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Mathieu	
  Acher,	
  Benoit	
  Combemale,	
  Olivier	
  Barais	
  
Model-­‐Based	
  	
  
Variability	
  Management	
  
	
  
2	
  
Research	
  in	
  so6ware	
  
engineering.	
  
-­‐  8	
  faculty	
  members	
  
-­‐  35	
  researchers	
  and	
  
engineers	
  on	
  projects	
  
We’re	
  hiring!	
  	
  
engineers,	
  PhD	
  students,	
  post-­‐docs	
  
Variability	
  /	
  Product	
  lines	
  	
  
Model-­‐driven	
  Engineering	
  
Language	
  Engineering	
  (e.g.,	
  DSLs)	
  
Scala	
  
3	
  
3	
  
European	
  Projects	
  	
  
	
  
Industrial	
  CollaboraCons	
  
	
  
Academics	
  partners	
  
Acknowledgments	
  (la	
  famille)	
  
Marianela	
  Ciolfi	
  Felice	
  	
  
Joao	
  Bosco	
  Ferreira	
  Filho	
  
Guillaume	
  Bécan	
  
Suresh	
  Pilay	
  	
  
Sana	
  Ben	
  Nasr	
  
(MSc/PhD	
  students,	
  	
  
University	
  of	
  Rennes	
  1)	
  
	
  
Prof.	
  Philippe	
  Collet	
  
Prof.	
  Philippe	
  Lahire	
  	
  
(University	
  of	
  Nice	
  Sophia	
  AnWpolis)	
  
	
  
Prof.	
  Robert	
  B.	
  France	
  	
  
(Colorado	
  State	
  University)	
  
	
  
Prof.	
  Patrick	
  Heymans	
  	
  
(University	
  of	
  Namur)	
  
Audience	
  
•  No	
  pre-­‐requisite	
  background!	
  
•  Targeted	
  Audience	
  
•  Academics	
  or	
  pracWWoners	
  	
  
•  Curious	
  guys:	
  e.g.,	
  PhD	
  students	
  or	
  modellers	
  unaware	
  of…	
  	
  
–  Variability	
  and	
  so6ware	
  product	
  lines	
  (SPLs)	
  
–  Variability	
  modelling	
  	
  
–  ConfiguraWon	
  
•  MDE	
  guys:	
  people	
  involved	
  or	
  interested	
  in	
  the	
  development	
  of	
  
model	
  management	
  tools	
  
–  e.g.,	
  model	
  composiWon/decomposiWon	
  
•  SPL	
  guys:	
  advances	
  that	
  want	
  to	
  learn	
  new	
  techniques	
  
5	
  
At	
  the	
  end	
  of	
  the	
  tutorial…	
  
•  You	
  will	
  have	
  an	
  overview	
  of	
  what’s	
  going	
  on	
  in	
  the	
  field	
  of	
  	
  
variability	
  and	
  model-­‐based	
  so6ware	
  product	
  line	
  engineering	
  
•  You	
  will	
  be	
  able	
  to	
  go	
  further	
  with	
  the	
  languages	
  and	
  modelling	
  
techniques	
  
•  so	
  to	
  reuse	
  them	
  in	
  pracWcal	
  or	
  academic	
  contexts	
  	
  
•  SupporWng	
  material:	
  
hbps://github.com/FAMILIAR-­‐project/familiar-­‐documentaWon/blob/
master/presentaWons/EC2013/README.md	
  	
  
•  slides	
  of	
  the	
  tutorial	
  
•  related	
  arWcles,	
  	
  
•  FAMILIAR	
  scripts,	
  
•  CVL	
  models,	
  
•  and	
  packaged	
  tools	
  to	
  interacWvely	
  play	
  with	
  the	
  models	
  during	
  the	
  
tutorial	
  
6	
  
Differences	
  with	
  previous	
  tutorials	
  at	
  
SPLC’12	
  /	
  MODELS’12	
  
•  Larger	
  perspecWve/moWvaWon	
  
•  Including	
  modelling/language/architectural	
  examples	
  
	
  
•  Not	
  only	
  about	
  feature	
  models	
  
•  not	
  only	
  about	
  FAMILIAR	
  
•  but	
  new	
  techniques	
  for	
  reverse	
  engineering	
  (VaMoS’13)	
  and	
  composing	
  
(MODELS’13)	
  feature	
  models	
  will	
  be	
  presented	
  	
  
•  Model-­‐based	
  product	
  line	
  engineering	
  
•  Common	
  Variability	
  Language	
  (CVL)	
  
FAMILIAR	
  is	
  now	
  a	
  project	
  
	
  not	
  only	
  a	
  language	
  for	
  managing	
  feature	
  models!	
  
7	
  
[MOTIVATION/PROBLEM]	
  Why	
  modeling	
  and	
  managing	
  Variability	
  
does	
  and	
  will	
  maber	
  (30’)	
  
[SOLUTION	
  FOR	
  MANAGING	
  FEATURE	
  MODELS]	
  Managing	
  Variability	
  
Models	
  with	
  FAMILIAR	
  (1h45’)	
  
	
  
	
  
[SOLUTION	
  FOR	
  MODEL-­‐BASED	
  DERIVATION	
  OF	
  PRODUCT]	
  Model-­‐based	
  
variability	
  engineering:	
  examples,	
  support	
  and	
  open	
  issues	
  
(45’)	
  
8	
  
Plan	
  
[MOTIVATION/PROBLEM]	
  Why	
  modeling	
  and	
  managing	
  Variability	
  
does	
  and	
  will	
  maber	
  (30’)	
  
[SOLUTION	
  FOR	
  MANAGING	
  FEATURE	
  MODELS]	
  Managing	
  Variability	
  
Models	
  with	
  FAMILIAR	
  (1h45’)	
  
	
  
	
  
[SOLUTION	
  FOR	
  MODEL-­‐BASED	
  DERIVATION	
  OF	
  PRODUCT]	
  Model-­‐based	
  
variability	
  engineering:	
  examples,	
  support	
  and	
  open	
  issues	
  
(45’)	
  
9	
  
Plan	
  
10	
  
So6ware-­‐intensive	
  systems	
  
come	
  in	
  many	
  variants	
  	
  
11	
  
Linux	
  
Kernel	
  
Database	
  
Engine	
  
Printer	
  
Firmware	
  
Features	
  in	
  MicrosoS	
  Office	
  
15	
  
Ec2013 tutorial-mb variability-final
17	
  
Variability	
  	
  
“the	
  ability	
  of	
  a	
  system	
  to	
  be	
  efficiently	
  extended,	
  
changed,	
  customized	
  or	
  configured	
  for	
  use	
  in	
  a	
  
parCcular	
  context”	
  	
  
Mikael	
  Svahnberg,	
  Jilles	
  van	
  Gurp,	
  and	
  Jan	
  Bosch	
  (2005)	
  
«	
  A	
  set	
  of	
  programs	
  is	
  considered	
  to	
  consWtute	
  
a	
  family,	
  whenever	
  it	
  is	
  worthwhile	
  to	
  study	
  
programs	
  from	
  the	
  set	
  by	
  first	
  studying	
  the	
  
common	
  properCes	
  of	
  the	
  set	
  and	
  then	
  
determining	
  the	
  special	
  properCes	
  of	
  the	
  
individual	
  family	
  members	
  »	
  
	
  
	
  
	
  
	
  
	
  
