Studying the impact of Social Structures on Software Quality

Studying the Impact of Social
Structures on Software Quality
Nicolas Bettenburg and Ahmed E. Hassan
Queen’s University, Kingston, Canada

1

“If software developers
were angels, debugging
would be unnecessary!”
(in ‘Why programs fail’, Elsevier 2009)

James Larus
Microsoft Research

2

Software errors cost
companies millions of dollars
each year!

3

Where will the errors be?

4

Measure the
source code...
complexity
cohesion
coupling
churn
...
bugs

5

...and create a Prediction Model

6

New Source Code

Measurements

Risk of Bugs

7

We can also use a
prediction model to
understand factors!
We can look inside the
Box and study the model!

vs
8
8

In this work:
SOCIAL
STRUCTURES

9

300,000 Bug Reports (BugZilla)

Linked through
Change-Log Analysis

224,643 Transactions (CVS)

11

Measure Measure
Discussion Post-Release
Metrics Bugs

6 months 6 months
time
Eclipse 3.0

12

Discussion Social
CONTENT STRUCTURES

4 Dimensions
of Measures

Measures of Communication
WORKFLOW DYNAMICS

13

Bug 137808
Summary: Exceptions from createFromString lock-up the editor
Product: [Modeling] EMF Reporter: Patrick Sodre <psodre@gmail.com>
Component: Core Assignee: Marcelo Paternostro <marcelop@ca.ibm.com>

Metadata
Status: VERIFIED FIXED QA Contact:
Severity: normal
Priority: P3 CC: merks@ca.ibm.com
Version: 2.2
Target Milestone: ---
Hardware: PC
OS: Windows XP
Whiteboard:

Opened: 2006-04-20 14:25 -
Description:
0400

As discussed on the newsgroup under the Thread with the same name I am opening
this bug entry. Here is a history of the thread.

-- From Ed Merks

Patrick,

The value is checked before it's applied and can't be applied until it's valid.
But this BigDecimal cases behaves oddly because the exception thrown by

new BigDecimal("badvalue")
Source Code
has a null message and the property editor relies on returning a non-null
message string to indicate there is an error.

Please open a bugzilla which I'll fix like this:

### Eclipse Workspace Patch 1.0
#P org.eclipse.emf.edit.ui
Index: src/org/eclipse/emf/edit/ui/provider/PropertyDescriptor.java
===================================================================
RCS file:
/cvsroot/tools/org.eclipse.emf/plugins/org.eclipse.emf.edit.ui/src/org/eclipse/emf/edit/ui/provider/PropertyDescriptor.java,v
retrieving revision 1.10
diff -u -r1.10 PropertyDescriptor.java
--- src/org/eclipse/emf/edit/ui/provider/PropertyDescriptor.java 21 Mar 2006
16:42:30 -0000 1.10
+++ src/org/eclipse/emf/edit/ui/provider/PropertyDescriptor.java 20 Apr 2006

11:59:10 -0000
@@ -162,7 +162,8 @@
}
catch (Exception exception)
{
- return exception.getMessage();
+ String message = exception.getMessage();
+ return message == null ? exception.toString() : message;
}
}
Diagnostic diagnostic =
Diagnostician.INSTANCE.validate(EDataTypeCellEditor.this.eDataType, value);

Patrick Sodre wrote:
Hi,
It seems that if the user inputs an invalid parameter that gets created from
"createFromString" the Editor locks-up until the user explicitly calls "restore
Default Value".
Is this the expected behavior or could something better be done? For
instance if an exception is thrown restore the value back to what it was before
Patch
after displaying a pop-up error message.
I understand that for DataTypes defined by the user he/she should take care
of catching the exceptions but for the default ones like BigInteger/BigDecimal
I think the EMF runtime could do some of the grunt work...
If you think this is something worth pursuing I could post an entry in
Bugzilla.
Stack Trace
Regards,
Patrick Sodre

Below is the stack trace that I got from the Editor...

