SlideShare une entreprise Scribd logo
1  sur  131
Télécharger pour lire hors ligne
Linking E-Mails and Source Code Artifacts
Alberto Bacchelli, Michele Lanza
REVEAL @ Faculty of Informatics
University of Lugano
Romain Robbes
PLEIAD @ DCC
University of Chile
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
E-mails are precious
for software engineering
0!
2000!
4000!
6000!
8000!
10000!
12000!
14000!
16000!
Jun-95!
Sep-95!
Dec-95!
Mar-96!
Jun-96!
Sep-96!
Dec-96!
Mar-97!
Jun-97!
Sep-97!
Dec-97!
Mar-98!
Jun-98!
Sep-98!
Dec-98!
Mar-99!
Jun-99!
Sep-99!
Dec-99!
Mar-00!
Jun-00!
Sep-00!
Dec-00!
Mar-01!
Jun-01!
Sep-01!
Dec-01!
Mar-02!
Jun-02!
Sep-02!
Dec-02!
Mar-03!
Jun-03!
Sep-03!
Dec-03!
Mar-04!
Jun-04!
Sep-04!
Dec-04!
Mar-05!
Jun-05!
Sep-05!
Dec-05!
Mar-06!
Jun-06!
Sep-06!
Dec-06!
Mar-07!
Jun-07!
Sep-07!
Dec-07!
Mar-08!
Jun-08!
Sep-08!
Dec-08!
Mar-09!
Jun-09!
Sep-09!
Dec-09!
Mar-10!
E-mails are the
“bread and butter of
project communication”
- Karl Fogel, creator of the Subversion project
Number of e-mails
0
1
2
3
4
5
6
0% 5% 10% 15% 20% 25% 30%
Maintaining mental models: a study of developer work habits
LaToza, Venolia, DeLine [ICSE 2006]
E-mails
Planned
Meetings
Unplanned
Meetings
Internal
Documents
Bug Database
External
Documents
Phone
Web
IM
Other
Effectiveness
Frequency of usage
0
1
2
3
4
5
6
0% 5% 10% 15% 20% 25% 30%
Maintaining mental models: a study of developer work habits
LaToza, Venolia, DeLine [ICSE 2006]
E-mails
Planned
Meetings
Unplanned
Meetings
Internal
Documents
Bug Database
External
Documents
Phone
Web
IM
Other
Effectiveness
Frequency of usage
E-mails are widely used
and highly effective
E-mails are
people-centric information
used to exchange knowledge
Linking E-Mails and Source Code Artifacts
Recovering Traceability Links - State of the Art
Vector Space Model
Probabilistic Model
Latent Semantic Indexing
Recovering Traceability Links - State of the Art
Vector Space Model
Probabilistic Model
Latent Semantic Indexing
Antoniol, Canfora,
Casazza, De Lucia, Merlo
TSE 2002
Recovering Traceability Links - State of the Art
Vector Space Model
Probabilistic Model
Latent Semantic Indexing
Marcus and Maletic
ICSE 2003
Recovering Traceability Links
Vector Space Model
Latent Semantic Indexing
Recovering Traceability Links
Vector Space Model
Latent Semantic Indexing
Recovering Traceability Links
Vector Space Model
Latent Semantic Indexing
Without robust, well-designed time-tested, and,
eventually well-established and accepted benchmarks,
research on application of IR methods to problems in
Software Engineering will not reach its full potential.
- Alex Dekhtyar and Jane Huffman Hayes, ICSM 2006
Without benchmarks,
Software Engineering will not reach its full potential.
Benchmarking the Link
System
ArgoUML
Augeas
Away3D
Freenet
Habari
JMeter
Benchmarking the Link
System Language
ArgoUML Java
Augeas
Away3D
Freenet Java
Habari
JMeter Java
Benchmarking the Link
System Language
ArgoUML Java
Augeas C
Away3D ActionScript
Freenet Java
Habari PHP5
JMeter Java
Benchmarking the Link
System Language Releases
ArgoUML Java 11
Augeas C 17
Away3D ActionScript 9
Freenet Java 30
Habari PHP5 12
JMeter Java 20
Benchmarking the Link
System Language Releases Entities
ArgoUML Java 11 18,252
Augeas C 17 8,042
Away3D ActionScript 9 2,351
Freenet Java 30 37,878
Habari PHP5 12 1,105
JMeter Java 20 11,105
Benchmarking the Link
System Language Releases Entities E-Mails
ArgoUML Java 11 18,252 355
Augeas C 17 8,042 281
Away3D ActionScript 9 2,351 370
Freenet Java 30 37,878 379
Habari PHP5 12 1,105 374
JMeter Java 20 11,105 380
Benchmarking the Link
System Language Releases Entities E-Mails
ArgoUML Java 11 18,252 355
Augeas C 17 8,042 281
Away3D ActionScript 9 2,351 370
Freenet Java 30 37,878 379
Habari PHP5 12 1,105 374
JMeter Java 20 11,105 380
The Miler Web Application
The Miler Web Application
The Miler Web Application
release history
The Miler Web Application
release history
The Miler Web Application
release history
The Miler Web Application
release history
The Miler Web Application
release history
The Miler Web Application
release history
The Miler Web Application
release history
System Language Releases Entities E-Mails
ArgoUML Java 11 18,252 355
Augeas C 17 8,042 281
Away3D ActionScript 9 2,351 370
Freenet Java 30 37,878 379
Habari PHP5 12 1,105 374
JMeter Java 20 11,105 380
Benchmarking the Link