David	
  L.	
  Parnas	
  —	
  ‘‘On	
  the	
  design	
  and	
  development	
  of	
  program	
  
families’’	
  in	
  TransacCons	
  on	
  SoSware	
  Engineering,	
  SE-­‐2(1):1–9,	
  1976	
  	
  19	
  
aka	
  Variability	
  
Variability	
  	
  
“the	
  ability	
  of	
  a	
  system	
  to	
  be	
  efficiently	
  
extended,	
  changed,	
  customized	
  or	
  
configured	
  for	
  use	
  in	
  a	
  parCcular	
  context”	
  	
  
Mikael	
  Svahnberg,	
  Jilles	
  van	
  Gurp,	
  and	
  Jan	
  Bosch	
  (2005)	
  
	
  
	
  
20	
  
21	
  21	
  
Extensible	
  architectures	
  
(eg	
  plugins-­‐based)	
  
ConfiguraCon	
  
files	
  
System	
  
Preferences	
  
Configurators	
  
Source	
  code	
  
Build	
  
systems	
  
Comparison	
  of	
  *	
  
Structural	
  or	
  behavorial	
  	
  
models	
  
External	
  Variability	
  
Internal	
  Variability	
  
Variability	
  @	
  run.Cme	
  
22	
  
«	
  Feature	
  Model	
  ExtracWon	
  from	
  Large	
  CollecWons	
  of	
  Informal	
  Product	
  DescripWons	
  »	
  	
  
Jean-­‐Marc	
  Davril,	
  Edouard	
  Delfosse,	
  Negar	
  Hariri,	
  Mathieu	
  Acher,	
  Jane	
  Cleland-­‐Huang,	
  Patrick	
  
Heymans	
  (ESEC/FSE’13)	
  
23	
  
«	
  The	
  Anatomy	
  of	
  a	
  Sales	
  Configurator:	
  An	
  Empirical	
  Study	
  of	
  111	
  Cases	
  »	
  Ebrahim	
  Khalil	
  Abbasi,	
  
Arnaud	
  Hubaux,	
  Mathieu	
  Acher,	
  QuenWn	
  Boucher,	
  and	
  Patrick	
  Heymans	
  (CAiSE’13)	
  
24	
  
«	
  ExtracWon	
  and	
  EvoluWon	
  of	
  Architectural	
  Variability	
  Models	
  in	
  Plugin-­‐based	
  Systems	
  »	
  	
  	
  
Mathieu	
  Acher,	
  Anthony	
  Cleve,	
  Philippe	
  Collet,	
  Philippe	
  Merle,	
  Laurence	
  Duchien,	
  Philippe	
  
Lahire	
  ECSA/SoSyM’13	
  
If	
  you’re	
  able	
  to	
  master	
  variability…	
  
•  Reduce	
  development	
  costs	
  	
  
•  Reduce	
  cerWficaWon	
  costs	
  	
  
•  Shorten	
  Wme-­‐to-­‐market	
  	
  
•  But,	
  are	
  you	
  able?	
  	
  
– developing,	
  verifying,	
  cerWfying	
  billions	
  of	
  variants	
  is	
  
challenging!	
  
	
   25	
  
Variability = Complexity
ChrisWan	
  Kästner	
  slide	
  
a	
  unique	
  variant	
  for	
  every	
  
person	
  on	
  this	
  planet	
  
33	
  features	
  
opWonal,	
  independent	
  
ChrisWan	
  Kästner	
  slide	
  
320	
  features	
  
	
  
more	
  variants	
  than	
  esWmated	
  
	
  	
  atoms	
  in	
  the	
  universe	
  
opWonal,	
  independent	
  
2000	
  features	
   10000	
  
features	
  
ChrisWan	
  Kästner	
  slide	
  
30	
  
	
  
	
  
Avoid	
  solving	
  the	
  same	
  problem!	
  
	
  
	
  
	
  2,	
  3…n	
  Cmes	
  	
  
AutomaCon?	
  
31	
  
Unused	
  flexibility	
  
32	
  
Illegal	
  variant	
  
 
	
  
Goal:	
  So6ware	
  mass	
  customizaWon	
  	
  
/	
  AdapWve	
  and	
  configurable	
  systems	
  
	
  
Problem:	
  Variability	
  =	
  Complexity	
  
	
  
Approach:	
  Model-­‐based	
  variability	
  management	
  
33	
  
Why	
  managing	
  Variability	
  	
  
does	
  (and	
  will)	
  maier	
  
34	
  
So6ware-­‐intensive	
  systems	
  
come	
  in	
  many	
  variants	
  	
  
Model-­‐based	
  	
  
Variability	
  Management	
  
 
Modeling	
  Variability	
  
	
  
CommunicaCve	
  
	
  
AnalyCc	
  
	
  
GeneraCve	
  
	
   35	
  
36	
  
Ec2013 tutorial-mb variability-final
38	
  
Factoring	
  out	
  commonaliCes	
  
	
  for	
  Reuse	
  [Krueger	
  et	
  al.,	
  1992]	
  [Jacobson	
  et	
  al.,	
  1997]	
  
	
  
	
  
	
  
	
  
	
  
	
  
Managing	
  variabiliCes	
  	
  
	
  for	
  So6ware	
  Mass	
  CustomizaCon	
  [Bass	
  et	
  al.,	
  1998]	
  [Krueger	
  et	
  al.,	
  2001],	
  [Pohl	
  et	
  al.,	
  2005]	
  
	
  
	
  
Mobile
3G+ 3G GPS
Maps
Camera
ü	
  
ü	
  
ü	
  
Mobile
3G+ 3G GPS
Maps
Camera
Domain/Variability	
  Model	
  
ConfiguraCon	
   SoSware	
  Generator	
  
Domain	
  Artefacts	
  	
  
	
  
Domain	
  	
  
Engineering	
  
ApplicaCon	
  	
  
Engineering	
  
«	
  the	
  investments	
  required	
  to	
  develop	
  the	
  reusable	
  arBfacts	
  during	
  
domain	
  engineering,	
  are	
  outweighed	
  by	
  the	
  benefits	
  of	
  deriving	
  the	
  
individual	
  products	
  during	
  applica.on	
  engineering	
  »	
  
Jan	
  Bosch	
  et	
  al.	
  (2004)	
  	
  	
  
40	
  
99%	
  domain	
  engineering,	
  	
  
1%	
  applicaCon	
  engineering?	
  