java.lang.NumberFormatException
at java.math.BigDecimal.<init>(BigDecimal.java:368)
at
org.eclipse.emf.ecore.impl.EcoreFactoryImpl.createEBigDecimalFromString(EcoreFactoryImpl.java:559)
at
org.eclipse.emf.ecore.impl.EcoreFactoryImpl.createFromString(EcoreFactoryImpl.java:116)
at
org.eclipse.emf.edit.ui.provider.PropertyDescriptor$EDataTypeCellEditor.doGetValue(PropertyDescriptor.java:183)
at org.eclipse.jface.viewers.CellEditor.getValue(CellEditor.java:449)
at
org.eclipse.ui.views.properties.PropertySheetEntry.applyEditorValue(PropertySheetEntry.java:135)
at
org.eclipse.ui.views.properties.PropertySheetViewer.applyEditorValue(PropertySheetViewer.java:249)
at

------- Comment #1 From Ed Merks 2006-04-20 15:09:23 -0400 -------

The fix has been committed to CVS. Thanks for reporting this problem.

Discussion Social
CONTENT STRUCTURES

4 Dimensions
of Measures

WORKFLOW DYNAMICS

16

Bug 137808

# PARTICIPANTS IN
Severity: normal
Version: 2.2

DISCUSSION
Hardware: PC
OS: Windows XP
Whiteboard:

Opened: 2006-04-20 14:25 -
Description:
0400


-- From Ed Merks

Patrick,






ROLE OF
===================================================================
RCS file:

PARTICIPANTS
16:42:30 -0000 1.10
11:59:10 -0000
@@ -162,7 +162,8 @@
}
{
}
}

REPUTATION

Hi,
Default Value".
Bugzilla.

CENTRALITY
Regards,
Patrick Sodre


at
at
at
at
at
at


The fix has been committed to CVS. Thanks for reporting this problem. 17

Discussion Social
CONTENT STRUCTURES

4 Dimensions
of Measures

WORKFLOW DYNAMICS

18

Bug 137808
Severity: normal
Version: 2.2
Hardware: PC
OS: Windows XP
Whiteboard:

Opened: 2006-04-20 14:25 -

# MESSAGES
Description:
0400


-- From Ed Merks

Patrick,




MESSAGE


LENGTH
===================================================================
RCS file:
16:42:30 -0000 1.10
11:59:10 -0000
@@ -162,7 +162,8 @@
}
{
}

REPLY TIME
}

Hi,
Default Value".
Bugzilla.

INTERESTINGNESS
Regards,
Patrick Sodre


at
at
at
at
at
at



Bug 137808
Severity: normal
Version: 2.2
Hardware: PC
OS: Windows XP
Whiteboard:

Opened: 2006-04-20 14:25 -
Description:
0400


-- From Ed Merks
# MESSAGES
Patrick,





===================================================================
MESSAGE
LENGTH
RCS file:
16:42:30 -0000 1.10
11:59:10 -0000
@@ -162,7 +162,8 @@
}
{
}
}

REPLY TIME

Hi,
Default Value".
Bugzilla.

Regards,
Patrick Sodre


INTERESTINGNESS
at
at
at
at
at
at



Bug 137808
Severity: normal
Version: 2.2
Hardware: PC
OS: Windows XP
Whiteboard:

Opened: 2006-04-20 14:25 -

# MESSAGES
Description:
0400


-- From Ed Merks

Patrick,




MESSAGE


LENGTH
===================================================================
RCS file:
16:42:30 -0000 1.10
11:59:10 -0000
@@ -162,7 +162,8 @@
}
{
}

REPLY TIME
}

Hi,
Default Value".
Bugzilla.

