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Invited Talk at TU Graz

This document discusses the potentials and challenges of recommendation systems for software engineering. It covers: 1. There is a large need for recommendation systems to address the main challenges in software projects, such as daily changes, information overload, distributed development, and high competition. 2. Some initial research systems have shown promising early results but have limitations in the types of scenarios and contexts they support. 3. Future recommendation systems should support both knowledge consumers and providers during development and collaboration tasks. 4. Major research challenges include better modeling, representing, contextualizing and sharing knowledge in software engineering projects.

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Dr.
Walid
Maalej

 TU
München
 Poten&als
and
 Challenges
of
 Recommenda&on
 Systems
for
So6ware
 Engineering
 Invited
Talk
@
 Ins&tute
of
So6ware
Technology
 Graz
University
of
Technology


Summary 1
 A
large
need
and
high
poten&als
for
recommenda.on
systems
to
 address
today’s
main
challenges
in
so5ware
engineering
projects
 2
 First
research
results
are
promising
but
have
limita&ons
in
 supported
scenarios
and
context‐awareness
 3
 Recommenda.on
systems
should
support
both
knowledge
 consumer
&
provider
during
development
&
collabora&on
tasks
 4
 Major
research
challenges
include
modeling,
represen.ng,
 sessionizing
and
sharing
context
 © W. Maalej, July 2010 Poten&als
and
Challenges
of
RecSys
in
SE

 2
Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 3

Today’s
Challenges
of
So6ware
Projects
 Daily
Change
 •  Change
in
requirements,
design,
 and
project
seHngs
 •  Knowledge
ages

 Informa&on
Overload
 quickly
 2
 •  Projects
with
complex
 1
 technologies,
diverse
 “Mul&ple”
Distribu&on
 frameworks
and
 •  Outsourcing,
offshoring,
open
 requirements
 source,
cross‐organiza.onal
 Four
increasing
 •  Immense
informa.on
sources
 projects
 challenges 
 •  Informa.on
scaOered
across
 •  Limited
awareness
about
 several
systems
 3
 informa.on
 4
 •  Problems
in
coordina.on,
 High
Compe&&on
 knowledge
sharing

 •  Short
“.me
to
market”
 •  Highest
produc.vity,
flexibility
and
 quality
are
required
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 4

Poten&als
of
Recommenda&on
Systems
in
 So6ware
Engineering
 Needs
for
Recommenda&on
Systems 
 Chances
of
Recommenda&on
Systems 
 •  To
cope
with
these
growing
 •  The
nature
of
so5ware
engineering
 challenges
developers
need
 increases
the
poten.als
of
RecSys
 automated
assistance:
 •  Most
data
used
is
structured
or
 •  In
both
collabora.on
and
 semi‐structured
 development
tasks
 •  Development
ac.vi.es
and
 •  To
increase
development
 project
ar.facts
have
well
 efficiency
and
product
quality
 defined
seman.cs
 So6ware
Engineering
is
a
perfect
domain
for
recommenda&on
systems 
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 5

Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 6

Recent
Research
Reaped
Several
Tools
 Tool
 Goal
 Context
 Trigger
 Style
 Corpus
 Inform
newcomers
and
 Explicit
query
(content
 Client/
 CVS,
bug
reports,
 Hipikat
 maintainers
about
past
 Manual
 similarity)
 Server
 emails
 documenta.on
 Method
comments
and
 Foster
code
reuse
by
 Client/
 JavaDoc,
source
 CodeBroker
 signature;
discourse
&
 Con.nuous
 sugges.ng
methods
 Server
 code

 user
model
on
methods
 Speed
up
bug
fixes
by
 Community
data
 Current
bug
report
 Client/
 Dhruv
 recommending
related

 Con.nuous
 (code,
emails,
 (content
similarity)
 Server
 ar.facts

 bug
reports...)
 Hide
non‐relevant
 Task
based
user
 Ar.facts
in
 Eclipse
 Mylyn
 ar.facts
for
current
 interac.on
with
 Con.nuous
 project
 Plug‐in
 task
 ar.facts
 workspace
 Predict
next
methods
 Client/
 Swing
apps
from
 RASCAL
 Analysis
of
current
class
 Manual
 to
be
reused
 Server
 SourceForge
 Give
example
code
for
 Client/
 Strathcona
 Structural
context
 Manual
 Source
code
 third
party
APIs
 Server
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 7