System Language Releases Entities E-Mails
ArgoUML Java 11 18,252 355
Augeas C 17 8,042 281
Away3D ActionScript 9 2,351 370
Freenet Java 30 37,878 379
Habari PHP5 12 1,105 374
JMeter Java 20 11,105 380
Benchmarking the Link
System Language Releases Entities E-Mails
ArgoUML Java 11 18,252 355
Augeas C 17 8,042 281
Away3D ActionScript 9 2,351 370
Freenet Java 30 37,878 379
Habari PHP5 12 1,105 374
JMeter Java 20 11,105 380
Benchmarking the Link
System Language Releases Entities E-Mails
ArgoUML Java 11 18,252 355
Augeas C 17 8,042 281
Away3D ActionScript 9 2,351 370
Freenet Java 30 37,878 379
Habari PHP5 12 1,105 374
JMeter Java 20 11,105 380
Benchmarking the Link
http://miler.inf.usi.ch
Vector Space Model
Vector Space Model
D1 D2 D3 ... DN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
Vector Space Model
D1 D2 D3 ... DN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
Vector Space Model
D1 D2 D3 ... DN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
Vector Space Model
D1 D2 D3 ... DN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
Vector Space Model
D1 D2 D3 ... DN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
Vector Space Model
D1 D2 D3 ... DN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
Vector Space Model
E1 E2 E3 ... EN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
Vector Space Model
E1 E2 E3 ... EN
t1
t2
...
tC
0 1 2 0
0 0 1 4
1 2 0 0
term frequency
Vector Space Model
E1 E2 E3 ... EN
t1
t2
...
tC
0 0.3 0.3 0
0 0 0.01 0.5
0.02 0.4 0 0
term frequency
Vector Space Model
E1 E2 E3 ... EN
t1
t2
...
tC
0 0.3 0.3 0
0 0 0.01 0.5
0.02 0.4 0 0
term frequency
inverse document
frequency
Vector Space Model
term frequency
inverse document
frequency
E1 E2 E3 ... EN
t1
t2
...
tC
0 0.01 0.01 0
0 0 0.01 0.5
0.02 0.4 0 0
Vector Space Model
E1 E2 E3 ... EN Q
t1
t2
...
tC
0 0.01 0.01 0 0
0 0 0.01 0.5 0.2
0.02 0.4 0 0 0.01
E1 E2 E3 ... EN Q
t1
t2
...
tC
0 0.01 0.01 0 0
0 0 0.01 0.5 0.2
0.02 0.4 0 0 0.01
Vector Space Model
E1 E2 E3 ... EN Q
t1
t2
...
tC
0 0.01 0.01 0 0
0 0 0.01 0.5 0.2
0.02 0.4 0 0 0.01
Vector Space Model
E1
E1 E2 E3 ... EN Q
t1
t2
...
tC
0 0.01 0.01 0 0
0 0 0.01 0.5 0.2
0.02 0.4 0 0 0.01
Vector Space Model
E1
E1 E2 E3 ... EN Q
t1
t2
...
tC
0 0.01 0.01 0 0
0 0 0.01 0.5 0.2
0.02 0.4 0 0 0.01
Vector Space Model
E1
E1 E2 E3 ... EN Q
t1
t2
...
tC
0 0.01 0.01 0 0
0 0 0.01 0.5 0.2
0.02 0.4 0 0 0.01
Vector Space Model
E1
E3
E7
VSM on JMeter - Choosing query type and threshold
entire content classname&package classname
F-Measure
Threshold
VSM on JMeter - Choosing query type and threshold
entire content classname&package classname
F-Measure
Threshold0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
0
0.1
0.2
0.3
0.4
VSM on JMeter - Choosing query type and threshold
entire content classname&package classname
F-Measure
Threshold0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
0
0.1
0.2
0.3
0.4
VSM on JMeter - Choosing query type and threshold
entire content classname&package classname
F-Measure
Threshold0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
0
0.1
0.2
0.3
0.4
VSM on JMeter - Best configuration results
0
0.2
0.4
0.6
0.8
1.0
0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
precision recall f-measure
Threshold
VSM - Best configuration results
ArgoUML Freenet JMeter Away3D Habari Augeas
Threshold
F-Measure
0
0.1
0.2
0.3
0.4
0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
VSM - Best configuration results
ArgoUML Freenet JMeter Away3D Habari Augeas
Threshold
F-Measure
0
0.1
0.2
0.3
0.4
0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
Latent Semantic Indexing
Latent Semantic Indexing
‣ Synonymy
Latent Semantic Indexing
‣ Synonymy
NSUML NSUMLModelFacade
Latent Semantic Indexing
‣ Synonymy
NSUML NSUMLModelFacade=
Latent Semantic Indexing
‣ Synonymy
NSUML NSUMLModelFacade
‣ Polysemy
=
Latent Semantic Indexing
‣ Synonymy
NSUML NSUMLModelFacade
‣ Polysemy
dialog Dialog
=
Latent Semantic Indexing
‣ Synonymy
NSUML NSUMLModelFacade
‣ Polysemy
dialog Dialog
=
=
Latent Semantic Indexing
E1 E2 ... EN
t1
t2
...
tC
0 1 0
0 0 4
1 2 0
Latent Semantic Indexing
E1 E2 ... EN
t1
t2
...
tC
0 1 0
0 0 4
1 2 0
Single Value
Decomposition
E1 E2 ... EN
tpc1
tpc2
...
tpcK
0 0.02 0
0 0 0.4
0.1 0.2 0
Latent Semantic Indexing
E1 E2 ... EN
t1
t2
...
tC
0 1 0
0 0 4
1 2 0
Single Value
Decomposition
E1 E2 ... EN
tpc1
tpc2
...
tpcK
0 0.02 0
