131016 wcre-matching

How DevelopersSpend their Effort

Zephyrin Soh et al.

Introduction

Context and Example

Data

Effort vs.Complexity

Research Question

Metrics

Matching

Results

Factors AffectingEffort

Additional Files

Bug Severity

Developers’Experience

Conclusion

Towards Understanding How DevelopersSpend their Effort during

Maintenance Activities

Zephyrin Soh, Foutse Khomh, Yann-Gael Gueheneuc,Giuliano Antoniol

Department of Computer and Software EngineeringEcole Polytechnique de Montreal, Quebec, Canada

October 16, 2013

Pattern Trace Identification, Detection, and Enhancement in JavaSOftware Cost-effective Change and Evolution Research Lab


Zephyrin Soh et al.

Introduction

Context and Example

Data


Research Question

Metrics

Matching

Results


Additional Files

Bug Severity


Conclusion

Outline

Introduction

Effort vs. Complexity

Factors Affecting Effort

Conclusion

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Zephyrin Soh et al.

Introduction

Context and Example

Data


Research Question

Metrics

Matching

Results


Additional Files

Bug Severity


Conclusion

IntroductionContext and Example (1/2)

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Eclipse bug #188083

Patch #74156

File: 2LOC : 26 + 18 LOC - 8 LOC


Zephyrin Soh et al.

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Eclipse bug #134884

Patch #94002

File: 2LOC : 20 + 19 LOC - 1 LOC


Zephyrin Soh et al.

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Complexity of the Changes

I Which change is more complex?

vs.

Eclipse bug #134884

Patch #94002

File: 2

LOC : 20

+ 19 LOC

- 1 LOC

Eclipse bug #188083

Patch #74156

File: 2

LOC : 26

+ 18 LOC

- 8 LOC


Zephyrin Soh et al.

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Research Question

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Matching

Results


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Effort Needed to Provide a Patch

Spend a certain effort to:

I Explore the program

I Find relevant program entities

I Understand entities and make changes

1. How to estimate the effort spend to provide a patch?

2. Does a complex patch need more effort?


Zephyrin Soh et al.

Introduction

Context and Example

Data


Research Question

Metrics

Matching

Results


Additional Files

Bug Severity


Conclusion

IntroductionData

Need detailed information

I Developers’ programming activities

Interactions histories⇒ developers’ effort

I Changes made to address the tasksPatches⇒ source code before and afterchanges

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Zephyrin Soh et al.

Introduction

Context and Example

Data


Research Question

Metrics

Matching

Results


Additional Files

Bug Severity


Conclusion

Effort vs. ComplexityResearch Question

Does the complexity of the implementation of atask reflect developers effort?

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Zephyrin Soh et al.

Introduction

Context and Example

Data


Research Question

Metrics

Matching

Results


Additional Files

Bug Severity


Conclusion

Effort vs. ComplexityMetrics

Developers’ effort

I Time Spend: Total duration spent on all files and theircontents

I Cyclomatic complexity: Cyclomatic complexity of theexploration graph

Complexity of the changes

I Entropy: How much the changes are scattered betweenfiles [1]

I Change distance: How much difference between thesource code before the changes and source code after.

[1] A. E. Hassan, Predicting faults using the complexity of code changes, ICSE2009

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Zephyrin Soh et al.

Introduction

Context and Example

Data


Research Question

Metrics

Matching

Results


Additional Files

Bug Severity


Conclusion

Effort vs. ComplexityMatching (1/2)

How do we match interactions and patches?

2,408 Interactions histories 3,395 Patches?

Assumption: An interaction is matched to a patch (i.e., thepatch is the result of the corresponding interaction) if andonly if both are attached to the same bug report, by thesame developer at the same date (date/hour/minutes).

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Zephyrin Soh et al.

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Unbalanced matchings

Developers modify files without interacting with them:

I Changes not requiring much effort, e.g., propagation ofrefactoring

I Interactions are not collected when performing the task


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F6F4

F5F3

F2

F1

F7

F3

F2

F1

F8


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F6F4

F5F3

F2

F1

F7

F3

F2

F1

F8

F7

F6

F5

F9

F2

F3

F1

F4F8


Zephyrin Soh et al.