Limita&ons
of
Current
Tools
 “Pseudo”
Context‐Awareness 
 No
pro‐ac.veness,
limited
context
and
personaliza.on
 “Hard‐coded”
knowledge
and
 Limited
focus:
only
reuse
and
 heuris&cs
 
 bug
fixing
scenarios 
 Centralized
and
inflexible
 Informa&on
provision
and
 architecture
 experience
capture
not
supported
 Limita&on
in
 func&onality
and
 technology
 A
systema&c
account
is
required
to
tape
the
poten&als
of
RecSys
in
SE
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 8

Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 9

A
Lightweight
Knowledge
Exchange
Process 
 Looking
for
and
 Knowledge
Sharing

 iden.fying
 knowledge
 Knowledge
 Provider
 Moving
and
 Knowledge
 incorpora.ng
 Knowledge
Access

 knowledge

 Seeker
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 10
Recommenda&on
Landscape
 When Knowledge Access Knowledge Sharing What Propose... Ask to share / capture ... Software Code examples, methods, Ways of using APIs, used Artifacts components, requirements to reuse documentation… Engineering Related Related, useful information for the Information that help to solve a Information current task… particular problem… Warn about a problematic change, New quality measure, design Quality patterns to improve quality… patterns… Tools How-tos, new features… Experience with new tools… Associations of people with People Experts to contact… Collaboration expertise areas… Collaboration artifacts: mails, Awareness Ad-hoc collaboration… decision rationale… Related open issued, emerging Status, open issues, rationale Coordination priorities… behind priority changes… ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 11
Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons:
A.
Context
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 12

What
is
Context?
 Used Artifacts Developer’s Changed Working Session Interactions Artifacts Read Artifacts Context is the set of all events and information, which can be observed or interpreted during knowledge work, except those events and pieces of information that constitute the change ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 13
A
Context
Aware
Model
of
So6ware
 Engineering
Work
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 14
Developer’s
Work:
From
Interac&ons
to
Inten&ons 
 Assist
Colleague
on
 ?
 Reusing
Component
C 
 Fix
Table
Rendering
Bug
 ?
 
 Interac&on
 Current
 Granularity
 Inten&on
 Task
T1:
Implement
XML
 Export 
 Session
 Work
Session
1
 Work
Session
2
 Work
Session
3
 Work
Session
4
 …
 Seman.c

 Read Reuse 
 Impl. 
 Read
Bug
 Seek 
 Debug
 Impl. Test
 Close
 
 
 …
 Chat 
 …
 …
 interac.on
 Task Lib 
 
 Class 
 Report
 Info
 App Met App Bug 
 
 
 h
 Interac.on
 Use
 Download
 Edit
 Copy
 Paste
 Open
 
 
 Scroll
 Edit
 
 Import
 Open
 Add
 
 Edit
 Add
 Step
into
 Step
into
 with
tools
 Run ..Read Search .. ... 
 
 Write 
 
 
 
 
 Scroll 
 
 Tool
T1Library
L 
 Classpath Method
b Method
b 
 Task
List Task
T

 URL
 

 URL Method
a 
 Class
X 
 URL 
 
 
 
 Breakpoint Method
x Method
y 
 
 
 Time
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 15
A
Scratch
of
Context‐Aware
Recommenda&on
Tools 
 Addi.onal

 feedback
 Recommenda&on
Tool
 Interac.on

 interact
 trigger
 Ontoloy
 Context
Observer
 
problem
 
problem
 
Problem
 Applica&on

 sensors
 Elicita&on
 events
 Session‐ iza&on
 Execu.on
 OS

 Execu&on
Env.
 Ontology
 sensors
 sensors
 update
 User
Profile
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 16
Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons:
B.
Knowledge
Sharing
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 17

Inverse
Search
to
Support
Informa&on
Providers
 Conven&onal
recommenda&on
 systems 
 1.  Matches
the
corpus
of
 informa.on
providers
against
 a
given
informa.on
needs
 (e.g.
a
set
of
queries)
 1.  Match
queries
of
knowledge
 seekers
against
a
given
corpus

 2.  Iden.fy
documents/ knowledge
worth
sharing
 2.  Pull
informa.on
into
their
 local
space

 This
model
assists
(and
mo.vates)
 knowledge
providers
in
capturing
 This
model
excludes
knowledge
 and
sharing
their
knowledge

 providers
although
they
are
 poten.al
providers
of
addi.onal
 informa.on
 Recommenda&on
Systems
using
 inverse
search
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 18

