C UES FOR S CENT I NTENSIFICATION IN D EBUGGING Alexandre Perez and - - PowerPoint PPT Presentation

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C UES FOR S CENT I NTENSIFICATION IN D EBUGGING Alexandre Perez and - - PowerPoint PPT Presentation

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C UES FOR S CENT I NTENSIFICATION IN D EBUGGING Alexandre Perez and Rui Abreu Faculty of Engineering University of Porto, Portugal November 4th 2013, International Workshop on Program Debugging F AULT L OCALIZATION Runs mid() { Suspiciousness

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CUES FOR SCENT INTENSIFICATION IN DEBUGGING

Alexandre Perez and Rui Abreu

Faculty of Engineering University of Porto, Portugal

November 4th 2013, International Workshop on Program Debugging

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FAULT LOCALIZATION

2 mid() { int x,y,z,m; read(“Enter 3 numbers:”,x,y,z); m = z; if (y<z) { if (x<y) m = y; else if (x<z) m = y; // ***BUG*** } else { if (x>y) m = y; else if (x>z) m = x; } print(“Middle number is:”,m); }

0.41 0.41 0.41 0.50 0.0 0.58 0.71 0.0 0.0 0.0 0.0 0.0 0.0 0.41

Runs 1 2 3 4 5 6 Suspiciousness

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FAULT LOCALIZATION

3 mid() { int x,y,z,m; read(“Enter 3 numbers:”,x,y,z); m = z; if (y<z) { if (x<y) m = y; else if (x<z) m = y; // ***BUG*** } else { if (x>y) m = y; else if (x>z) m = x; } print(“Middle number is:”,m); }

0.41 0.41 0.41 0.50 0.0 0.58 0.71 0.0 0.0 0.0 0.0 0.0 0.0 0.41

Runs 1 2 3 4 5 6 Suspiciousness

Are Automated Debugging Techniques Actually Helping Programmers?

Chris Parnin and Alessandro Orso

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{chris.parnin|orso}@gatech.edu ABSTRACT

is notoriously difficult and extremely time con- esearchers have therefore invested a co effort in developi second activity, fault understandin the root caus

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INFORMATION FORAGING

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Predator: person debugging the program. Prey: what the predator seeks to know to pinpoint the fault.

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INFORMATION FORAGING

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Proximal cues: runtime behaviors that suggest information relative to the prey. Information scent: perceived likelihood that a cue will potentially lead to the fault. Topology: is the collection of paths through which the programmer can navigate.

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INFORMATION FORAGING

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choice = max ✓information gain cost ◆

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SUNBURST

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SUNBURST

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SUNBURST

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1 1 Project

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SUNBURST

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1 2 1 Project 2 Source Folder

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SUNBURST

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1 2 3 1 Project 2 Source Folder 3 Package

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SUNBURST

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1 2 3 4 1 Project 2 Source Folder 3 Package 4 File

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SUNBURST

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1 2 3 4 5 1 Project 2 Source Folder 3 Package 4 File 5 Class

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SUNBURST

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1 2 3 4 5 6 1 Project 2 Source Folder 3 Package 4 File 5 Class 6 Method

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SUNBURST

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1 2 3 4 5 6 7 1 Project 2 Source Folder 3 Package 4 File 5 Class 6 Method 7 Statement

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SUNBURST

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High Suspiciousness Low Suspiciousness

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SUNBURST

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SUNBURST

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Root Change

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11

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Check it out at www.gzoltar.com

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INFORMATION FORAGING

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choice = max ✓information gain cost ◆

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INFORMATION FORAGING

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choice = max ✓information gain cost ◆

color coding and the hierarchical visualization increase information scent interaction features can reduce the cost

  • f navigation
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USER STUDY

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40 Participants

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USER STUDY

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Students of the Master in Informatics and Computing Engineering at University of Porto

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USER STUDY

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5+ years of Java/JUnit experience

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http://xstream.codehaus.org/

(De)serializes Java objects into XML 17 kLOC, 306 classes Participants were unfamiliar with the application

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454 final List<Object> parameter = new ArrayList<Object>(); 455 if (targetType == null) { 456 parameter.add(targetType); 457 } 458 final List<Object> arrays = new ArrayList<Object>();

com.thoughtworks.xstream.mapper.AnnotationMapper

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454 final List<Object> parameter = new ArrayList<Object>(); 455 if (targetType == null) { 456 parameter.add(targetType); 457 } 458 final List<Object> arrays = new ArrayList<Object>();

== instead of !=

com.thoughtworks.xstream.mapper.AnnotationMapper

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SETUP

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Participants were asked to locate and fix the fault. Metric: time-to-green. Timeout: 30 minutes.