–  specifies	
  what	
  you	
  want	
  (click,	
  click,	
  click)	
  a	
  customized	
  
product	
  is	
  automaWcally	
  built	
  for	
  you	
  
–  Iterate	
  the	
  process	
  for	
  n	
  products	
  
Amount
of
effort
Application
Engineering
More Sophisticated
Technology
Domain
Engineering
Variability	
  AbstracCon	
  
Model	
  (VAM)	
  
ConfiguraCon	
  
(resoluCon	
  model)	
  
Domain	
  Artefacts	
  
(e.g.,	
  models)	
  
SoSware	
  Generator	
  
(derivaCon	
  engine)	
  
ü	
   ü	
  
Variability	
  
RealizaCon	
  
Model	
  
(VRM)	
  
42	
  
Configurations
Derivation
Process
Models of
the
“system”
Feature
Model
How to
realize the
variability
(another	
  research	
  area/applicaWon:	
  
adapWve	
  systems	
  aka	
  dynamic	
  so6ware	
  product	
  lines	
  
Models@run.Wme)	
  
hip://www.kevoree.org	
  
from	
  Cloud	
  stack	
  to	
  
embedded	
  devices	
  
Ec2013 tutorial-mb variability-final
Variability	
  Handling	
  in	
  AUTOSAR	
  
Body	
  
control	
  
Low-­‐end	
  light-­‐
control	
  
AdapWve-­‐curve	
  
light-­‐control	
  
Feature	
  Modeling	
  
(Variability	
  abstracWon)	
  
Generic	
  Template	
  
(Variability	
  RealizaWon)	
  
LightType	
  
…	
   System	
  
constant	
  
Low	
  End	
   High	
  End	
  
Car	
  
1..1
Feature	
  
v.	
  4.04	
  (upcoming)	
  
v.	
  4.03	
  
Low	
  End	
  ==	
  1	
  
High	
  End	
  ==	
  1	
   VariaWon	
  
point	
  
Adapted	
  from	
  the	
  CVL	
  tutorial	
  at	
  SPLC’12	
  by	
  Oystein	
  Haugen,	
  Andrezj	
  Wasowski,	
  Krzysztof	
  Czarnecki	
  	
  
Variability	
  Handling	
  in	
  AUTOSAR	
  (2)	
  
Feature	
  Modeling	
  
(Variability	
  abstracWon)	
  
Generic	
  Template	
  
(Variability	
  RealizaWon)	
  
Low	
  End	
   High	
  End	
  
Car	
  
1..1
Body	
  
control	
  
Low-­‐end	
  
light-­‐control	
  
VariaCon	
  Point	
  Types	
  
•  Variability	
  is	
  applied	
  to	
  different	
  parts	
  of	
  the	
  
metamodel	
  
– AggregaWon,	
  associaWon,	
  abribute	
  value,	
  property	
  
set	
  
•  ResulWng	
  variability	
  
– OpWonal	
  component	
  
– OpWonal	
  port	
  
– OpWonal	
  connector	
  
– Parameter	
  variability	
  
Component	
  
Port	
  
Adapted	
  from	
  the	
  CVL	
  tutorial	
  at	
  SPLC’12	
  by	
  Oystein	
  Haugen,	
  Andrezj	
  Wasowski,	
  Krzysztof	
  Czarnecki	
  	
  
49	
  
«	
  Mapping	
  Features	
  to	
  Models:	
  A	
  Template	
  Approach	
  Based	
  on	
  Superimposed	
  Variants»	
  
Krzysztof	
  Czarnecki	
  and	
  Michal	
  Antkiewicz	
  GPCE’05	
  
50	
  
«	
  Mapping	
  Features	
  to	
  Models:	
  A	
  Template	
  Approach	
  Based	
  on	
  Superimposed	
  Variants»	
  
Krzysztof	
  Czarnecki	
  and	
  Michal	
  Antkiewicz	
  GPCE’05	
  
51	
  
«	
  Mapping	
  Features	
  to	
  Models:	
  A	
  Template	
  Approach	
  Based	
  on	
  Superimposed	
  Variants»	
  
Krzysztof	
  Czarnecki	
  and	
  Michal	
  Antkiewicz	
  GPCE’05	
  
52	
  
«	
  Mapping	
  Features	
  to	
  Models:	
  A	
  Template	
  Approach	
  Based	
  on	
  Superimposed	
  Variants»	
  
Krzysztof	
  Czarnecki	
  and	
  Michal	
  Antkiewicz	
  GPCE’05	
  
Safe	
  composiWon?	
  No!	
  
53	
  
«Verifying	
  Feature-­‐Based	
  Model	
  Templates	
  Against	
  
Well-­‐Formedness	
  OCL	
  Constraints	
  »	
  Krzysztof	
  Czarnecki	
  Krzysztof	
  Pietroszek	
  GPCE’06	
  
Ooops	
  
54	
  
«Verifying	
  Feature-­‐Based	
  Model	
  Templates	
  Against	
  
Well-­‐Formedness	
  OCL	
  Constraints	
  »	
  Krzysztof	
  Czarnecki	
  Krzysztof	
  Pietroszek	
  GPCE’06	
  
Another	
  approach	
  
55	
  
«	
  Reconciling	
  AutomaWon	
  and	
  Flexibility	
  in	
  Product	
  DerivaWon	
  »	
  Gilles	
  Perrouin,	
  Jacques	
  Klein,	
  
Nicolas	
  Guelfi,	
  Jean-­‐Marc	
  Jézéquel	
  SPLC’08	
  
56	
  
«	
  Reconciling	
  AutomaWon	
  and	
  Flexibility	
  in	
  Product	
  DerivaWon	
  »	
  Gilles	
  Perrouin,	
  Jacques	
  Klein,	
  
Nicolas	
  Guelfi,	
  Jean-­‐Marc	
  Jézéquel	
  SPLC’08	
  
Merging-­‐based	
  DerivaCon	
  of	
  Product	
  
Ec2013 tutorial-mb variability-final
Variability	
  at	
  the	
  language	
  level	
  
	
  
58
Variability	
  in	
  
Metamodeling	
  
•  SemanWc	
  variaWon	
  point	
  
•  DSML	
  Families	
  
•  Knowledge	
  capitalizaWon	
  
•  Language	
  Engineering	
  
	
  
Variability	
  in	
  
Modeling	
  
Variability	

Variability


 










	
  Engineering	
  SemanCcs	
  in	
  Modeling	
  Languages	
  
59
Abstract
Syntax
(AS)
Concrete
Syntax
(CS)
Semantics
Domain
(SD)
Mac
Mas
•  Variability	
  in	
  metamodeling	
  (DSML	
  families,	
  variaWon	
  point...):	
  
–  Abstract	
  syntax:	
  staWc	
  introducWon	
  (AOM),	
  inheritance	
  (OOP)	
  
–  Concrete	
  syntax:	
  view	
  point	
  (OBEO	
  Designer)	
  
–  SemanWcs:	
  sWll	
  a	
  problem!	
  how	
  to	
  define	
  and	
  manage	
  semanBc	
  
variability	
  (in	
  the	
  DSML	
  and	
  the	
  associated	
  tools)?	
  
DSL4	
  
DSL3	
  DSL2	
  
DSL1	
  
Language	
  Family	
  
(expresiveness,	
  semanWc	
  variaWon	
  point,	
  	
  
implementaWon	
  variaWon	
  point,	
  viewpoints,	
  tooling,	
  etc.)	
  
RM	
  
dsl1	
  
RM	
  
dsl2	
  
RM	
  
dsl3	
  RM	
  
dsl4	
  
Challenge1:	
  Modular	
  
Language	
  Design	
  
Challenge3:	
  
Language	
  
ComposiWon	
  
Challenge2:	
  
Variability	
  Modeling	
  
«	
  Variability	
  Management	
  in	
  Modeling	
  Languages	
  »	
  Suresh	
  Pilay	
  PhD	
  thesis	
  (ongoing)	
  
DSL	
  
Variability	
  
model	
  
CVL	
  
Base	
  	
  
model	
  
Generic	
  &	
  	
  
Standardized	
  
resoluCon	
  
models	
  
Focused	
  on	
  	
  
a	
  domain	
  
Execute	
  CVL	
  
	
  
	
  
Resolved	
  	
  
models	
  
DescripWon	
  of	
  
possible	
  
variaWons	
  in	
  
the	
  system	
  
Domain	
  
model	
  of	
  a	
  
parWcular	
  
family	
  of	
  
system	
  
SelecWon	
  of	
  a	
  set	
  
of	
  opWons	
  in	
  the	
  
variaWon	
  model	
  
Family	
  of	
  systems	
  fully	
  
described	
  in	
  the	
  
domain	
  specific	
  
language.	
  