Roles
and
Time
in
Informa&on
Access
 Retroac.ve
Search
 Synchronous
 Index
 Query
 Queries
 Results
 Knowledge
 Seeker
 Prospec.ve
Search
 Inverse
Search
 Asynchronous
 Index
 Subscrip&on
 Queries
 
inverse
Search
 No&fica&on
 






Sharing
 Knowledge
 Knowledge
 Seeker
 Provider
 Consumer
 Provider
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 19
Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 20

Challenges
of
Context
Awareness
 Efficient
Instrumenta&on
 How
can
heterogeneous
 Privacy
Protec&on
 Context
Modeling
 tools
be
efficiently
 How
can
we
protect
users’
 How
can
we
model
abstract
 instrumented?
 privacy
while
collec.ng
 no.on
of
context
to
support
 sensi.ve
informa.on?
What
 unique
scenarios?
What
is
 Major
research
 are
acceptable
trade‐offs?

 part
of
the
context?
 challenges
on
 context‐ Context
Representa&on
 
 Aggrega&on
and
Processing
 
 awareness 
 Can
we
efficiently
represent
 How
can
we
aggregate
 data
and
knowledge

and
 Context

 context
for
different
levels
of
 enable
reasoning
and

 Sessioniza&on
 
 granularity?
Can
we
measure
 seman.c
interpreta.on? 
 and
compare
subjec.ve
 How
can
we
“package”
 
 context
like
experience?
 context
events?
How
can
a
 context
switch
be
detected?
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 21


TeamWeaver
Open
Source
Plamorm
 •  A
framework
and
a
set
of
recommenda.on
tools
for
so5ware
engineering
 •  Created
from
past
and
current
research
projects
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 22
Related
Events 
 Conferences
 •  Interna.onal
Conference
on
Automated
So5ware
Engineering
 •  Interna.onal
Conference
on
So5ware
Engineering
 •  ACM
Recommender
Systems
 Workshops
 •  Int.
Workshop
on
Recommenda.on
Systems
in
So5ware
Engineering
 (RSSE)
 •  Int.
Workshop
on
Managing
Requirements
Knowledge
(MaRK)
 •  Social
So5ware
Engineering
(SSE)
 •  Coopera.ve
and
Human
Aspects
in
So5ware
Engineering
(ChaiSE)
 •  Search‐Based
So5ware
Engineering
(SBSE)
 •  Workshop
on
Context,
Informa.on
and
Ontologies
(@EKAW)
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 23
Bibliography
 RecSys
in
So6ware
Engineering
 •  H‐J.
Happel,
W.
Maalej,
Poten.als
and
Challenges
of
Recommenda.on
Systems
for
So5ware
 Development.
In
RSSE'08,
2008.

 •  M.
P.
Robillard,
R.
J.
Walker,
and
T.
Zimmermann.
Recommenda.on
systems
for
so5ware
 engineering.
IEEE
So5ware,
2010.
 •  A.
Felfernig,
et
al.
Recommenda.on
and
Decision
Technologies
For
Requirements
Engineering.
In
 RSSE’10,
2010.
 •  W.
Maalej,
A.
Sahm,
Assis.ng
Engineers
in
Switching
Ar.facts
by
using
Task
Seman.c
and
Interac.on
 History.
In
RSSE’10,
2010.
 •  W.
Maalej,
AK
Thurimella,
Towards
a
Research
Agenda
for
Recommenda.on
Systems
in
 Requirements
Engineering.
In
MaRK’09,
2009.
 Context
&
Inten&ons
 •  W.
Maalej,
Inten.on
Based
Integra.on
of
So5ware
Engineering
Tools,
Dr
Hut
Verlag,
2010
 •  W.
Maalej,
H‐J.
Happel,
Can
Development
Work
Describe
Itself?
In
MSR’10,
IEEE
2010.
 •  W.
Maalej,
Task‐First
or
Context‐First?
Tool
Integra<on
Revisited.
In
ASE’09,
2009.
 Knowledge
Sharing
 •  W
Maalej,
H‐J
Happel,
Lightweight
Knowledge
Sharing
in
Distributed
So5ware
Teams.
In
PAKM,
2008
 •  H‐J
Happel,
Social
Search
and
Need‐driven
Knowledge
Sharing
in
Wikis
with
Woogle.
In
WikiSym,
 2009
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 24
Summary
 1
 A
large
need
and
high
poten.als
for
recommenda.on
systems
to
 address
today’s
main
challenges
in
so5ware
engineering
projects
 2
 First
research
results
are
promising
but
have
limita.ons
in
 supported
scenarios
and
context‐awareness
 3
 Recommenda.on
systems
should
support
both
knowledge
 consumer
&
provider
during
development
&
collabora.on
tasks
 4
 Major
research
challenges
include
modeling,
represen.ng,
 sessionizing,
aggrega.ng
and
sharing
context
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 25
For
more
informa&on
 contact:
 Dr.
Walid
Maalej

