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

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Integrating Influence Mechanisms into Impact Analysis for Increased Precision

Ben Breech

Lori PollockMike Tegtmeyer

University of Delaware Army Research Lab

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Background: Impact Analysis

• If I change function C, what other functions could be affected (impacted)?

• Uses• Regression testing• Planning changes

A

mainB

C

D

E

G H

F

C

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Background: Challenges• Conservative -- impacts shouldn’t be

missed

• Precision -- impacts should be close as possible to “true” results

• Efficiency -- analysis should be quick

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Background: Impact Analysis Kinds

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Background:Impact Analysis Kinds

SourceCode

Static Analyzer Impacts

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

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ExecuteInstrumented

Program

Post ExecAnalysis

Dynamic Information

Impacts

Input

- 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

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Method A Method B

stmt a1stmt a2…

stmt b1stmt b2…

Statement Level

• Expensive• Precise

Slicing

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Method A Method B

Method Level

• Less expensive• Less precise

Call graph traversals

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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

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Example of Dynamic Impact Analysis

PathImpact, Law and Rothermel, ICSE 03

A

mainB

C

D

E

G H

F

main

A

C

D

F

E

Find Impact of G:

Trace: Main G r A C F C r r D r E r D r r r x

G

(call graph only for demonstration)

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Can we improve results?

• PathImpact is “safe”• Doesn’t miss impacts among exec’d methods

• Purely method level

• What can statement level info add?

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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;}

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Insight: Propagation of Changes

• Change propagates through variables • Change propagates into methods by

parameters/return values• Global variables can propagate change

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Example Revisited

A

mainB

C

D

E

G H

F

main

A

C

D

F

E

Find Impact of G:


G

Assume: No Global Variables in program C has no parameters/return vals

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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

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Influence Graph Example

A

main BC

D

E

G H

F

A

C

G

int G (void)

v

int H (int x)

Hv

void A (struct_type &x)

r

void C (void)r

v, rr

r

r: ref. edgev: val. edge(none): call edge (demo only)

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Conservative Assumptions

Building influence graph• Ignore const • Ref. Parameters always modified• Function pointers edges to all

functions with address taken

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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)

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Example

A

main BC

D

E

G H

F

EC

D

v

v

r

rv, r

r

r


Find Impact of C:

r: ref. edgev: val. edge

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Research Questions

• Is the impact analysis cost reasonable?

• Does the dynamic analysis give more precision than current techniques?

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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

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Timing Results

• Influence Graph - little overhead to build

• Impact Analysis on 9 GB trace ~ 7 mins• PathImpact ~ 5mins• Reasonable time for analysis

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Precision Results

avg min max008.espresso 5.8 (3.8%) 1 8

099.go 1.0 (0.3%) 0 307

130.li 4.9 (4.6%) 2 117

132.ijpeg 0 (0%) 0 0

147.vortex 2.7 (1%) 1 363

164.gzip 1.0 (2%) 1 2

300.twolf 1.6 (2%) 0 3

Space 4.3 (18%) 1 35

• Always subset of PathImpact

• ~ 4% savings

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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

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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

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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?

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

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