant Slices is Correct Effective Slicing

  7. We Can Slice Twice • If we take the union of slices as our program and slice again on the same inputs… • we may get a smaller program • Example: the union of relevant slices for inputs 2 and 3… Effective Slicing

  8. Fixpoint Computation ✓ ✓ So long as n in {2,3} choice of n is unimportant Effective Slicing

  9. Effective Slicing • Dynamic slicing algorithms - two arguments • P - the program • σ - the initial state • Effective slicing algorithm - an additional argument • 𝚷 - the nodes to consider when calculating potential dependence • effective(P, σ, ∅ ) = full(P, σ) • effective(P, σ, P) = relevant(P, σ) Effective Slicing

  10. Effective Slicing for Approximation • Potential dependence need only be taken into account when the potential statement is in the union of slices • Choose 𝚷 to be all nodes in the union of execution slices Effective Slicing

  11. Two Correct Effective Slices ✓ ✓ Effective Slicing

  12. Summary • Unions of relevant slices are correct • Take into account potential dependences • Relevant slicing can be used in a fixpoint computation • Semantic information can be extracted from the result • Effective slicing generalizes full and relevant slicing • Possibly potential statements are an explicit parameter • Effective slicing can be used to find an approximation of the fixpoint Effective Slicing

  13. Future Work • Theoretical • How many steps to reach fixpoint? • Practical • How big are unions of relevant slices? • How good an approximation can effective slicing give? • How many dynamic semantic facts can be extracted? • eg., what choices of initial state are irrelevant for this subset? Effective Slicing

  14. Effective Slicing Anne Mulhern Computer Sciences Department University of Wisconsin-Madison Madison, WI USA mulhern@cs.wisc.edu www.cs.wisc.edu/~mulhern

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