 TUM
 maalejw@cs.tum.edu
 www1.in.tum.de/walidmaalej
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 26
Backups
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 27
Four
States
of
Private
and
Organiza&onal
 Knowledge
Space
 A user has lots of knowledge about There is enough knowledge w.r.t. a a topic, while there is not much certain topic, both locally and in the knowledge in the organization organization Documents in private space Organizational Information many Information gap overload Information Personal few shortage information gap few many Documents in organizational space While there is lots of knowledge in Few knowledge exists both locally the organization, the user does not and globally have much knowledge ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 28
The
Big
Picture
of
Context
Aware
Development
 Environments
 Time Short Term Context Long Term Context   Import of external components Component   Developers profiles Reuse   Documentation used on reusing APIs   Documents changed Scenario Context   Error message   Environments   Developers profiles Error Handling   Search keywords on handling errors   Discussion threads ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 29
Which
problems
to
you
encounter
when
you
try
 to
answer
your
ques&ons
during
development? 
 Answer
 %
o5en
or
usual
 I
can’t
specify
my
ques.on
appropriately
in
 33,58%
 search
tools
 I
do
not
know
where
to
find
answers
to
my
 27,88%
 ques.ons
 Answers
to
my
ques.ons
are
outdated
 40,16%
 Answers
to
my
ques.ons
are
too
general
(out
 57,61%
 of
context)
 Answers

to
my
ques.ons
are
scaOered
across
 70,64%
 various
sources
 Answers
to
my
ques.ons
are
not
available
 38,06%
 I
don’t
have
rights
to
access
required
 7,80%
 informa.on
 Experts
are
not
willing
to
help
 9,27%
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 30

Defini&on
 "A
recommenda.on
system
for
so5ware
 engineering
is
a
so5ware
applica.on
that
 provides
informa.on
items
es.mated
to
be
 valuable
for
a
so5ware
engineering
task
in
a
 given
context."
[Robillard,
Walker,
 Zimmermann,
2009]
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 31

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Software Factories in the Real World: How an IBM® WebSphere® Integration Fact...
byProlifics
 
KEY
On the Relationship Between Change Coupling and Software Defects
byMarco D'Ambros
 
PPTX
CosTriage: A Cost-Aware Algorithm for Bug Reporting Systems (AAAI 2011)
bySung Kim
 
PDF
Automated Java Code Generation (ICDIM 2006)
byIT Industry
 
PDF
Cloud computing: evolution or redefinition
byPET Computação
 
KEY
Get ready for web3.0! Open up your app!
byDavid Coallier
 
PDF
Technical Challenges in Resource Discovery
byPaul Walk
 
PDF
Technical Coping Strategies for Resource Discovery - Paul Walk
byJisc
 
KEY
JISC CNI Meeting, Edinburgh 2010
byPaul Walk
 
PPT
A Software Factory Integrating Rational Team Concert and WebSphere tools
byProlifics
 
PPTX
Web Scale Discovery Reality Check
byJeff Wisniewski
 
PDF
Devnology back toschool software reengineering
byDevnology
 
PDF
Final Year Project Guidance
byVarad Meru
 
KEY
Supporting Developers, Supporting Research
byPaul Walk
 
PPT
Systems engineering and project management – partners in successful projects
byAssociation for Project Management
 
PDF
Globalizing Existing Applications
byInfosys
 
PPT
6 chap
bysujitkumar Sujit.Karande
 
It Role State Exploration 7 Nov Illumine
byibecome
 
Alla ricerca della user story perduta
byBetter Software
 
Alla ricerca della User Story perduta
byEdoardo Schepis
 
Software Factories in the Real World: How an IBM® WebSphere® Integration Fact...
byProlifics
 
On the Relationship Between Change Coupling and Software Defects
byMarco D'Ambros
 
CosTriage: A Cost-Aware Algorithm for Bug Reporting Systems (AAAI 2011)
bySung Kim
 
Automated Java Code Generation (ICDIM 2006)
byIT Industry
 
Cloud computing: evolution or redefinition
byPET Computação
 
Get ready for web3.0! Open up your app!
byDavid Coallier
 
Technical Challenges in Resource Discovery
byPaul Walk
 
Technical Coping Strategies for Resource Discovery - Paul Walk
byJisc
 
JISC CNI Meeting, Edinburgh 2010
byPaul Walk
 
A Software Factory Integrating Rational Team Concert and WebSphere tools
byProlifics
 