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CONTROL GROUP

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Find and fix the fault without the aid of GZoltar. 7 out of 20 participants completed the task.

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CONTROL GROUP

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Average time: 23.4 minutes*

*Those that did not find the fault were assigned as taking the maximum time (30 minutes)

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EXPERIMENTAL GROUP

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Find and fix the fault with the aid of GZoltar. All participants completed the task.

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EXPERIMENTAL GROUP

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Average time: 7.9 minutes

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FAULT LOCALIZATION

mid() { int x,y,z,m; read(“Enter 3 numbers:”,x,y,z); m = z; if (y<z) { if (x<y) m = y; else if (x<z) m = y; // ***BUG*** } else { if (x>y) m = y; else if (x>z) m = x; } print(“Middle number is:”,m); }

0.41 0.41 0.41 0.50 0.0 0.58 0.71 0.0 0.0 0.0 0.0 0.0 0.0 0.41

Runs 1 2 3 4 5 6 Suspiciousness

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24

FAULT LOCALIZATION

mid() { int x,y,z,m; read(“Enter 3 numbers:”,x,y,z); m = z; if (y<z) { if (x<y) m = y; else if (x<z) m = y; // ***BUG*** } else { if (x>y) m = y; else if (x>z) m = x; } print(“Middle number is:”,m); }

0.41 0.41 0.41 0.50 0.0 0.58 0.71 0.0 0.0 0.0 0.0 0.0 0.0 0.41

Runs 1 2 3 4 5 6 Suspiciousness

INFORMATION FORAGING

Proximal cues: runtime behaviors that suggest information relative to the prey. Information scent: perceived likelihood that a cue will potentially lead to the fault. Topology: is the collection of paths through which the programmer can navigate.

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SLIDE 37

24

SUNBURST

1 2 3 4 5 6 7 1 Project 2 Source Folder 3 Package 4 File 5 Class 6 Method 7 Statement

FAULT LOCALIZATION

mid() { int x,y,z,m; read(“Enter 3 numbers:”,x,y,z); m = z; if (y<z) { if (x<y) m = y; else if (x<z) m = y; // ***BUG*** } else { if (x>y) m = y; else if (x>z) m = x; } print(“Middle number is:”,m); }

0.41 0.41 0.41 0.50 0.0 0.58 0.71 0.0 0.0 0.0 0.0 0.0 0.0 0.41

Runs 1 2 3 4 5 6 Suspiciousness

INFORMATION FORAGING

Proximal cues: runtime behaviors that suggest information relative to the prey. Information scent: perceived likelihood that a cue will potentially lead to the fault. Topology: is the collection of paths through which the programmer can navigate.

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SLIDE 38

24

SUNBURST

1 2 3 4 5 6 7 1 Project 2 Source Folder 3 Package 4 File 5 Class 6 Method 7 Statement

FAULT LOCALIZATION

mid() { int x,y,z,m; read(“Enter 3 numbers:”,x,y,z); m = z; if (y<z) { if (x<y) m = y; else if (x<z) m = y; // ***BUG*** } else { if (x>y) m = y; else if (x>z) m = x; } print(“Middle number is:”,m); }

0.41 0.41 0.41 0.50 0.0 0.58 0.71 0.0 0.0 0.0 0.0 0.0 0.0 0.41

Runs 1 2 3 4 5 6 Suspiciousness

INFORMATION FORAGING

Proximal cues: runtime behaviors that suggest information relative to the prey. Information scent: perceived likelihood that a cue will potentially lead to the fault. Topology: is the collection of paths through which the programmer can navigate.