Presented at the SCAM international workshop 2015

1. Matthew B. Kelly Jason S. Alexander Bram Adams Ahmed E. Hassan
Recovering a Balanced Overview
of Topics in a Software Domain

2. Domain Analysis
2

3. Domain Analysis
3
address bar

4. Domain Analysis
4
address bar
tabbed
browsing

5. Domain Analysis
5
address bar
tabbed
browsing
HTML rendering engine

6. Domain Analysis
6
address bar
tabbed
browsing
HTML rendering engine
JavaScript engine

7. Domain Analysis
7
address bar
tabbed
browsing
HTML rendering engine
JavaScript engine
browser extensions

8. Domain Analysis
8
address bar
tabbed
browsing
HTML rendering engine
JavaScript engine
GUI components
browser extensions

9. Domain Analysis
9
address bar
tabbed
browsing
HTML rendering engine
JavaScript engine
GUI components
browser extensions
bookmarks
history
supporting libraries
CSS
XML
A manual, expensive process for large domains!

10. Topic Modeling
10
html css xml
javascript png
jpeg gif sqlite
bmp
gtk event
image html
button frame
window

11. Topic Modeling
11
Latent Dirichlet
Allocation
html css xml
javascript png
jpeg gif sqlite
bmp
gtk event
image html
button frame
window

12. Topic Modeling
12
KeywordsTopic
html css xml
javascript
A
png jpeg gif
bmp image
B
sqlite
C
Latent Dirichlet
Allocation
gtk event
button
frame
window
D
html css xml
javascript png
jpeg gif sqlite
bmp
gtk event
image html
button frame
window

13. Topic Modeling
13
KeywordsTopic
html css xml
javascript
A
png jpeg gif
bmp image
B
sqlite
C
html css xml
javascript png
jpeg gif sqlite
bmp
gtk event
image html
button frame
window
Latent Dirichlet
Allocation
gtk event
button
frame
window
D
A: 0.4
B: 0.4
C: 0.2
D: 0.0
A: 0.2
B: 0.2
C: 0.0
D: 0.6

14. Topic Modeling
14
KeywordsTopic
html css xml
javascript
A
png jpeg gif
bmp image
B
sqlite
C
html css xml
javascript png
jpeg gif sqlite
bmp
gtk event
image html
button frame
window
Latent Dirichlet
Allocation
gtk event
button
frame
window
D
A: 0.4
B: 0.4
C: 0.2
D: 0.0
A: 0.2
B: 0.2
C: 0.0
D: 0.6
Human analysis

15. Unbalanced Domain Analysis
15
…

16. Unbalanced Domain Analysis
16
Corpus
…

17. Unbalanced Domain Analysis
17
LDACorpus
…
Topics

18. Unbalanced Domain Analysis
18
No consideration of project sizes.
But, useful for prioritizing based on popularity.
LDACorpus
…
Topics

19. Balanced Domain Analysis
19
LDA
LDA
LDA
…
…

20. Balanced Domain Analysis
20
LDA
LDA
LDA
…
…
Topics
Topics
Topics

21. Balanced Domain Analysis
21
LDA
LDA
LDA
…
…
Topics
Topics
Topics
Clustering

22. Balanced Domain Analysis
22
LDA
LDA
LDA
…
…
Topics
Topics
Topics
Clustering
Topics

23. Balanced Domain Analysis
23
LDA
LDA
LDA
…
…
Topics
Topics
Topics
Clustering
Topics
Commonalities and variability exposed
regardless of size!

24. Case Study: Over 39M Lines of Code
24

25. Case Study: Over 39M Lines of Code
25
Text
Based
GUI
Based

26. Case Study: Over 39M Lines of Code
26
Text
Based
GUI
Based
Web
Browsers

27. Case Study: Over 39M Lines of Code
27
Text
Based
GUI
Based
Web
Browsers
Question:
Can Domain Analysis be performed with Topic Models?

28. 28
0
10
20
30
40
50
60
70
80
90
100
Percent of
Systems
contained
in cluster
(spread)
Top 10 Topic Clusters
GUI
Base
d
Successful Identification of Commonalities & Variability in
Subdomain

29. Successful Identification of Commonalities & Variability in
Subdomain
0
10
20
30
40
50
60
70
80
90
100
Percent of
Systems
contained
in cluster
(spread)
Top 10 Topic Clusters
29
GTK+ ui framework:
gtk, view, window, action
GUI
Base
d

30. Successful Identification of Commonalities & Variability in
Subdomain
0
10
20
30
40
50
60
70
80
90
100
Percent of
Systems
contained
in cluster
(spread)
Top 10 Topic Clusters
30
GTK+ ui framework:
gtk, view, window, action
Qt ui framework:
qstring, qwidget, parent, window
GUI
Base
d

31. 31
0
10
20
30
40
50
60
70
80
90
100
Percent of
Systems
contained
in cluster
(spread)
Top 10 Topic Clusters
Tex
t
Bas
ed
GUI
Bas
ed
We
b
Bro
wse
rs
Successful Identification of Commonalities &
Variability in Domain

32. Successful Identification of Commonalities &
Variability in Domain
Tex
t
Bas
ed
GUI
Bas
ed
We
b
Bro
wse
rs
0
10
20
30
40
50
60
70
80
90
100
Percent of
Systems
contained
in cluster
(spread)
Top 10 Topic Clusters
32
layout:
view, window, event, widget, terminal, tab

33. Successful Identification of Commonalities &
Variability in Domain
Tex
t
Bas
ed
GUI
Bas
ed
We
b
Bro
wse
rs
0
10
20
30
40
50
60
70
80
90
100
Percent of
Systems
contained
in cluster
(spread)
Top 10 Topic Clusters
33
layout:
view, window, event, widget, terminal, tab
text-based components:
text, items, line, term, htext

34. 34
0
2
4
6
8
10
12
14
16
18
20
Unbalanced LDA spreads Topics across Software Systems

35. 35
0
2
4
6
8
10
12
14
16
18
20
Entropy value: 0.43
Unbalanced LDA spreads Topics across Software Systems

36. 36
0
2
4
6
8
10
12
Balanced LDA spreads Topics across Software Systems

37. 37
0
2
4
6
8
10
12
Entropy value: 0.98
Balanced LDA spreads Topics across Software Systems

38. Threats
38
•Comments: more semantic information than code,
but often missing
•Only open source systems studied
•Other documentation
•One set of thresholds and cluster size tested

42. VS.