Program Slicing Tools

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Program Slicing Tools

• By
• Soujanya Devineni

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Goal

• The main goal of the project is to compare and
  evaluate four existing program slicing tools
  namely.
• Kamkars slicing tool
• Spyder tool
• WPIS tool
• Unravel tool
• A method for evaluation of the tools.
• Tools evaluated by concentrating on following
• Measuring program/slice ratio for different
  slices.
• Time and space requirements.
• Discussion about restrictions.

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Method

• The method suggested contain 6 steps
• Classifying the tools.
• Verifying a language subset.
• Constructing test programs
• Analyzing limitations.
• Brief discussion of the slicing tools.
• Kamkars Slicing tool
• Primarily implemented to evaluate Kamkars
  algorithms.
• Application area is debugging.
• A dynamic slicing tool.

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Slicing tools

• SPYDER tool
• A debugging tool that assists user in locating
  bugs.
• Performs both static and dynamic slicing.
• Wisconsin Program slicing tool
• Software system that supports on C programs.
• Includes backward slicing, forward slicing and
  chopping
• void main()      int i 1     int sum
  0     while (ilt11)          sum add(sum,
  i)         i add(i, 1)
•      printf("sum d\n", sum)    printf("i
  d\n", i)
• static int add(int a, int b)      return(a
  b)

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Slicing tools

• The Wisconsin tool is a static slicing tool.
• Unravel slicing tool
• A slicing tool evaluates ANCI C code.
• It is a static slicing tool.
• Evaluation is done using the specified method.

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Conclusion

• Regarding slice efficiency
• Dynamic slicers (Kamkars and Spyder) produce
  smaller slices than static slicers (WPIS and
  Unravel).
• Dynamic slices have knowledge of control flow.
• Time requirements
• Dynamic tools (Kamkars) are faster to static
  tools (WPIS).
• Space requirements
• Dynamic slicing is low compared to static
  slicing.
• Overall, we observed that dynamic slicers produce
  smaller and more useful slices than static
  slicers.