All	
  regular	
  DSL	
  tools	
  
can	
  be	
  applied	
  to	
  these	
  
models	
  
61	
  
RealizaCon	
  
model	
  
Language
Units
Language
Features
how to realize
the features
Configuration
of languages
Derivation
Process
Languages
«	
  Variability	
  Management	
  Modeling	
  Languages	
  »	
  Suresh	
  Pilay	
  PhD	
  thesis	
  (ongoing)	
  
Ec2013 tutorial-mb variability-final
63	
  
«	
  ExtracWon	
  and	
  EvoluWon	
  of	
  Architectural	
  Variability	
  Models	
  in	
  Plugin-­‐based	
  Systems	
  »	
  	
  	
  
Mathieu	
  Acher,	
  Anthony	
  Cleve,	
  Philippe	
  Collet,	
  Philippe	
  Merle,	
  Laurence	
  Duchien,	
  Philippe	
  
Lahire	
  ECSA/SoSyM’13	
  
64	
  
«	
  ExtracWon	
  and	
  EvoluWon	
  of	
  Architectural	
  Variability	
  Models	
  in	
  Plugin-­‐based	
  Systems	
  »	
  	
  	
  
Mathieu	
  Acher,	
  Anthony	
  Cleve,	
  Philippe	
  Collet,	
  Philippe	
  Merle,	
  Laurence	
  Duchien,	
  Philippe	
  
Lahire	
  ECSA/SoSyM’13	
  
FraSCAti
SCAParser
Java Compiler
JDK6 JDT
Optional
Mandatory
Alternative-
Group
Or-Group
Assembly Factory
resthttp
Binding
MMFrascati
Component Factory
Metamodel
MMTuscany
constraints
rest requires MMFrascati
http requires MMTuscany
FM1
Variability	
  Model	
  
65	
  
Variability	
  Model	
  
FraSCAti
SCAParser
Java Compiler
JDK6 JDT
Optional
Mandatory
Alternative-
Group
Or-Group
Assembly Factory
resthttp
Binding
MMFrascati
Component Factory
Metamodel
MMTuscany
constraints
rest requires MMFrascati
http requires MMTuscany
FM1
FraSCAC	
  Architecture	
  
Set	
  of	
  	
  Safe	
  
Variants	
  
authorized	
  by	
  
FraSCAC	
  
Scope	
  is	
  
too	
  large	
  
Illegal	
  	
  Variant	
  	
  
66	
  
67	
  
FraSCAC	
  Architecture	
  
FraSCAti
SCAParser
Java Compiler
JDK6 JDT
Optional
Mandatory
Alternative-
Group
Or-Group
Assembly Factory
resthttp
Binding
MMFrascati
Component Factory
Metamodel
MMTuscany
constraints
rest requires MMFrascati
http requires MMTuscany
FM1
Feature	
  Model	
  
FraSCAti
SCAParser
Java Compiler
JDK6 JDT
Optional
Mandatory
Alternative-
Group
Or-Group
Assembly Factory
resthttp
Binding
MMFrascati
Component Factory
Metamodel
MMTuscany
constraints
rest requires MMFrascati
http requires MMTuscany
FM1
ConfiguraCon	
   Derived	
  FraSCAC	
  Architecture	
  
[MOTIVATION/PROBLEM]	
  Why	
  modeling	
  and	
  managing	
  Variability	
  
does	
  and	
  will	
  maber	
  (30’)	
  
[SOLUTION	
  FOR	
  MANAGING	
  FEATURE	
  MODELS]	
  Managing	
  Variability	
  
Models	
  with	
  FAMILIAR	
  (1h45’)	
  
	
  
	
  
[SOLUTION	
  FOR	
  MODEL-­‐BASED	
  DERIVATION	
  OF	
  PRODUCT]	
  Model-­‐based	
  
variability	
  engineering:	
  examples,	
  support	
  and	
  open	
  issues	
  
(45’)	
  
68	
  
Plan	
  
Variability	
  Model	
  
ConfiguraCon	
  
Domain	
  Artefacts	
  (e.g.,	
  source	
  code)	
  
SoSware	
  Generator	
  
Modeling	
  
variability	
  	
  
is	
  crucial	
  
ü	
   ü	
  
70	
  
Unused	
  flexibility	
  
71	
  
Illegal	
  variant	
  
72	
  72	
  
Extensible	
  architectures	
  
(plugins-­‐based)	
  
ConfiguraCon	
  
files	
  
System	
  
Preferences	
  
Configurators	
  
Source	
  code	
  
Build	
  systems	
  
Comparison	
  of	
  Product	
  
 
Variability	
  AbstracCon	
  Model	
  
(VAM)	
  
	
  
CommunicaCve	
  
	
  
AnalyCc	
  
	
  
GeneraCve	
  
	
   73	
  
not, and, or, implies
Variability	
  Model	
  
Feature	
  Model:	
  de	
  facto	
  standard	
  
•  Research	
  	
  
–  2500+	
  citaWons	
  of	
  [Kang	
  et	
  al.,	
  1990]	
  on	
  Google	
  Scholar	
  	
  
–  Central	
  to	
  many	
  generaWve	
  approaches	
  
•  at	
  requirements	
  or	
  code	
  level	
  
–  Tools	
  &	
  Languages	
  (GUIDSL/FeatureIDE,	
  SPLOT,	
  FaMa,	
  
etc.)	
  
•  Industry	
  	
  
–  Tools	
  (Gears,	
  pure::variants),	
  	
  
•  Common	
  Variability	
  Language	
  (CVL)	
   74	
  
Ec2013 tutorial-mb variability-final
Feature	
  Models	
  
76	
  
Feature	
  Models	
  (Background)	
  
77	
  
Hierarchy:	
  rooted	
  tree	
  	
  
Variability:	
  	
  
•  mandatory,	
  	
  
•  opWonal,	
  	
  
•  Groups:	
  exclusive	
  or	
  inclusive	
  features	
  
•  Cross-­‐tree	
  constraints	
  
Optional
Mandatory
Xor-Group
Or-Group
78	
  
Hierarchy	
  +	
  Variability	
  	
  
=	
  	
  
set	
  of	
  valid	
  configuraCons	
  
{CarEquipment,	
  Comfort,	
  DrivingAndSafety,	
  Healthing,	
  AirCondiWoning,	
  FrontFogLights}	
  
configuraCon	
  =	
  set	
  of	
  features	
  selected	
  
Optional
Mandatory
Xor-Group
Or-Group
79	
  
Hierarchy	
  +	
  Variability	
  	
  
=	
  	
  
set	
  of	
  valid	
  configuraCons	
  
{CarEquipment,	
  Comfort,	
  DrivingAndSafety,	
  Healthing,	
  AirCondiWoning}	
  
configuraCon	
  =	
  set	
  of	
  features	
  selected	
  
Optional
Mandatory
Xor-Group
Or-Group
80	
  
Hierarchy	
  +	
  Variability	
  	
  
=	
  	
  
set	
  of	
  valid	
  configuraCons	
  
Optional
Mandatory
Xor-Group
Or-Group
{CarEquipment,	
  Comfort,	
  DrivingAndSafety,	
  Healthing,	
  AirCondiWoning,	
  