Web Scale Discovery Reality Check
byJeff Wisniewski
 
Devnology back toschool software reengineering
byDevnology
 
Final Year Project Guidance
byVarad Meru
 
Supporting Developers, Supporting Research
byPaul Walk
 
Systems engineering and project management – partners in successful projects
byAssociation for Project Management
 
Globalizing Existing Applications
byInfosys
 
6 chap
bysujitkumar Sujit.Karande
 

More from Walid Maalej

PDF
How Can Software Engineering Support AI
byWalid Maalej
 
PDF
Can Development Work Describe Itself?
byWalid Maalej
 
PPT
05 Making Tacit Requirements Explicit
byWalid Maalej
 
PPTX
10 A Machine Learning Approach for Identifying Expert Stakeholders
byWalid Maalej
 
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12 Leveraging Rule Deviations in IT Ecosystems for Implicit Requirements Elic...
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11 Towards a Research Agenda for Recommendation Systems in Requirements Engin...
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13 Continuous and Collaborative Validation: A Field Study of Requirements Kno...
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01 Using Defect Reports to Build Requirements Knowledge in Product Lines
byWalid Maalej
 
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07 Modeling and Managing Tacit Product Line Requirements Knowledge
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14 Reasoning on Requirements Knowledge to Support Creativity
byWalid Maalej
 
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03 How to Keep Domain Requirements Models Reasonably Sized
byWalid Maalej
 
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00 Opening: Why MaRK
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byWalid Maalej
 
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byWalid Maalej
 
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From Work To Word
byWalid Maalej
 
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Team Weaver Demo Camp June 08
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Potential And Challenges of Recommendation Systems for Software Development
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byWalid Maalej
 
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byWalid Maalej
 
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byWalid Maalej
 
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byWalid Maalej
 
04 The Papyrus tool as an Eclipse UML2-modeling environment for requirements
byWalid Maalej
 
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byWalid Maalej
 
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byWalid Maalej
 
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byWalid Maalej
 
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byWalid Maalej
 

Invited Talk at TU Graz

  • 1.
    Dr.
Walid
Maalej

 TU
München
 Poten&als
and
 Challenges
of
 Recommenda&on
 Systems
for
So6ware
 Engineering
 Invited
Talk
@
 Ins&tute
of
So6ware
Technology
 Graz
University
of
Technology


  • 2.
    Summary 1
 A
large
need
and
high
poten&als
for
recommenda.on
systems
to
 address
today’s
main
challenges
in
so5ware
engineering
projects
 2
 First
research
results
are
promising
but
have
limita&ons
in
 supported
scenarios
and
context‐awareness
 3
 Recommenda.on
systems
should
support
both
knowledge
 consumer
&
provider
during
development
&
collabora&on
tasks
 4
 Major
research
challenges
include
modeling,
represen.ng,
 sessionizing
and
sharing
context
 © W. Maalej, July 2010 Poten&als
and
Challenges
of
RecSys
in
SE

 2
  • 3.
    Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 3

  • 4.
    Today’s
Challenges
of
So6ware
Projects
 Daily
Change
 •  Change
in
requirements,
design,
 and
project
seHngs
 •  Knowledge
ages

 Informa&on
Overload
 quickly
 2
 •  Projects
with
complex
 1
 technologies,
diverse
 “Mul&ple”
Distribu&on
 frameworks
and
 •  Outsourcing,
offshoring,
open
 requirements
 source,
cross‐organiza.onal
 Four
increasing
 •  Immense
informa.on
sources
 projects
 challenges 
 •  Informa.on
scaOered
across
 •  Limited
awareness
about
 several
systems
 3
 informa.on
 4
 •  Problems
in
coordina.on,
 High
Compe&&on
 knowledge
sharing

 •  Short
“.me
to
market”
 •  Highest
produc.vity,
flexibility
and
 quality
are
required
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 4

  • 5.
    Poten&als
of
Recommenda&on
Systems
in
 So6ware
Engineering
 Needs
for
Recommenda&on
Systems 
 Chances
of
Recommenda&on
Systems 
 •  To
cope
with
these
growing
 •  The
nature
of
so5ware
engineering
 challenges
developers
need
 increases
the
poten.als
of
RecSys
 automated
assistance:
 •  Most
data
used
is
structured
or
 •  In
both
collabora.on
and
 semi‐structured
 development
tasks
 •  Development
ac.vi.es
and
 •  To
increase
development
 project
ar.facts
have
well
 efficiency
and
product
quality
 defined
seman.cs
 So6ware
Engineering
is
a
perfect
domain
for
recommenda&on
systems 
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 5