INTERESTINGNESS
Regards,
Patrick Sodre


at
at
at
at
at
at



Discussion Social
CONTENT STRUCTURES

4 Dimensions
of Measures

WORKFLOW DYNAMICS

23

2.3 Life Cycle of Bug Reports

FIXED

WORKSFORME

WONTFIX

INVALID
UNCONFIRMED
DUPLICATE

NEW / REOPEN ASSIGNED RESOLVED VERIFIED

CLOSED

24

REGRESSION MODEL

the amount of post-release defects into relation of our pre-
release measures. The complete linear regression model has
the form

Def ects = αi · ContentM easurei
i

+ βj · StructuralM easurej
j

+ γk · ComDynM easurek
k

+ δl · W orkf lowM easurel +
l

Based on this model, we will investigate the statistical
relationships between the social interaction measures, which
are represented by the regression variables in the model, and
post release defects, represented by the dependent variable 25

REGRESSION MODEL

Dependentamount of post-release defects into relation of our pre-
the Variable
(what is predicted)
the form

i

j

k

l


REGRESSION MODEL

Regression
the Variable Coefﬁcients
(what is predicted)
the form

i

j

k

l


REGRESSION MODEL

Regression
Independent
Variable
the Coefﬁcients
(what is predicted) Variables
the form

i

j

k

l


APPROACH
Hierarchical Analysis
Successfully used in the past! (Cataldo, Mockus)

Goal: Investigate the effect of each
variable on the model.

(1) Eliminate variables with high correlation.

(2) Build linear model step-by-step, each time
adding new independent variables.

(3) At each step, evaluate how well the set of
independent variables explains the data.
26

APPROACH

:0.

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63.(. ;;; ;;; ;;

63.( ;;; ;; ;;; ;;;

,./39. ;;; ;;; ;;; ;;;

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(!)8 ;;; ;;; ;;; ;;; ;;; ;;; ;;;
!##
)(0-.(1 ; ;;; ;;; ;;; ;;; ;;; ;;; ;;;
=
=
(+).,) ; ;;; ;;; ;;; ;;; ;;; ;; ;; ;;;
!#

==
(6.7) ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;;

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1,0-.) ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;;

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/01-2) ;;; ;;; ; ; ;;; ;;; ;;; ;; ; ;

(/01-2 ;;; ;; ;;; ;;; ;;; ;;; ;;; ;;;

()-*! ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ; ;;; ;;;

()*+,-. ;;; ;;; ;; ; ;;; ;; ;;; ;;; ;;; ; ;;;

$%' ;;; ;;; ;;; ;;; ;;; ; ; ;;; ;;;

:0. :0 4(1. 4(1 63.(. 63.( ,./39. ,./39 (!)8 )(0-.(1 (+).,) (6.7) (/0,1 (34(5 1,0-.) (1,0-. /01-2) (/01-2 ()-*! ()*+,-. $%'
!
27

APPROACH

:0.

:0 ;;;

4(1. ;;; ;;;

4(1 ;;; ;;; ;;;

63.(. ;;; ;;; ;;

63.( ;;; ;; ;;; ;;;

,./39.

,./39 ;;
;;;

;;;
;;;

;;; ;;;
;;;

;;;
;;;

;;; ;;;
Correlogram shows
(!)8

)(0-.(1 ;
;;;

;;;
;;; ;;;

;;;
;;;

;;;
;;;

;;;
;;;

;;;
;;;

;;; ;;;
correlation “hotspots” !##
=
=
(+).,) ; ;;; ;;; ;;; ;;; ;;; ;; ;; ;;;
!#

==
(6.7) ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;;

(/0,1 ; ;; ;;; ;;; ;;; ;;; ;;; ;;; ;;;

(34(5 ; ;;; ;;; ;;; ;;; ;;; ;; ;;; ; ;;; ;;; ;;; ;;;

1,0-.) ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;;

(1,0-. ; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;;

/01-2) ;;; ;;; ; ; ;;; ;;; ;;; ;; ; ;

(/01-2 ;;; ;; ;;; ;;; ;;; ;;; ;;; ;;;

()-*! ;;; ;;; ;;; ;;; ;;; ;;; ;;; ;;; ; ;;; ;;;

()*+,-. ;;; ;;; ;; ; ;;; ;; ;;; ;;; ;;; ; ;;;

$%' ;;; ;;; ;;; ;;; ;;; ; ; ;;; ;;;

:0. :0 4(1. 4(1 63.(. 63.( ,./39. ,./39 (!)8 )(0-.(1 (+).,) (6.7) (/0,1 (34(5 1,0-.) (1,0-. /01-2) (/01-2 ()-*! ()*+,-. $%'
!
27