AutomaWcHeadLights}	
  
configuraCon	
  =	
  set	
  of	
  features	
  selected	
  
ü	
  
ü	
  
ü	
  
ü	
  
ü	
  
ü	
  
81	
  
Hierarchy	
  +	
  Variability	
  	
  
=	
  	
  
set	
  of	
  valid	
  configuraCons	
  
Optional
Mandatory
Xor-Group
Or-Group
{AirCondiWoning,	
  FrontFogLights}	
  
{AutomaWcHeadLights,	
  AirCondiWoning,	
  FrontFogLights}	
  
{AutomaWcHeadLights,	
  FrontFogLights,	
  AirCondiWoningFrontAndRear}	
  
{AirCondiWoningFrontAndRear}	
  
{AirCondiWoning}	
  
{AirCondiWoningFrontAndRear,	
  FrontFogLights}	
  
{CarEquipment,	
  Comfort,	
  
DrivingAndSafety,	
  
Healthing}	
   X
Feature	
  Models	
  
82	
  
Ec2013 tutorial-mb variability-final
 (FeAture	
  Model	
  scrIpt	
  Language	
  for	
  manIpulaWon	
  and	
  AutomaWc	
  Reasoning)	
  	
  
not, and, or, implies
φTVL
DIMACS
hip://familiar-­‐project.github.com/	
  
Mathieu	
  Acher,	
  Philippe	
  Collet,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  France	
  «	
  A	
  Domain-­‐Specific	
  Language	
  for	
  Large-­‐
Scale	
  Management	
  of	
  Feature	
  Models	
  »	
  Science	
  of	
  Computer	
  Programming	
  (SCP),	
  2013	
  
85	
  
Optional
Mandatory
Xor-Group
Or-Group
86	
  
Optional
Mandatory
Xor-Group
Or-Group
87	
  
Optional
Mandatory
Xor-Group
Or-Group
{AirCondiWoning,	
  FrontFogLights}	
  
{AutomaWcHeadLights,	
  AirCondiWoning,	
  
FrontFogLights}	
  
{AutomaWcHeadLights,	
  FrontFogLights,	
  
AirCondiWoningFrontAndRear}	
  
{AirCondiWoningFrontAndRear}	
  
{AirCondiWoning}	
  
{AirCondiWoningFrontAndRear,	
  FrontFogLights}	
  
{CarEquipment,	
  Comfort,	
  
DrivingAndSafety,	
  
Healthing}	
  
X
88	
  
Ec2013 tutorial-mb variability-final
 (FeAture	
  Model	
  scrIpt	
  Language	
  for	
  manIpulaWon	
  and	
  AutomaWc	
  Reasoning)	
  	
  
imporCng,	
  exporCng,	
  composing,	
  decomposing,	
  ediCng,	
  configuring,	
  
reverse	
  engineering,	
  compuCng	
  "diffs",	
  refactoring,	
  tesCng,	
  	
  
and	
  reasoning	
  about	
  (mulCple)	
  variability	
  models	
  
not, and, or, implies
φTVL
DIMACS
hip://familiar-­‐project.github.com/	
  
Mathieu	
  Acher,	
  Philippe	
  Collet,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  France	
  «	
  A	
  Domain-­‐Specific	
  Language	
  for	
  Large-­‐
Scale	
  Management	
  of	
  Feature	
  Models	
  »	
  Science	
  of	
  Computer	
  Programming	
  (SCP),	
  2013	
  
#1	
  Automated	
  Analysis	
  
91	
  
#2	
  MulCple	
  Feature	
  Models	
  
92	
  
93	
  93	
  
MulC-­‐*	
  variability	
  
	
  
	
  
	
  
	
  
*systems,	
  perspecCves,	
  or	
  stakeholders	
  
•  #1	
  Automated	
  analysis	
  	
  
–  Aka	
  support	
  to	
  beber	
  understand	
  and	
  play	
  with	
  your	
  feature	
  
model	
  (TVL	
  model)	
  
•  #2	
  Managing	
  mulCple	
  feature	
  models	
  
–  Composing	
  /	
  Decomposing	
  /	
  Diff	
  and	
  Reasoning	
  about	
  their	
  
relaWonships	
  
–  Combining	
  these	
  operators	
   94	
  
Two	
  Key	
  Requirements	
  
language	
  and	
  environment	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
And-Group
Optional
Mandatory
Xor-Group
Or-Group
constraints
……..
DirectX
V10 V10.1 v11
Outputs
VIVO DVI HDMI
S-Video Composite
VGA
GraphicCard And-Group
Optional
Mandatory
Xor-Group
Or-Group
TV output
constraints
VGA excludes TV output
HDMI implies v10.1 or v11
constraints
……..
constraints
……..
constraints
……..
//	
  foo.fml	
  
fm1	
  =	
  FM	
  (“foo1.tvl”)	
  
fm2	
  =	
  FM	
  (“foo2.m”)	
  
fm3	
  =	
  merge	
  intersecCon	
  {	
  fm1	
  fm2	
  }	
  
c3	
  =	
  counCng	
  fm3	
  
renameFeature	
  fm3.TV	
  as	
  “OutputTV”	
  
fm5	
  =	
  aggregate	
  {	
  fm3	
  FM	
  (“foo4.xml”)	
  }	
  
assert	
  (isValid	
  fm5)	
  	
  	
  
fm6	
  =	
  slice	
  fm5	
  including	
  fm5.TV.*	
  	
  
export	
  fm6	
  
	
  
True/False	
  
8759	
  
“OutputTV”,	
  “TV”	
  	
  
Interoperability	
   Language	
  faciliCes	
   Environment	
  
96	
  
Interoperability	
  
fm1	
  =	
  FM(“foo.tvl”)	
  
fm2	
  =	
  FM	
  (“foo.m”)	
  
	
  
serialize	
  fm4	
  into	
  SPLOT	
  
serialize	
  fm1	
  into	
  featureide	
  fm3	
  =	
  FM	
  (“foo.xmi”)	
  
fm4	
  =	
  FM	
  (A	
  :	
  B	
  ….)	
  
	
  
	
  	
  De/ComposiCon	
  
merge	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  diff	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  intersecWon	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  sunion	
  
	
  	
  
aggregate	
  
	
  map	
  
	
  unmap	
  
extract	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  slicing	
  
EdiCng	
  
renameFeature	
  
	
  removeFeature	
  
accessors	
  	
  
	
  copy	
  
	
   	
   	
   	
  	
   	
  	
  
Reasoning	
  	
  
counWng	
   configs	
  
isValid	
  
deads	
  cores	
  
falseOpWonals	
  
cleanup	
  
configuraWon	
  	
  
	
  select	
  
	
  deselect	
  
	
  asFM	
  compare	
  
setOpWonal 	
  	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  setMandatory	
  
setAlternaWves	
  
	
   	
  setOr	
  
	
  
	
  Language	
  FaciliCes	
  
fm1.*	
   fm1.B	
  
modular	
  mechanisms	
  
	
  
	
  
restricted	
  set	
  of	
  types	
  
iterator/condiWonal	
  
asserWon	
  
insert	
  
features	
  
Hello	
  World	
  
97	
  
helloworld.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
Typed	
  language	
  	
  
•  Domain-­‐specific	
  types	
  
–  Feature	
  Model,	
  	
  
–  ConfiguraWon,	
  	
  
–  Feature,	
  	
  
–  Constraint	
  	
  
•  Other	
  types	
  include	
  	
  
–  Set	
  
–  String	
  	
  
–  Boolean,	
  	
  
–  Enum,	
  	
  
–  Integer	
  and	
  Real.	
  	
