Amorphous Program Slicing Amorphous Program Slicing through Partial Evaluationthrough Partial Evaluation

David Binkley & Kyle SluderDavid Binkley & Kyle SluderLoyola College in MarylandLoyola College in Maryland

4501 N. Charles St.4501 N. Charles St.Baltimore, MD 21210Baltimore, MD 21210

AgendaAgenda

BackgroundBackground

FundamentalsFundamentals

MethodMethod

ResultsResults

Conclusions & Future WorkConclusions & Future Work

BackgroundBackground

Traditional slicingTraditional slicing Projection of program Projection of program

given criteriongiven criterion Criterion: (line #, Criterion: (line #,

{variables}){variables}) Preserves syntaxPreserves syntax

1.1. int foo()int foo()

2.2. {{

3.3. int x, y, z;int x, y, z;

4.4. x = 20;x = 20;

5.5. y = x + 10;y = x + 10;

6.6. z = 30;z = 30;

7.7. return x + y + z;return x + y + z;

8.8. }}

Criterion: (6, {z})

BackgroundBackground

Traditional slicing domainsTraditional slicing domains StaticStatic

Not concerned with program’s inputNot concerned with program’s input DynamicDynamic

Modifies slice based on inputModifies slice based on input

BackgroundBackground

Amorphous slicingAmorphous slicing Not syntax-preserving Not syntax-preserving

(biggest advantage)(biggest advantage) No distinction between No distinction between

static and dynamicstatic and dynamic

1.1. int foo()int foo()

2.2. {{

3.3. int x, y, z;int x, y, z;

4.4. x = 20;x = 20;

5.5. y = x + 10;y = x + 10;

6.6. z = 30;z = 30;

7.7. return x + y + z;return x + y + z;

8.8. }}

1.1. int foo()int foo()

2.2. {{

3.3. int z = 30;int z = 30;

4.4. return z;return z;

5.5. }}

BackgroundBackgroundS

ynta

x P

rese

rvat

ion

Specialized for input

Traditional static slicing Traditional dynamic slicing

Amorphous slicing (N/A)

All 1

No

Yes

BackgroundBackground

Applications of SlicingApplications of Slicing Debugging: original useDebugging: original use Program provingProgram proving RefactoringRefactoring Program/algorithm analysisProgram/algorithm analysis

BackgroundBackground

What is partial evaluation?What is partial evaluation?

ApplicationsApplications OptimizationOptimization Program (pre)compilationProgram (pre)compilation RefactoringRefactoring Program proving/analysisProgram proving/analysis

FundamentalsFundamentals

Based on similarity of partial evaluation Based on similarity of partial evaluation and amorphous slicingand amorphous slicing Foundation (Harman et al.)Foundation (Harman et al.) Application (Silva and Vidal)Application (Silva and Vidal)

Applied to CApplied to C No longer in the realm of functional No longer in the realm of functional

programmingprogramming A lot harder to do successfullyA lot harder to do successfully

MethodMethod

1.1. Pre-processingPre-processing Use TXL to extract Use TXL to extract

variables to global variables to global scopescope

2.2. Partially evaluatePartially evaluate Prepare configuration Prepare configuration

file (provide criterion)file (provide criterion) Run TempoRun Tempo

3.3. SliceSlice Use CodeSurferUse CodeSurfer

4.4. Post-processPost-process Use TXL for cleanupUse TXL for cleanup

ResultsResults

Computation exampleComputation example Program needs to Program needs to

compute statistics on compute statistics on array of integersarray of integers

Program exhibits bug Program exhibits bug in averagein average

ResultsResults

ResultsResults

Traditional slice not helpfulTraditional slice not helpful Syntactic-preservation constraint inhibits efficacySyntactic-preservation constraint inhibits efficacy Only shows what is already known: biggest is not Only shows what is already known: biggest is not

involved in computation of averageinvolved in computation of average

Amorphous slice helpfulAmorphous slice helpful Shows that average is not built correctly: does not rely Shows that average is not built correctly: does not rely

on sum, despite its presence in original programon sum, despite its presence in original program Sum must therefore not be receiving the right valueSum must therefore not be receiving the right value

ResultsResults

Safety slicingSafety slicing Array bounds safetyArray bounds safety Artificially insert assignments to variable Artificially insert assignments to variable

“safe” before array access“safe” before array access Assert safe = T at endAssert safe = T at end

ResultsResults

Conclusions and Future WorkConclusions and Future Work

Amorphous slicing is possible for CAmorphous slicing is possible for C

Partial evaluation is very viable method for Partial evaluation is very viable method for achieving that goalachieving that goal

Need more examples of efficacyNeed more examples of efficacy

Explore relationship between conditioned Explore relationship between conditioned slicing and “static” variables from P.E. slicing and “static” variables from P.E. perspectiveperspective

This work is supported by National Science Founda-tion grant CCR0305330. Kyle Sluder is supported bythe Loyola College in Maryland Hauber Fellowship.