/01-2) ;;; ;;; ; ; ;;; ;;; ;;; ;; ; ;

(/01-2

()-*! ;;;
;;;

;;; ;;;APPROACH
;; ;;;

;;;
;;;

;;;
;;;

;;;
;;;

;;;
;;;

;;; ;
;;;

;;; ;;;

()*+,-. ;;; ;;; ;; ; ;;; ;; ;;; ;;; ;;; ; ;;;

$%' ;;; ;;; ;;; ;;; ;;; ; ; ;;; ;;;

:0. :0 4(1. (1) Eliminate variables with high correlation.
4(1 63.(. 63.( ,./39. ,./39 (!)8 )(0-.(1 (+).,)
!
(6.7) (/0,1 (34(5 1,0-.) (1,0-. /01-2) (/01-2 ()-*! ()*+,-

igure 1. Pairwise correlations of social interaction measures with levels * p0.05, ** p0.01, *** p0.001. Strength of correlatio
olour intensities; negative correlations are marked with a dashed outline.

Variance Inflation Factor model that have a variance inflation factor g
log(Yi ) Model 1 Model 2 Model 3 (1) Build analysis with all
We start our model with a regression mode
NSOURCE
NSCOM
3.38
3.34
3.38
3.34
3.40
3.36 independent variables
all our variables. The variance inflation fa
NPATCH 3.94 3.88 3.90 model are presented in Table II, Model 1. W
PATCHS 3.84 3.82 3.84 variables that have a variance inflation facto
10. Measure VIF of each
(2) We remove the highest one (NMSG) from
NTRACE 4.62 4.60 4.57
TRACES 4.78 4.75 4.70
NLINK 2.24 2.22 1.90 model and recompute the variance inflation f
independent variable
NDEVS 9.32 9.27 1.91 reduced set of variables. The resulting mode
NUSERS 4.55 4.54 2.30
SNACENT 10.66 10.65 — Table II) contains only one more variable w
NMSG
REPLY
11.63
1.17
—
1.17
—
1.17
(3) Remove variable remove the regre
factor larger than 10. We with
(SNACENT) from the model and recomput
factors. highest VIF
REPLYE 2.04 1.91 1.90
DLEN 4.21 1.91 1.87 In the resulting model (Model 3 in
DLENE 4.65 1.98 1.96 variables have an inflation factor larger than 5
INT 2.82 2.82 2.60 our analysis of multicollinearity.
INTE 1.71 1.71 1.71
WA
WAE
2.26
2.08
1.99
2.06
1.96
2.02
Repeat until Analysis Design
C. Hierarchical all VIF below
threshold (t=10)
After having determined the reduced set
Table II variables with low multicollinearity, we pro
S TEP - WISE ANALYSIS OF MULTICOLLINEARITY. 28

APPROACH
(2) Build linear models step-by-step

log(Yi ) MB M1 M2 M3 M4 M5
CHURN 4.996 *** 4.631 *** 4.658 *** 5.303 *** 3.688 *** 4.470 ***
NSOURCE 1.694 *** 1.698 *** 1.772 *** 1.769 *** 1.667 ***
NTRACE 0.79 0.768 0.864 0.881 1.115
NPATCH 0.209 * 0.210 * 0.284 + 0.231 * 0.291
NSCOM 1.218 1.194 1.246 1.208 1.244
PATCHS
TRACES
12.607
1.016
* 12.626
1.012
Baseline Model:
* 11.200
*
1.004
* 12.736
0.989
18.207
0.975
**