0 0 0.4
0.1 0.2 0
Latent Semantic Indexing
E1 E2 ... EN
t1
t2
...
tC
0 1 0
0 0 4
1 2 0
Single Value
Decomposition
E1 E2 ... EN
tpc1
tpc2
...
tpcK
0 0.02 0
0 0 0.4
0.1 0.2 0
Latent Semantic Indexing
E1 E2 ... EN
t1
t2
...
tC
0 1 0
0 0 4
1 2 0
Single Value
Decomposition
LSI - Choosing the number of topics and query type
entire content classname&package classname
F-Measure
Number of topics
10 30 50 70 90 110 130 150 170 190 210 230 250 270 290 310 330 350
0
0.1
0.2
0.3
0.4
LSI - Choosing the number of topics and query type
entire content classname&package classname
F-Measure
Number of topics
10 30 50 70 90 110 130 150 170 190 210 230 250 270 290 310 330 350
0
0.1
0.2
0.3
0.4
LSI - Choosing the number of topics and query type
entire content classname&package classname
F-Measure
Number of topics
10 30 50 70 90 110 130 150 170 190 210 230 250 270 290 310 330 350
0
0.1
0.2
0.3
0.4
LSI - Choosing the number of topics and query type
entire content classname&package classname
F-Measure
Number of topics
LSI on JMeter - Best configuration results
0
0.2
0.4
0.6
0.8
0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
precision recall f-measure
Threshold
0
0.15
0.30
0.45
0.60
0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
LSI - Best configuration results
ArgoUML Freenet JMeter Away3D Habari Augeas
Threshold
F-Measure
0
0.15
0.30
0.45
0.60
0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91
LSI - Best configuration results
ArgoUML Freenet JMeter Away3D Habari Augeas
Threshold
F-Measure
What replaces PluggableImport and Generator2?
(and other language module questions)
Tom Morris tfmo...@gmail.com
September 23, 2006 - 13:12:51
We're trying to implement support in ArgoEclipse for reverse engineering which
means that we need to deal with the PluggableImport interface. It doesn't really
make sense to modify that interface because it is deprecated, but I can't figure
o u t w h a t r e p l a c e s i t . Th e c o m m e n t s s ay t o r e g i s t e r w i t h
org.argouml.uml.reveng.Import but that class has no registration method.
Additionally, it itself depends on the deprecated PluggableImport interface.
On the code generation side of things, Generator2 has been deprecated in favor
of CodeGenerator, but they don't appear to have equivalent functionality, so I
don't understand how this is meant to work.
Are there examples of modules which have been converted to the new structure?
Is there a design discussion somewhere which describes how to convert old style
modules to new style modules?
Who's working on this stuff? I'm happy to help if I can get an idea of what the
design direction is.
Tom
What replaces PluggableImport and Generator2?
(and other language module questions)
Tom Morris tfmo...@gmail.com
September 23, 2006 - 13:12:51
We're trying to implement support in ArgoEclipse for reverse engineering which
means that we need to deal with the PluggableImport interface. It doesn't really
make sense to modify that interface because it is deprecated, but I can't figure
o u t w h a t r e p l a c e s i t . Th e c o m m e n t s s ay t o r e g i s t e r w i t h
org.argouml.uml.reveng.Import but that class has no registration method.
Additionally, it itself depends on the deprecated PluggableImport interface.
On the code generation side of things, Generator2 has been deprecated in favor
of CodeGenerator, but they don't appear to have equivalent functionality, so I
don't understand how this is meant to work.
Are there examples of modules which have been converted to the new structure?
Is there a design discussion somewhere which describes how to convert old style
modules to new style modules?
Who's working on this stuff? I'm happy to help if I can get an idea of what the
design direction is.
Tom
Text Matching
Text Matching
Entity Name
Text Matching
Entity Name
dictionary word?
dictionary word?
Text Matching
Entity Name
no
Text Matching
Entity Name
no
Name case sensitive
dictionary word?
dictionary word?
Text Matching
Entity Name
Name case sensitive
yes
Regular Expression
no
dictionary word?
Text Matching
Entity Name
Name case sensitive Regular Expression
no yes
Text Matching - Regular Expression
Classname
Text Matching - Regular Expression
.
/ 
space Classname
Text Matching - Regular Expression
.
/ 
space Classname
space
Text Matching - Regular Expression
.
/ 
space Classname
.
/