  • 6.
    Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 6

  • 7.
    Recent
Research
Reaped
Several
Tools
 Tool
 Goal
 Context
 Trigger
 Style
 Corpus
 Inform
newcomers
and
 Explicit
query
(content
 Client/
 CVS,
bug
reports,
 Hipikat
 maintainers
about
past
 Manual
 similarity)
 Server
 emails
 documenta.on
 Method
comments
and
 Foster
code
reuse
by
 Client/
 JavaDoc,
source
 CodeBroker
 signature;
discourse
&
 Con.nuous
 sugges.ng
methods
 Server
 code

 user
model
on
methods
 Speed
up
bug
fixes
by
 Community
data
 Current
bug
report
 Client/
 Dhruv
 recommending
related

 Con.nuous
 (code,
emails,
 (content
similarity)
 Server
 ar.facts

 bug
reports...)
 Hide
non‐relevant
 Task
based
user
 Ar.facts
in
 Eclipse
 Mylyn
 ar.facts
for
current
 interac.on
with
 Con.nuous
 project
 Plug‐in
 task
 ar.facts
 workspace
 Predict
next
methods
 Client/
 Swing
apps
from
 RASCAL
 Analysis
of
current
class
 Manual
 to
be
reused
 Server
 SourceForge
 Give
example
code
for
 Client/
 Strathcona
 Structural
context
 Manual
 Source
code
 third
party
APIs
 Server
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 7

  • 8.
    Limita&ons
of
Current
Tools
 “Pseudo”
Context‐Awareness 
 No
pro‐ac.veness,
limited
context
and
personaliza.on
 “Hard‐coded”
knowledge
and
 Limited
focus:
only
reuse
and
 heuris&cs
 
 bug
fixing
scenarios 
 Centralized
and
inflexible
 Informa&on
provision
and
 architecture
 experience
capture
not
supported
 Limita&on
in
 func&onality
and
 technology
 A
systema&c
account
is
required
to
tape
the
poten&als
of
RecSys
in
SE
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 8

  • 9.
    Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 9

  • 10.
    A
Lightweight
Knowledge
Exchange
Process 
 Looking
for
and
 Knowledge
Sharing

 iden.fying
 knowledge
 Knowledge
 Provider
 Moving
and
 Knowledge
 incorpora.ng
 Knowledge
Access

 knowledge

 Seeker
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 10
  • 11.
    Recommenda&on
Landscape
 When Knowledge Access Knowledge Sharing What Propose... Ask to share / capture ... Software Code examples, methods, Ways of using APIs, used Artifacts components, requirements to reuse documentation… Engineering Related Related, useful information for the Information that help to solve a Information current task… particular problem… Warn about a problematic change, New quality measure, design Quality patterns to improve quality… patterns… Tools How-tos, new features… Experience with new tools… Associations of people with People Experts to contact… Collaboration expertise areas… Collaboration artifacts: mails, Awareness Ad-hoc collaboration… decision rationale… Related open issued, emerging Status, open issues, rationale Coordination priorities… behind priority changes… ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 11
  • 12.
    Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons:
A.
Context
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 12

  • 13.
    What
is
Context?
 Used Artifacts Developer’s Changed Working Session Interactions Artifacts Read Artifacts Context is the set of all events and information, which can be observed or interpreted during knowledge work, except those events and pieces of information that constitute the change ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 13
  • 14.
    A
Context
Aware
Model
of
So6ware
 Engineering
Work
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 14
  • 15.
    Developer’s
Work:
From
Interac&ons
to
Inten&ons 
 Assist
Colleague
on
 ?
 Reusing
Component
C 
 Fix
Table
Rendering
Bug
 ?
 
 Interac&on
 Current
 Granularity
 Inten&on
 Task
T1:
Implement
XML
 Export 
 Session
 Work
Session
1
 Work
Session
2
 Work
Session
3
 Work
Session
4
 …
 Seman.c

 Read Reuse 
 Impl. 
 Read
Bug
 Seek 
 Debug
 Impl. Test
 Close
 
 
 …
 Chat 
 …
 …
 interac.on
 Task Lib 
 
 Class 
 Report
 Info
 App Met App Bug 
 
 
 h
 Interac.on
 Use
 Download
 Edit
 Copy
 Paste
 Open
 
 
 Scroll
 Edit
 
 Import
 Open
 Add
 
 Edit
 Add
 Step
into
 Step
into
 with
tools
 Run ..Read Search .. ... 
 