Code Churn
NLINK 1.764 *** 1.613 ** 1.600
** ** 1.666 1.596 +
NPART 2.481 2.888 4.480 4.542
NDEVS 0.475 0.582 0.385 0.274
NUSERS
REPLY
0.749
(Ball, Naggapan)
0.803
1.019
0.692
0.986
0.792
0.982
REPLYE 0.117 *** 0.082 *** 0.044 ***
DLEN 0.936 0.898 * 0.876 +
DLENE 2.499 1.251 2.044
INT 0.829 ** 0.821 ** 0.963
INTE 1.109 1.013 1.306
WA 1.432 *** 1.224 +
WAE 2.718 * 2.169
CON1-3 Fig. 2 ***
χ2 559.01 *** 698.5 *** 700.15 731.5 *** 752.3 *** 1055.19 ***
Dev. Expl. 10.71% 13.38 % 13.41 % 14.02 % 14.41 % 26.07 %
∆χ2 139.48 1.652 31.357 20.28 302.87
*** p0.001, ** p0.01, * p0.05, + p 0.1
29

APPROACH

CHURN 4.996 *** 4.631 *** 4.658 *** 5.303 *** 3.688 *** 4.470 ***
NSOURCE 1.694 *** 1.698 *** 1.772 *** 1.769 *** 1.667 ***
NTRACE 0.79 0.768 0.864 0.881 1.115
NPATCH 0.209 * 0.210 * 0.284 + 0.231 * 0.291
NSCOM
PATCHS
1.218
12.607 *
1.194
12.626
Adding ﬁrst dimension
* *
1.246
11.200
* **
1.208
12.736
1.244
18.207

** Discussion Content
TRACES 1.016 1.012 1.004 0.989 0.975
NLINK 1.764 *** 1.613 ** 1.600
** + 1.666 1.596
NPART 2.481 2.888 4.480 4.542
NDEVS 0.475 0.582 0.385 0.274
NUSERS 0.749 0.803 0.692 0.792
REPLY
REPLYE Increase in ***
explanatory power
1.019
0.117 ***
0.986
0.082
***
0.982
0.044
DLEN 0.936 * +0.898 0.876
DLENE
INT
statistically signiﬁcant
2.499
0.829
** **
1.251
0.821
2.044
0.963
INTE 1.109 1.013 1.306
WA 1.432 *** 1.224 +
WAE 2.718 * 2.169
CON1-3 Fig. 2 ***
χ2 559.01 *** 698.5 *** 700.15 731.5 *** 752.3 *** 1055.19 ***
Dev. Expl. 10.71% 13.38 % 13.41 % 14.02 % 14.41 % 26.07 %
∆χ2 139.48 1.652 31.357 20.28 302.87
*** p0.001, ** p0.01, * p0.05, + p 0.1
30

APPROACH

CHURN 4.996 *** 4.631 *** 4.658 *** 5.303 *** 3.688 *** 4.470 ***
NSOURCE
NTRACE
1.694
0.79
*** 1.698
0.768
*** 1.772
0.864 Adding second
*** 1.769
0.881
*** 1.667
1.115
***

NPATCH 0.209 * 0.210 * 0.284 + 0.231
* 0.291
NSCOM
PATCHS
1.218
12.607 *
1.194
12.626 *
1.246
11.200 *
dimension **
1.208
12.736
*
1.244
18.207
TRACES
NLINK
1.016
1.764 ***
1.012
1.613 **
1.004
1.600 Discussion Content
**
0.989
1.666
** +
0.975
1.596
NPART 2.481 2.888 4.480 4.542
NDEVS 0.475 0.582 0.385 0.274
NUSERS 0.749 0.803 0.692 0.792
REPLY
REPLYE
1.019
0.117 Increase in ***
***
0.986
0.082
***
0.982
0.044
DLEN 0.936 0.898
* + 0.876
DLENE
INT
2.499
0.829
explanatory power:
**
1.251
0.821
**
2.044
0.963
INTE
WA
1.109
not statistically+
1.013
1.432
***
1.306
1.224
WAE 2.718
* 2.169
CON1-3
χ2 559.01 *** 698.5 *** 700.15 731.5 ***
signiﬁcant! ***
752.3 *** 1055.19 ***
Fig. 2

Dev. Expl. 10.71% 13.38 % 13.41 % 14.02 % 14.41 % 26.07 %
∆χ2 139.48 1.652 31.357 20.28 302.87
*** p0.001, ** p0.01, * p0.05, + p 0.1
31