  
•  A	
  set	
  of	
  operaWons,	
  called	
  operators,	
  are	
  defined	
  for	
  a	
  given	
  type.	
  	
  
98	
  
basics2.fml	
  
Typed	
  language	
  	
  
99	
  
basics2.fml	
  
Typed	
  language	
  	
  
100	
  
basics2.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
ImporCng/ExporCng	
  feature	
  models	
  
101	
  
FAMILIAR
S2T2
TVL
feature-model-synthesis
(visual configurator)
(language)
(language)FaMa
Internal	
  notaWon	
  or	
  by	
  “filename	
  extensions”	
  	
  
basics3.fml	
  
Feature	
  Accessors	
  (1)	
  
102	
  
6Accessors.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
Other	
  constructs	
  
103	
  
6Accessors2.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
ConfiguraCon	
  
104	
  
conf.fml	
   Optional
Mandatory
Xor-Group
Or-Group
105	
  
φ FM
A	
  ^	
  
A	
  ó	
  B	
  ^	
  	
  
C	
  =>	
  A	
  ^	
  
D	
  =>	
  A	
  	
  
Optional
Mandatory
Xor-Group
Or-Group
OperaCons	
  for	
  Feature	
  Models	
  (1)	
  
106	
  
φ
operatorsFM.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
OperaCons	
  for	
  Feature	
  Models	
  (2)	
  
107	
  
φ
operatorsFM2.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
OperaCons	
  for	
  Feature	
  Models	
  (3)	
  
108	
  
operatorsFM3.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
 	
  
	
  	
  
	
  	
   	
  	
  
	
  	
   	
  	
  
	
  	
  
	
  	
   	
  	
  
	
  	
  
	
  	
  
	
  	
  
	
  	
   	
  	
  
	
  	
  
	
  	
  
	
  	
  
	
  	
   	
  	
  
	
  	
  
SoC	
  support	
  =	
  ComposiCon/DecomposiCon	
  
for	
  managing	
  
large,	
  complex	
  and	
  mulCple	
  
feature	
  models	
  
FORM	
  1998,	
  Tun	
  et	
  al.	
  2009	
  (SPLC),	
  Hartmann	
  2008	
  (SPLC),	
  Lee	
  et	
  al.	
  2010,	
  Czarnecki	
  2005,	
  Reiser	
  et	
  al.	
  2007	
  (RE	
  journal),	
  Hartmann	
  
et	
  al.	
  2009	
  (SPLC),	
  Thuem	
  et	
  al.	
  2009	
  (ICSE),	
  Classen	
  et	
  al.	
  2009	
  (SPLC),	
  Mendonca	
  et	
  al.	
  2010	
  (SCP),	
  Dunghana	
  et	
  al.	
  2010,	
  Hubaux	
  et	
  
al.	
  2011	
  (SoSyM),	
  Zaid	
  et	
  al.	
  2010	
  (ER),	
  She	
  et	
  al.,	
  2011	
  (ICSE),	
  etc.	
  
Composing	
  Feature	
  Models	
  (1)	
  
110	
  
aggregateBasics.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
Composing	
  Feature	
  Models	
  (2)	
  
111	
  
aggregate1.fml	
  
Previous	
  
version	
  
Optional
Mandatory
Xor-Group
Or-Group
Composing	
  Feature	
  Models	
  (3)	
  
112	
  
mergeMI.fml	
  
Mathieu	
  Acher,	
  Philippe	
  Collet,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  France	
  «	
  Comparing	
  Approaches	
  for	
  
ImplemenWng	
  Feature	
  Model	
  ComposiWon	
  »	
  ECMFA’10	
  
see	
  also	
  Thuem,	
  Kastner	
  and	
  Batory,	
  ICSE’09	
  
Comparing	
  Feature	
  Models	
  
113	
  
compare.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
Ec2013 tutorial-mb variability-final
Merge	
  IntersecCon:	
  Available	
  Suppliers	
  
115	
  
∩	
  
∩	
  
A	
  customer	
  
has	
  some	
  
requirements	
  
Suppliers?	
  
Products?	
  
In	
  FAMILIAR	
  
116	
  
suppliersExample0.fml	
  
Merge	
  Union:	
  Availability	
  Checking	
  
117	
  
Can	
  suppliers	
  provide	
  all	
  products?	
  
Yes!	
  
“compare”	
  
	
  	
  
	
  
∩	
  
Optional
Mandatory
Xor-Group
Or-Group
In	
  FAMILIAR	
  
118	
  
suppliersExample.fml	
  
Merging	
  operaCon:	
  	
  implementaCon	
  issues	
  
119	
  
How	
  to	
  synthesise	
  a	
  feature	
  model	
  that	
  represents	
  
the	
  union	
  of	
  input	
  sets	
  of	
  configuraCons?	
  
Optional
Mandatory
Xor-Group
Or-Group
T2
MRI
Medical Image
HeaderAnonymized
T1
DICOM
Header excludes DICOM
Header implies Anonymized
Anonymized v Header v ~DICOM v ~T1 v ~T2
Anonymized v Header v DICOM v ~T1 v ~T2
120	
  
Merging	
  operaCon:	
  semanCc	
  issues	
  (2)	
  
φ
Union	
  
IntersecWon	
  	
  
Diff	
  
	
   How	
  to	
  synthesise	
  a	
  feature	
  model	
  that	
  represents	
  
the	
  union	
  of	
  input	
  sets	
  of	
  configuraCons?	
  
Merging	
  operaCon:	
  algorithm	
  
121	
  
φ1
φ2
φ3
φ123
merged	
  proposiWonal	
  formula	
  
T2
MRI
Medical Image
HeaderAnonymized
T1
DICOM
merged	
  hierarchy	
  
+	
  
Set	
  mandatory	
  features	
  
Detect	
  Xor	
  and	
  Or-­‐groups	
  
Compute	
  “implies/excludes”	
  
constraints	
  
How	
  to	
  synthesise	
  a	
  feature	
  
model	
  that	
  represents	
  the	
  
union	
  of	
  input	
  sets	
  of	
  
configuraCons?	
  
see	
  also	
  [Czarnecki	
  SPLC’07	
  or	
  SPLC’12]	
  
Optional
Mandatory
Xor-Group
Or-Group
Merging	
  operaCon:	
  back	
  to	
  hierarchy	
  
122	
  
mergeNonPC.fml	
  
>	
  configs	
  fm4	
  
res12:	
  (SET)	
  {{C;A};{A;B};{A};{A;B;C}}	
   ?	
  Mathieu	
  Acher,	
  Benoit	
  Combemale,	
  Philippe	
  Collet,	
  Olivier	
  Barais,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  
France	
  «	
  Composing	
  your	
  ComposiWons	
  of	
  Variability	
  Models	
  »	
  MODELS’13	
  
Optional
Mandatory
Xor-Group
Or-Group
see	
  also	
  [Acher	
  et	
  al.,	
  ECMFA’10	
  /	
  MODELS’13]	
  