space
Text Matching - Regular Expression
.
/ 
space Classname
.
/

space
Text Matching - Regular Expression
java
class
as
php
c
.
/ 
space Classname
.
/

space
package
Text Matching - Regular Expression
java
class
as
php
c
.
/ 
space Classname
.
/

space
.
/ 
space package
Text Matching - Regular Expression
java
class
as
php
c
dictionary word?
Text Matching
Entity Name
Name case sensitive Regular Expression
yesno
Text Matching
dictionary word?
Text Matching
Dialog DialogTree
dictionary word?
dictionary word?
Text Matching
Entity Name
Name case sensitive Regular Expression
yesno
CamelCase?
Text Matching
Entity Name
Name case sensitive Regular Expression
noyes
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Recall
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Precision
Recall
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
P
R
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
P
R
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
Java
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
P
R
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
ActionScript
P
R
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
P
R
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
PHP5
P
R
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
P
R
Text Matching
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Precision Recall F
ArgoUML
Freenet
JMeter
Away3D
Habari
Augeas
0.61 0.64 0.63
0.59 0.59 0.59
0.59 0.65 0.62
0.41 0.72 0.52
0.49 0.38 0.43
0.15 0.64 0.24
C
P
R
Precision
Recall
Overall results
Precision
Recall
Overall results
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Freenet
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Freenet
Overall results
VSM Text MatchingLSI
Precision
Recall
VSM Text MatchingLSI
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
ArgoUML
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
JMeter
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Away3D
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Habari
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Augeas
0
0.2
0.4
0.6
0.8
0 0.2 0.4 0.6 0.8
Freenet
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts
Linking E-Mails and Source Code Artifacts