APPROACH

CHURN 4.996 *** 4.631 *** 4.658 *** 5.303 *** 3.688 *** 4.470 ***
NSOURCE
NTRACE
1.694
0.79
*** 1.698
0.768
*** 1.772
0.864
*** 1.769
0.881 Adding
*** 1.667
1.115
***

0.209 0.210 0.284 0.231
third **
NPATCH * * + * 0.291
NSCOM 1.218 1.194 1.246 1.208 1.244
PATCHS 12.607 * 12.626 * 11.200 * 12.736 * 18.207
TRACES
NLINK
1.016
1.764 ***
1.012
1.613 **
1.004
1.600 ** dimension
0.989
1.666 ** +
0.975
1.596
NPART 2.481 2.888 4.480 4.542
NDEVS 0.475 0.582 0.385 0.274
NUSERS 0.749 0.803 0.692 0.792
REPLY
REPLYE
1.019
0.117 ***
0.986
0.082Increase in
***
0.982
0.044
***

explanatory
DLEN 0.936 0.898 * + 0.876
DLENE 2.499 1.251 2.044
INT 0.829 ** 0.821 ** 0.963
INTE
WA
1.109 1.013
1.432 power +
***
1.306
1.224
WAE
CON1-3
2.718
signiﬁcant!
* 2.169
Fig. 2
***
χ2 559.01 *** 698.5 *** 700.15 731.5 *** 752.3 *** 1055.19 ***
Dev. Expl. 10.71% 13.38 % 13.41 % 14.02 % 14.41 % 26.07 %
∆χ2 139.48 1.652 31.357 20.28 302.87
*** p0.001, ** p0.01, * p0.05, + p 0.1
32

APPROACH

CHURN 4.996 *** 4.631 *** 4.658 *** 5.303 *** 3.688 *** 4.470 ***
NSOURCE 1.694 *** 1.698 *** 1.772 *** 1.769 *** 1.667 ***
NTRACE 0.79 0.768 0.864 0.881 1.115
NPATCH 0.209 * 0.210 * 0.284 + 0.231 * 0.291
NSCOM 1.218 1.194 1.246 1.208 1.244
PATCHS 12.607 * 12.626 * 11.200 * 12.736 * 18.207 **
TRACES 1.016 1.012 1.004 0.989 0.975
NLINK 1.764 *** 1.613 ** 1.600 ** 1.666 ** 1.596 +
NPART 2.481 2.888 4.480 4.542
NDEVS 0.475 0.582 0.385 0.274
NUSERS 0.749 0.803 0.692 0.792
REPLY 1.019 0.986 0.982
REPLYE 0.117 *** 0.082 *** 0.044 ***
DLEN 0.936 0.898 * 0.876 +
DLENE 2.499 1.251 2.044
INT 0.829 ** 0.821 ** 0.963
INTE 1.109 1.013 1.306
WA 1.432 *** 1.224 +
WAE 2.718 * 2.169
CON1-3 Fig. 2 ***
χ2 559.01 *** 698.5 *** 700.15 731.5 *** 752.3 *** 1055.19 ***
Dev. Expl. 10.71% 13.38 % 13.41 % 14.02 % 14.41 % 26.07 %
∆χ2 139.48 1.652 31.357 20.28 302.87
*** p0.001, ** p0.01, * p0.05, + p 0.1
33

Model based on 14.41% Variation
Social Structures Explained

Code Metrics Explained
(Zimmermann 2007)

34


What happens when we combine both?

Code Metrics Explained
(Zimmermann 2007)

34


30.77% Variation
Combined Model
Explained

Traditional Model
17.04% Variation
(Zimmermann,
Explained
PROMISE 2007)
35

Size of Patches
Workﬂow
Code Churn
# Code Examples
Strongest # Links
Variables
(Odds Ratios) Length of the Discussion
Interestigness of Report
# Patches
Reply Time

36

Size of Patches
Workﬂow
Code Churn
# Code,Examples
Strongest io n
t
# Links
la tion !
Variablesr
o re sa
C Ca u
(Odds Ratios)
o t Length of the Discussion
n Interestigness of Report
# Patches
Reply Time

37

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