collaboration in se and studies in segal - uvic.caaalbu/ceng 412 2009/collaboration in se and... ·...

Collaboration in software engineering and

Empirical Studies at SEGAL

Daniela DamianSoftware Engineering Global interAction Laboratory

University of Victoria, Canada

collaboration in software engineering

GOALS

establish the scope and capabilities of a project

drive convergence towards a final architecture and design

manage dependencies among activities, artifacts and organizations

identify, record and resolve errors

record organizational memory

collaboration in software engineering

TOOLS

GENERIC COMMUNICATION TOOLS

PHONE, TELECONFERENCES

EMAIL, DISCUSSION LISTS, WEB

INSTANT MESSAGING, VIDEOCONF.

MODEL-ORIENTED TECHNOLOGIES

COLLAB REQUIREMENTS TOOLS

COLLAB UML DIAGRAM CREATION

S/W CONFIGURATION MGMT SYSTES

BUG TRACKING SYSTEMS

SEGAL Research

GOAL:

improve socio-technical coordination

FOCUS:

distributed teams

APPROACH:

focus on people and collaboration

leverage invisible relationships between people and artifacts

our approach to study collaboration in global teams

use social network approaches to get insights into coordination patterns

what are information flow patterns?

are there “good” communication structures that foster effective collaboration?

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+",-(.&'(/#*&0'%("

1#2"-.0

3'%'(&'45%-60

!"# $%&& '()(*+,-(./ 0(%-!"#"$%&3"#7 8-9" :;

Jazz social network: how is the team communicating?

the Jazz Social Network

what are the properties of this Network?

Sparse

Core-periphery

Sparse

Core-periphery

Jazz social network

Core-periphery index = 0.758

a core of developers connect all teams, no team is central

(60/112 members and 75% of communication)

communication and coordination success

Goals and approach

communication believed to impact coordination outcome

successful coordination == successful integration

In jazz: teams involved in a build have high coordination needs

coordination facilitated by commenting or observing communication on work items

What are good Communication Structures?

Can we use communication networks to predict integration results?

Hierarchical Brokers Complete

Relate communication involved in a Build to results of Integration

time

SCMRepository

Build

Result 2

ERROR

Build

Result 3

OK

Build

Result 1

OK Network 2 Network 3

time

Stream

Build N NetworkBuild N

Failed

t0 t1

c1

c2

c3

c4

w1 w2

Previous

Build

c1c2 c3 c4

c

w

commented on

subscribed tocontributor

change set

associated with

work item delivered change set

directed connection


Social Network MeasuresDensity for CompletenessDegree Centralityfor ActivityBetweennessfor ControlStructural Holesfor Redundancy

SN Build 1

SN Build 3

SN Build 4

SN Build 2

SN Build 5

SN Build 6

a) b)

c1 c2

c6c7

c3 c4

c5


Social Network MeasuresDensity for CompletenessDegree Centralityfor ActivityBetweennessfor ControlStructural Holesfor Redundancy

NO Statistically significant Effect

Single communication structures measures have no impact on build results

SN Build 1

SN Build 3

SN Build 4

SN Build 2

SN Build 5

SN Build 6

We could predict around 70% of failing build results

?

PREDICT

input

Bayesian Classifier

train with all measures from

past builds

Predicting integration Resultswith a combination of measures

timenow

Practical Implications

communication does matter in the quality of integration results

integration outcome can be predicted using social network approaches

Failed Build 1Build 2

Bug 123

GUI API

Network

Bug 321

CompilerFile Handling

DataBase GUI TestSpell Check Bug 222

AdamInes

Frank

Cathrin

HelgaEve

Gina

Dillan

Adrian

Filter all tasks that were part of the

Failed Build 1

Connect all filtered people via

task-based communication

Filter the people that contributed

to the Failed Build 1

Filter the people that contributed to

filtered tasks

Connect all filtered people via

task-based communication

Filter all tasks that are part

of the project

Example 1:

Failed Build

Example 2:

Communication Broker

in Distributed Projects


Bug 123

GUI API

Network

Bug 321



AdamInes

Frank

Cathrin

HelgaEve

Gina

Dillan

People of Interest


Bug 123

GUI API

Network

Bug 321



AdamInes

Frank

Cathrin

HelgaEve

Gina

Dillan

Social Network


Bug 123

GUI API

Network

Bug 321



AdamInes

Frank

Cathrin

HelgaEve

Gina

Dillan

Social Network

task

person

person is related to task

task is related to task

communicates withfiltered task

filtered person

Adrian


Bug 123

GUI API

Network

Bug 321



AdamInes

Frank

Cathrin

HelgaEve

Gina

Dillan

Tasks of Interest

Adrian


Bug 123

GUI API

Network

Bug 321



AdamInes

Frank

Cathrin

HelgaEve

Gina

Dillan

People and Tasks of Interest

Adrian

Adrian


Bug 123

GUI API

Network

Bug 321



AdamInes

Frank

Cathrin

HelgaEve

Gina

Dillan

People and Tasks of Interest

Adrian

Adrian

Project-wide people-artifact network.

References

Wolf, T., T. Nguyen and D. Damian, “Does distance still matter?”, Journal of Software Process: Improvement and Practice, oct, 2008

Wolf, T., A. Schroeter, D. Damian and Nguyen, T., “Predicting build failures using communication social network measures”, ICSE 2009, August 2008

Wolf, T., A. Schroeter, D. Damian, L. Panjer and T. Nguyen, “Mining task-based social networks to explore collaboration in software teams”, IEEE Software, Special Issue on Mining Software Repositories, jan/feb 2009

Marczak, S., D. Damian, Ulrike Stege, Adrian Schröter. “Patterns of Information Flow in Interdependent Requirements Social Networks and Implications for Requirements-Driven Collaboration”. Proc. of International Conference on Requirements Engineering (RE 08), Barcelona, 2008

Thanks to SEGAL graduate students!

segal.uvic.ca

Sabrina Marczak

Irwin KwanLucas Panjer

Thanh Nguyen

Timo Wolf

Rafael Prikladniki

Adrian Schroeter [email protected]

collaboration in se and studies in segal - uvic.caaalbu/ceng 412 2009/collaboration in se and... ·...

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