 Write 
 
 
 
 
 Scroll 
 
 Tool
T1Library
L 
 Classpath Method
b Method
b 
 Task
List Task
T

 URL
 

 URL Method
a 
 Class
X 
 URL 
 
 
 
 Breakpoint Method
x Method
y 
 
 
 Time
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 15
  • 16.
    A
Scratch
of
Context‐Aware
Recommenda&on
Tools 
 Addi.onal

 feedback
 Recommenda&on
Tool
 Interac.on

 interact
 trigger
 Ontoloy
 Context
Observer
 
problem
 
problem
 
Problem
 Applica&on

 sensors
 Elicita&on
 events
 Session‐ iza&on
 Execu.on
 OS

 Execu&on
Env.
 Ontology
 sensors
 sensors
 update
 User
Profile
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 16
  • 17.
    Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons:
B.
Knowledge
Sharing
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 17

  • 18.
    Inverse
Search
to
Support
Informa&on
Providers
 Conven&onal
recommenda&on
 systems 
 1.  Matches
the
corpus
of
 informa.on
providers
against
 a
given
informa.on
needs
 (e.g.
a
set
of
queries)
 1.  Match
queries
of
knowledge
 seekers
against
a
given
corpus

 2.  Iden.fy
documents/ knowledge
worth
sharing
 2.  Pull
informa.on
into
their
 local
space

 This
model
assists
(and
mo.vates)
 knowledge
providers
in
capturing
 This
model
excludes
knowledge
 and
sharing
their
knowledge

 providers
although
they
are
 poten.al
providers
of
addi.onal
 informa.on
 Recommenda&on
Systems
using
 inverse
search
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 18

  • 19.
    Roles
and
Time
in
Informa&on
Access
 Retroac.ve
Search
 Synchronous
 Index
 Query
 Queries
 Results
 Knowledge
 Seeker
 Prospec.ve
Search
 Inverse
Search
 Asynchronous
 Index
 Subscrip&on
 Queries
 
inverse
Search
 No&fica&on
 






Sharing
 Knowledge
 Knowledge
 Seeker
 Provider
 Consumer
 Provider
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 19
  • 20.
    Outline
 1
 Mo&va&on
 2
 State
of
the
Art
 3
 Poten&als
 4
 Research
Direc&ons
 5
 Next
Steps

 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 20

  • 21.
    Challenges
of
Context
Awareness
 Efficient
Instrumenta&on
 How
can
heterogeneous
 Privacy
Protec&on
 Context
Modeling
 tools
be
efficiently
 How
can
we
protect
users’
 How
can
we
model
abstract
 instrumented?
 privacy
while
collec.ng
 no.on
of
context
to
support
 sensi.ve
informa.on?
What
 unique
scenarios?
What
is
 Major
research
 are
acceptable
trade‐offs?

 part
of
the
context?
 challenges
on
 context‐ Context
Representa&on
 
 Aggrega&on
and
Processing
 
 awareness 
 Can
we
efficiently
represent
 How
can
we
aggregate
 data
and
knowledge

and
 Context

 context
for
different
levels
of
 enable
reasoning
and

 Sessioniza&on
 
 granularity?
Can
we
measure
 seman.c
interpreta.on? 
 and
compare
subjec.ve
 How
can
we
“package”
 
 context
like
experience?
 context
events?
How
can
a
 context
switch
be
detected?
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 21

  • 22.
    
TeamWeaver
Open
Source
Plamorm
 •  A
framework
and
a
set
of
recommenda.on
tools
for
so5ware
engineering
 •  Created
from
past
and
current
research
projects
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 22
  • 23.
    Related
Events 
 Conferences
 •  Interna.onal
Conference
on
Automated
So5ware
Engineering
 •  Interna.onal
Conference
on
So5ware
Engineering
 •  ACM
Recommender
Systems
 Workshops
 •  Int.
Workshop
on
Recommenda.on
Systems
in
So5ware
Engineering
 (RSSE)
 •  Int.
Workshop
on
Managing
Requirements
Knowledge
(MaRK)
 •  Social
So5ware
Engineering
(SSE)
 •  Coopera.ve
and
Human
Aspects
in
So5ware
Engineering
(ChaiSE)
 •  Search‐Based
So5ware
Engineering
(SBSE)
 •  Workshop
on
Context,
Informa.on
and
Ontologies
(@EKAW)
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 23
  • 24.
    Bibliography
 RecSys
in
So6ware
Engineering
 •  H‐J.
Happel,
W.
Maalej,
Poten.als
and
Challenges
of
Recommenda.on
Systems
for
So5ware
 Development.
In
RSSE'08,
2008.