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Effort vs. ComplexityResults

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Effort vs. complexity of the changes

I 1028 matchings and 217 unbalanced matchings

I Developers do not necessary spend more effort on tasksrequiring more complex changes


Zephyrin Soh et al.

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Bug Severity


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Effort vs. ComplexityResults

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Effort vs. complexity of the changes

I 1028 matchings and 217 unbalanced matchings

I Developers do not necessary spend more effort on tasksrequiring more complex changes

Time (sec.)

Cyclomatic Complexity


Time (sec.)

Entropy

Entropy

Change distance

Change distance

0.16

0.27

0.31

0.33


Zephyrin Soh et al.

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Matching

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Bug Severity


Conclusion

Factors Affecting EffortAdditional Files

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Additional Files

I Exploring files that should not be modified

I Significantly relevant files vs. additional (useful andaccidental) files

I Effort vs. number of additional files: 0.63 (time) and0.82 (cyclomatic complexity)

F4

F1F2

F5F6

F3

F7F9F8

62% 38%


Zephyrin Soh et al.

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Metrics

Matching

Results


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Bug Severity


Conclusion

Factors Affecting EffortBug Severity

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Bug severity

I Bug severity indicates how much a bug can affect theperformance and stability of the system [2]

I The resolution time of severe bugs is greater than theresolution time of less severe bugs [3]

I Developers may spent more effort when fixing severebugs wrt. less severe bugs

[2] Lamkanfi et al., Predicting the severity of a reported bug, MSR 2010[3] Panjer. Predicting eclipse bug lifetimes, MSR 2007


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Bug severity





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Bug severity




15

663

132

218


Zephyrin Soh et al.

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Conclusion

Factors Affecting EffortDevelopers’ Experience (1/2)

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Developers’ Experience

I NB

I NF and NLOC (Overall and relevant)


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I NB


F6F4

F5F3

F2

F1

F7

F2 (5 LOC)

F1 (2 LOC)

Task

T1

NB NF NLOC

0 0 (0) 0 (0)


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I NB


F6F4

F5F3

F2

F1

F7

F2 (5 LOC)

F1 (2 LOC)

Task

T1

T2 (Case 1)

NB NF NLOC

0 0 (0) 0 (0)

1 2 (0) 7 (0)

F6F5

F5

F4

F3

F7F4

F5 F3


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I NB


F6F4

F5F3

F2

F1

F7

F2 (5 LOC)

F1 (2 LOC)

Task

T1

T2 (Case 1)

NB NF NLOC

0 0 (0) 0 (0)

1 2 (0) 7 (0)

F6F5

F5

F4

F3

F7F4

F5 F3

T2 (Case 2) 1 2 (1) 7 (5)

F6F5

F2

F4

F3

F7F4

F2 F3


Zephyrin Soh et al.

Introduction

Context and Example

Data


Research Question

Metrics

Matching

Results


Additional Files

Bug Severity


Conclusion



I Developers experience does not reduce their effortI When a program evolves, developers may increasingly

perform tasks on parts of the program on which theyhave no previous experience

I Consistent result with [4] (#commits) for Mylyn andPDE project⇒ NB and NF can assess developers’ experience

[4] Robbes et al., Using developer interaction data to compare expertisemetrics, MSR 2013

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Conclusion

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Thanks for your attention!

Time (sec.)



Time (sec.)

Entropy

Entropy

Change distance

Change distance

0.16

0.27

0.31

0.33

F4

F1F2

F5F6

F3

F7F9F8

62% 38%

15

663

132

218

F6F4

F5F3

F2

F1

F7

F2 (5 LOC)

F1 (2 LOC)

Task

T1

T2 (Case 1)

NB NF NLOC

0 0 (0) 0 (0)

1 2 (0) 7 (0)

F6F5

F5

F4

F3

F7F4

F5 F3

131016 wcre-matching

Technology