– Well-­‐defined	
  semanWcs	
  
– Guarantee	
  semanWcs	
  properWes	
  by	
  construcWon	
  
– More	
  compact	
  feature	
  models	
  than	
  reference-­‐based	
  
techniques	
  [Schobbens	
  et	
  al.,	
  2007],	
  [Hartmann	
  et	
  al.,	
  2007]	
  
•  Easier	
  to	
  understand	
  
•  Easier	
  to	
  analyze	
  (e.g.,	
  compare	
  with	
  another)	
  
– Applicable	
  to	
  any	
  proposiWonal	
  feature	
  models	
  	
  
•  Full	
  support	
  of	
  proposiWonal	
  constraints	
  	
  
•  Different	
  hierarchies	
  [Van	
  Den	
  Broek	
  et	
  al.,	
  SPLC’2010/2012]	
  
– SyntacWcal	
  strategies	
  fail	
  [Alves	
  et	
  al.,	
  2006],	
  [Segura	
  et	
  al.,	
  2007]	
  
123	
  
Related	
  Works	
  
Ec2013 tutorial-mb variability-final
125	
  
Problem:	
  mulCple	
  „car	
  models“	
  	
  
126	
  
Problem:	
  mulCple	
  „car	
  models“	
  	
  
127	
  
Problem:	
  mulCple	
  „car	
  models“	
  	
  
128	
  
Problem:	
  mulCple	
  „car	
  models“	
  	
  
	
  
#2	
  –	
  boiom-­‐up:	
  elaborate	
  a	
  feature	
  model	
  for	
  each	
  model	
  line	
  and	
  merge	
  them	
  
Two	
  modeling	
  approaches	
  
#1	
  –	
  top-­‐down:	
  specify	
  constraints	
  (e.g.,	
  excludes)	
  of	
  all	
  model	
  lines	
  upfront	
  
	
  
129	
  
#1	
  top-­‐down	
  
130	
  
#1	
  boiom-­‐up	
  
FM_1	
  
FM_2	
  
FM_3	
  
FM_r	
  merge	
  
131	
  
#1	
  boiom-­‐up	
  (FAMILIAR)	
  
FM_1	
  
FM_2	
  
FM_3	
  
FM_r	
  merge	
  
audiMerge.fml	
  
Ec2013 tutorial-mb variability-final
133	
  
Building	
  “views”	
  of	
  a	
  feature	
  model	
  
•  Problem:	
  given	
  a	
  feature	
  model,	
  how	
  to	
  
decompose	
  it	
  into	
  smaller	
  feature	
  models?	
  
•  SemanWcs?	
  
– What’s	
  the	
  hierarchy	
  
– What’s	
  the	
  set	
  of	
  configuraWons?	
  
134	
  
Building	
  “views”	
  of	
  a	
  feature	
  model	
  
A	
  first	
  try	
  
A3 => P1
P2 => A5
R
A2
A5 A6
A1
A3 A4
A
fm0
P3P2P1
P
P1 => P2
A2
A5 A6
A1
A3 A4
A
fmExtraction1
A2
A5 A6
A1
A3 A4
A
fmExtraction2
A3 => A5
A4 => A6
Problem:	
  You	
  can	
  select	
  A3	
  without	
  A5	
  
Hierarchy	
  and	
  ConfiguraCon	
  maier!	
   135	
  
Slicing	
  Operator	
  
W
constraints
E implies D
R implies E
D excludes F
S implies (F and not E)
P
R S
fm1
AV
T U
B C D
E F
Optional
Mandatory
Xor-Group
Or-Group
T
S E D
constraints
E implies D
D implies E
slicing	
  criterion	
  :	
  an	
  arbitrary	
  set	
  of	
  features,	
  relevant	
  for	
  a	
  feature	
  model	
  user	
  
slice	
  :	
  a	
  new	
  feature	
  model,	
  represenWng	
  a	
  projected	
  set	
  of	
  configuraWons	
  	
  
136	
  
Slicing	
  operator:	
  going	
  into	
  details	
  
projected	
  set	
  of	
  configuraCons	
  
137	
  
fm1	
  =	
  {	
  	
  
{A,B,C,D,E,P,R,T,U,W},	
  	
  
{A,B,C,F,P,S,T,U,W},	
  	
  
{A,B,C,D,E,P,R,T,W},	
  	
  
{A,B,C,F,P,S,T,V,W},	
  	
  
{A,B,C,F,P,S,T,U,V,W},	
  	
  
{A,B,C,F,P,S,T,W},	
  	
  
{A,B,C,D,E,P,R,T,V,W},	
  	
  
}	
  
fm1	
  =	
  {	
  	
  
{A,B,C,D,E,P,R,T,U,W},	
  	
  
{A,B,C,F,P,S,T,U,W},	
  	
  
{A,B,C,D,E,P,R,T,W},	
  	
  
{A,B,C,F,P,S,T,V,W},	
  	
  
{A,B,C,F,P,S,T,U,V,W},	
  	
  
{A,B,C,F,P,S,T,W},	
  	
  
{A,B,C,D,E,P,R,T,V,W},	
  	
  
}	
  
fm1p	
  =	
  {	
  	
  
{D,E,T},	
  	
  
{S,T},	
  	
  
{D,E,T},	
  	
  
{S,T},	
  	
  
{S,T},	
  	
  
{S,T},	
  	
  
{D,E,T}	
  
}	
  
fm1p	
  =	
  {	
  	
  
{D,E,T},	
  	
  
{S,T},	
  	
  
}	
  
W
constraints
E implies D
R implies E
D excludes F
S implies (F andnot E)
P
R S
fm1
AV
T U
B C D
E F
Optional
Mandatory
Xor-Group
Or-Group
+	
  
T
S E D
constraints
E implies D
D implies E
φs1
existenBal	
  
quanBficaBon	
  
of	
  features	
  
not	
  included	
  
in	
  the	
  slicing	
  
criterion	
  
138	
  
fm1p	
  =	
  {	
  	
  
{D,E,T},	
  	
  
{S,T}	
  
}	
  
Slicing	
  operator:	
  going	
  into	
  details	
  
synthesizing	
  the	
  corresponding	
  feature	
  model	
  
S	
   E	
   D	
  
T	
  
W
constraints
E implies D
R implies E
D excludes F
S implies (F andnot E)
P
R S
fm1
AV
T U
B C D
E F
φ1
Mathieu	
  Acher,	
  Philippe	
  Collet,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  France	
  «	
  SeparaWon	
  of	
  Concerns	
  in	
  
Feature	
  Modeling:	
  Support	
  and	
  ApplicaWons	
  »	
  AOSD’12	
  
Optional
Mandatory
Xor-Group
Or-Group
T
S E D
constraints
E implies D
D implies E
139	
  
Slicing	
  operator	
  with	
  FAMILIAR	
  (1)	
  
W
constraints
E implies D
R implies E
D excludes F
S implies (F andnot E)
P
R S
fm1
AV
T U
B C D
E F
slicingOp2.fml	
  
Optional
Mandatory
Xor-Group
Or-Group
140	
  
Slicing	
  with	
  FAMILIAR	
  (2)	
  
slicingOp.fml	
  
From	
  marke.ng,	
  
customers,	
  product	
  
management	
  	
  
From	
  exis.ng	
  so@ware	
  
assets	
  	
  (technical	
  variability)	
  
Metzger,	
  Heymans	
  et	
  al.	
  “DisambiguaBng	
  the	
  DocumentaBon	
  of	
  Variability	
  in	
  Sofware	
  Product	
  