Contenu connexe

Similaire à Linking E-Mails and Source Code Artifacts

Columnar processing for SQL-on-Hadoop: The best is yet to come
Columnar processing for SQL-on-Hadoop: The best is yet to comeColumnar processing for SQL-on-Hadoop: The best is yet to come
Columnar processing for SQL-on-Hadoop: The best is yet to come
Wang Zuo
 
ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...
ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...
ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...
SilvioDias29
 

Similaire à Linking E-Mails and Source Code Artifacts (20)

Attention mechanisms with tensorflow
Attention mechanisms with tensorflowAttention mechanisms with tensorflow
Attention mechanisms with tensorflow
 
Learning to Spot and Refactor Inconsistent Method Names
Learning to Spot and Refactor Inconsistent Method NamesLearning to Spot and Refactor Inconsistent Method Names
Learning to Spot and Refactor Inconsistent Method Names
 
Columnar processing for SQL-on-Hadoop: The best is yet to come
Columnar processing for SQL-on-Hadoop: The best is yet to comeColumnar processing for SQL-on-Hadoop: The best is yet to come
Columnar processing for SQL-on-Hadoop: The best is yet to come
 
Ecet 340 Your world/newtonhelp.com
Ecet 340 Your world/newtonhelp.comEcet 340 Your world/newtonhelp.com
Ecet 340 Your world/newtonhelp.com
 
Ecet 340 Motivated Minds/newtonhelp.com
Ecet 340 Motivated Minds/newtonhelp.comEcet 340 Motivated Minds/newtonhelp.com
Ecet 340 Motivated Minds/newtonhelp.com
 
Ecet 340 Extraordinary Success/newtonhelp.com
Ecet 340 Extraordinary Success/newtonhelp.comEcet 340 Extraordinary Success/newtonhelp.com
Ecet 340 Extraordinary Success/newtonhelp.com
 
Ecet 340 Education is Power/newtonhelp.com
Ecet 340 Education is Power/newtonhelp.comEcet 340 Education is Power/newtonhelp.com
Ecet 340 Education is Power/newtonhelp.com
 
ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...
ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...
ENCOR SA Scenario Especifica o algoritmo de hashing de senha a ser usado, nes...
 
Writing Metasploit Plugins
Writing Metasploit PluginsWriting Metasploit Plugins
Writing Metasploit Plugins
 
Intro to IO-Link
Intro to IO-LinkIntro to IO-Link
Intro to IO-Link
 
MLflow with R
MLflow with RMLflow with R
MLflow with R
 
A meta model supporting both hardware and smalltalk-based execution of FPGA c...
A meta model supporting both hardware and smalltalk-based execution of FPGA c...A meta model supporting both hardware and smalltalk-based execution of FPGA c...
A meta model supporting both hardware and smalltalk-based execution of FPGA c...
 
Ecet 340 Teaching Effectively--tutorialrank.com
Ecet 340 Teaching Effectively--tutorialrank.comEcet 340 Teaching Effectively--tutorialrank.com
Ecet 340 Teaching Effectively--tutorialrank.com
 
[CB20] DeClang: Anti-hacking compiler by Mengyuan Wan
[CB20] DeClang: Anti-hacking compiler by Mengyuan Wan[CB20] DeClang: Anti-hacking compiler by Mengyuan Wan
[CB20] DeClang: Anti-hacking compiler by Mengyuan Wan
 
DPRSG IC Design
DPRSG IC DesignDPRSG IC Design
DPRSG IC Design
 
Presentation2 1-150523155048-lva1-app6892
Presentation2 1-150523155048-lva1-app6892Presentation2 1-150523155048-lva1-app6892
Presentation2 1-150523155048-lva1-app6892
 
ECAD lab manual
ECAD lab manualECAD lab manual
ECAD lab manual
 
How I learned to stop worrying and love the dark silicon apocalypse.pdf
How I learned to stop worrying and love the dark silicon apocalypse.pdfHow I learned to stop worrying and love the dark silicon apocalypse.pdf
How I learned to stop worrying and love the dark silicon apocalypse.pdf
 
[team608] 전자석을 이용한 타자연습기
[team608] 전자석을 이용한 타자연습기[team608] 전자석을 이용한 타자연습기
[team608] 전자석을 이용한 타자연습기
 
Kotlin: forse è la volta buona (Trento)
Kotlin: forse è la volta buona (Trento)Kotlin: forse è la volta buona (Trento)
Kotlin: forse è la volta buona (Trento)
 

Dernier

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 

Dernier (20)

CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 

Linking E-Mails and Source Code Artifacts