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Integrating Influence Mechanisms into Impact Analysis for Increased Precision

Integrating Influence Mechanisms into Impact Analysis for Increased Precision. Ben Breech Lori Pollock. Mike Tegtmeyer. University of Delaware. Army Research Lab. Background: Impact Analysis. G. H. If I change function C, what other functions could be affected (impacted)? Uses

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Integrating Influence Mechanisms into Impact Analysis for Increased Precision

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  1. Integrating Influence Mechanisms into Impact Analysis for Increased Precision Ben Breech Lori Pollock Mike Tegtmeyer University of Delaware Army Research Lab

  2. Background: Impact Analysis G H • If I change function C, what other functions could be affected (impacted)? • Uses • Regression testing • Planning changes F B main C C E A D

  3. Background: Challenges • Conservative -- impacts shouldn’t be missed • Precision -- impacts should be close as possible to “true” results • Efficiency -- analysis should be quick

  4. Background: Impact Analysis Kinds

  5. Background:Impact Analysis Kinds Obtain conservative results • Accounts for all possible inputs and behaviors • Can give very large impact sets Bohner, Arnold 1996, Ryder and Tip, 2001, Turver and Munro, 1994 Source Code Static Analyzer Impacts

  6. Background:Impact Analysis Kinds Execute Instrumented Program Dynamic Information Post Exec Analysis Input Impacts • Not conservative -- results depend on input • Give impacts related to program use Orso et al. 2003, Law and Rothermel, 2003, Breech et al. 2005, Apiwattanapong et al. 2005

  7. Method B Method A stmt a1 stmt a2 … stmt b1 stmt b2 … Background:Impact Analysis Kinds • Expensive • Precise Slicing Statement Level

  8. Method B Method A Background:Impact Analysis Kinds • Less expensive • Less precise Call graph traversals Method Level

  9. Our Approach • Augment method level analysis with some statement level information • Use influence graph to capture how changes propagate • Both static and dynamic analysis • Goal: better results w/out large overhead

  10. Example of Dynamic Impact Analysis PathImpact, Law and Rothermel, ICSE 03 Find Impact of G: G G H F F B main main C C E E A A D D Trace: Main G r A C F C r r D r E r D r r r x (call graph only for demonstration)

  11. Can we improve results? • PathImpact is “safe” • Doesn’t miss impacts among exec’d methods • Purely method level • What can statement level info add?

  12. How do changes propagate? int G (void) { int x, y; …. if (x != 0) y = 10; else y = -10; return y; } int G (void) { int x, y; …. if (x == 0) y = 10; else y = -10; return y; } int G (void) { int x, y; …. if (x == 0) y = 10; else y = -10; return y; }

  13. Insight: Propagation of Changes • Change propagates through variables • Change propagates into methods by parameters/return values • Global variables can propagate change

  14. Example Revisited Find Impact of G: G G H F F B main main C C E E A A D D Trace: Main G r A C F C r r D r E r D r r r x Assume: No Global Variables in program C has no parameters/return vals

  15. Basis of Approach: Influence Graph Formalize ideas in influence graph • Nodes are methods • Edge p  q change can propagate from p to q • 3 Types of edges • Parameters/returns by value • Parameters/returns by reference • Global variables

  16. v v r r v, r r r Influence Graph Example int G (void) int H (int x) H H G G F void C (void) main B C C E A A D void A (struct_type &x) r: ref. edge v: val. edge (none): call edge (demo only)

  17. Conservative Assumptions Building influence graph • Ignore const • Ref. Parameters always modified • Function pointers  edges to all functions with address taken

  18. Dynamic Impact Analysis with the Influence Graph • Generate influence graph statically • Perform impact analysis for function of interest • Intuition: Check influence graph at each call/return to see if change can propagate • Global variables require more book keeping (details in paper)

  19. v v r r v, r r r Example Find Impact of C: H G F main B C E C E A D D Trace: Main G r A C F C r r D r E r D r r r x r: ref. edge v: val. edge

  20. Research Questions • Is the impact analysis cost reasonable? • Does the dynamic analysis give more precision than current techniques?

  21. Methodology • Analyzed 8 medium sized C programs(5,000 - 40,000 LoC) • Created gcc passes to build influence graph (little overhead) • Generated traces 8KB - 9 GB

  22. Timing Results • Influence Graph - little overhead to build • Impact Analysis on 9 GB trace ~ 7 mins • PathImpact ~ 5mins • Reasonable time for analysis

  23. Precision Results • Always subset of PathImpact • ~ 4% savings

  24. Why so little precision gain? • Changes propagated due to parameters/returns (esp. reference) • Conservatively assumed all reference vars were modified • Large percentage of functions with ref. vars • Performed basic analysis to build infl. graph

  25. Better Results?(new work!) • More static program analysis  better influence graph  better precision • Danger: more static analysis, more expensive build influence graph • Analyzed small program by hand • Got 10% gain when using def-use pairs

  26. Summary and Future Work • Can improve method level impact analysis by using some statement level information • Reasonable impact analysis time • Reasonable to spend time building better influence graph?

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