 •  M.
P.
Robillard,
R.
J.
Walker,
and
T.
Zimmermann.
Recommenda.on
systems
for
so5ware
 engineering.
IEEE
So5ware,
2010.
 •  A.
Felfernig,
et
al.
Recommenda.on
and
Decision
Technologies
For
Requirements
Engineering.
In
 RSSE’10,
2010.
 •  W.
Maalej,
A.
Sahm,
Assis.ng
Engineers
in
Switching
Ar.facts
by
using
Task
Seman.c
and
Interac.on
 History.
In
RSSE’10,
2010.
 •  W.
Maalej,
AK
Thurimella,
Towards
a
Research
Agenda
for
Recommenda.on
Systems
in
 Requirements
Engineering.
In
MaRK’09,
2009.
 Context
&
Inten&ons
 •  W.
Maalej,
Inten.on
Based
Integra.on
of
So5ware
Engineering
Tools,
Dr
Hut
Verlag,
2010
 •  W.
Maalej,
H‐J.
Happel,
Can
Development
Work
Describe
Itself?
In
MSR’10,
IEEE
2010.
 •  W.
Maalej,
Task‐First
or
Context‐First?
Tool
Integra<on
Revisited.
In
ASE’09,
2009.
 Knowledge
Sharing
 •  W
Maalej,
H‐J
Happel,
Lightweight
Knowledge
Sharing
in
Distributed
So5ware
Teams.
In
PAKM,
2008
 •  H‐J
Happel,
Social
Search
and
Need‐driven
Knowledge
Sharing
in
Wikis
with
Woogle.
In
WikiSym,
 2009
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 24
  • 25.
    Summary
 1
 A
large
need
and
high
poten.als
for
recommenda.on
systems
to
 address
today’s
main
challenges
in
so5ware
engineering
projects
 2
 First
research
results
are
promising
but
have
limita.ons
in
 supported
scenarios
and
context‐awareness
 3
 Recommenda.on
systems
should
support
both
knowledge
 consumer
&
provider
during
development
&
collabora.on
tasks
 4
 Major
research
challenges
include
modeling,
represen.ng,
 sessionizing,
aggrega.ng
and
sharing
context
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 25
  • 26.
    For
more
informa&on
 contact:
 Dr.
Walid
Maalej

 TUM
 maalejw@cs.tum.edu
 www1.in.tum.de/walidmaalej
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 26
  • 27.
    Backups
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 27
  • 28.
    Four
States
of
Private
and
Organiza&onal
 Knowledge
Space
 A user has lots of knowledge about There is enough knowledge w.r.t. a a topic, while there is not much certain topic, both locally and in the knowledge in the organization organization Documents in private space Organizational Information many Information gap overload Information Personal few shortage information gap few many Documents in organizational space While there is lots of knowledge in Few knowledge exists both locally the organization, the user does not and globally have much knowledge ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 28
  • 29.
    The
Big
Picture
of
Context
Aware
Development
 Environments
 Time Short Term Context Long Term Context   Import of external components Component   Developers profiles Reuse   Documentation used on reusing APIs   Documents changed Scenario Context   Error message   Environments   Developers profiles Error Handling   Search keywords on handling errors   Discussion threads ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 29
  • 30.
    Which
problems
to
you
encounter
when
you
try
 to
answer
your
ques&ons
during
development? 
 Answer
 %
o5en
or
usual
 I
can’t
specify
my
ques.on
appropriately
in
 33,58%
 search
tools
 I
do
not
know
where
to
find
answers
to
my
 27,88%
 ques.ons
 Answers
to
my
ques.ons
are
outdated
 40,16%
 Answers
to
my
ques.ons
are
too
general
(out
 57,61%
 of
context)
 Answers

to
my
ques.ons
are
scaOered
across
 70,64%
 various
sources
 Answers
to
my
ques.ons
are
not
available
 38,06%
 I
don’t
have
rights
to
access
required
 7,80%
 informa.on
 Experts
are
not
willing
to
help
 9,27%
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 30

  • 31.
    Defini&on
 "A
recommenda.on
system
for
so5ware
 engineering
is
a
so5ware
applica.on
that
 provides
informa.on
items
es.mated
to
be
 valuable
for
a
so5ware
engineering
task
in
a
 given
context."
[Robillard,
Walker,
 Zimmermann,
2009]
 ©
W.
Maalej,
July
2010
 Poten&als
and
Challenges
of
RecSys
in
SE

 31