Lines:	
  A	
  SeparaBon	
  of	
  Concerns,	
  FormalizaBon	
  and	
  Automated	
  Analysis“	
  (RE’07)	
  
V1 ⬄ f1
V2 ⬄ f2
V3 ⬄ f3
From	
  marke.ng,	
  
customers,	
  product	
  
management	
  	
  
From	
  exis.ng	
  
so@ware	
  assets	
  	
  
realizability	
  
usefulness	
  
Optional
Mandatory
Xor-Group
Or-Group
Realizability	
  checking	
  
aggregate	
  
{{V1,V3,V2,VP1},	
  
{V1,VP1},	
  
{V3,VP1},	
  	
  
{VP1}}	
  	
  
merge	
  diff	
  
(“unrealizable	
  products”
	
  
φ
1
slice	
  (“realizable	
  part”)	
  
2
3 compare	
  
4	
  
Mathieu	
  Acher,	
  Philippe	
  Collet,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  France	
  «	
  SeparaWon	
  of	
  Concerns	
  in	
  
Feature	
  Modeling:	
  Support	
  and	
  ApplicaWons	
  »	
  AOSD’12	
  	
  
Optional
Mandatory
Xor-Group
Or-Group
With	
  FAMILIAR	
  
144	
  
realizibility.fml	
  
Ec2013 tutorial-mb variability-final
146	
  
RevisiCng	
  Merge:	
  	
  
Aggregate	
  +	
  Slice	
  
Optional
Mandatory
Xor-Group
Or-Group
147	
  
RevisiCng	
  Aggregate,	
  	
  
Merge	
  and	
  Slice:	
  	
  
	
  
mergeWithAggregateMI.fml	
  
Mathieu	
  Acher,	
  Benoit	
  Combemale,	
  Philippe	
  Collet,	
  Olivier	
  Barais,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  
France	
  «	
  Composing	
  your	
  ComposiWons	
  of	
  Variability	
  Models	
  »	
  MODELS’13	
  
Optional
Mandatory
Xor-Group
Or-Group
148	
  
Mathieu	
  Acher,	
  Benoit	
  Combemale,	
  Philippe	
  Collet,	
  Olivier	
  Barais,	
  Philippe	
  Lahire,	
  Robert	
  B.	
  
France	
  «	
  Composing	
  your	
  ComposiWons	
  of	
  Variability	
  Models	
  »	
  MODELS’13	
  
149	
  
φ FM
	
  
	
  
	
  
	
  
	
  
	
  
Feature	
  Model	
  Synthesis	
  Problem	
  
[Czarnecki	
  et	
  al.,	
  SPLC’07]	
  
[She	
  et	
  al.,	
  ICSE’11]	
  
[Andersen	
  et	
  al.,	
  SPLC’12]	
  
A	
  ^	
  
A	
  ó	
  B	
  ^	
  	
  
C	
  =>	
  A	
  ^	
  
D	
  =>	
  A	
  	
  
φ
	
  
	
  
	
  
	
  
	
  
	
  
	
  
« How to synthesise an
accurate (w.r.t. the set of constraints/configurations)
meaningful (maintainable by a user), and
unique
feature model? » 
hip://familiar-­‐project.github.com/	
  
φ(SAT solvers or
Binary Decision Diagrams)
The	
  knowledge	
  can	
  be:	
  
	
  	
  
inconsistent	
  (e.g.,	
  root	
  feature	
  specified	
  is	
  not	
  possible)	
  
consistent	
  and	
  incomplete	
  (i.e.,	
  synthesis	
  algorithm	
  needs	
  
addiWonal	
  informaWon)	
  
consistent,	
  «	
  parCal	
  »	
  (e.g.,	
  not	
  all	
  the	
  hierarchy	
  is	
  specified)	
  and	
  
actually	
  complete	
  	
  
Mathieu	
  Acher,	
  Patrick	
  Heymans,	
  Anthony	
  Cleve,	
  Jean-­‐Luc	
  Hainaut,	
  Benoit	
  Baudry	
  «	
  Support	
  for	
  
Reverse	
  Engineering	
  and	
  Maintaining	
  Feature	
  Models	
  »	
  VaMoS’13	
  
#1	
  Reverse	
  Engineering	
  Scenarios	
  
•  [Haslinger	
  et	
  al.,	
  WCRE’11],	
  [Acher	
  et	
  al.,	
  VaMoS’12]	
  
φ
V
DAd OT M KAe CP R S
C requires T
Ae requires T
S equals M
V
DAd OT KAe SP R M
C requires T
S equals M
C
0..1
#2	
  Refactoring	
  
•  [Alves	
  et	
  al.,	
  GPCE’06],	
  [Thuem	
  et	
  al.,	
  ICSE’09]	
  
φ
V
DAd OT M KAe CP R S
C requires T
Ae requires T
S equals M
#3	
  Re-­‐Engineering	
  Feature	
  Models	
  of	
  	
  	
  	
  	
  
repository	
  
•  For	
  each	
  FM	
  we	
  execute	
  the	
  following	
  FAMILIAR	
  script…	
  
	
  
•  …	
  And	
  we	
  «compare»	
  syntacWcally	
  fm1	
  and	
  fm2	
  
•  semanWcal	
  comparison	
  is	
  not	
  needed:	
  we	
  know	
  that	
  they	
  are	
  refactoring	
  by	
  
construcWon	
  (good	
  test	
  case	
  though	
  ;-­‐))	
  
•  Results:	
  
–  147	
  synthesised	
  FMs	
  (69	
  %)	
  were	
  exactly	
  the	
  same	
  as	
  input	
  FMs	
  ;	
  	
  
–  40	
  synthesised	
  FMs	
  (19%)	
  were	
  correcWons	
  of	
  input	
  FMs	
  ;	
  	
  
–  24	
  synthesised	
  FMs	
  (12%)	
  were	
  different	
  (knowledge	
  needed)	
  
•  another	
  set	
  of	
  cross-­‐tree	
  constraints	
  was	
  synthesised.	
  	
  
•  feature	
  group	
  conflicts	
  in	
  six	
  cases	
  
SpecificaCon	
  of	
  the	
  hierarchy	
  is	
  the	
  main	
  issue	
  
φ
φ
	
  
	
  
	
  
	
  
	
  
	
  
FAMILIAR	
  
« Give me a formula
and some knowledge,
I will synthesise
an accurate,
meaningful,
unique
feature model » 
#1	
  Breathing	
  knowledge	
  into	
  feature	
  model	
  synthesis	
  
	
  formal	
  specificaWon	
  (consistency	
  and	
  completeness)	
  
	
  concrete	
  syntax	
  and	
  tooling	
  suport	
  
#2	
  PracCcal	
  applicaCons	
  
	
  reverse	
  engineering,	
  refactoring/re-­‐engineering	
  of	
  feature	
  models	
  
	
  	
  
hip://familiar-­‐project.github.com/	
  
Automated	
  support	
  is	
  highly	
  
needed	
  (ongoing	
  work)	
  
[MOTIVATION/PROBLEM]	
  Why	
  modeling	
  and	
  managing	
  Variability	
  
does	
  and	
  will	
  maber	
  (30’)	
  
[SOLUTION	
  FOR	
  MANAGING	
  FEATURE	
  MODELS]	
  Managing	
  Variability	
  
Models	
  with	
  FAMILIAR	
  (1h45’)	
  
	
  
	
  
[SOLUTION	
  FOR	
  MODEL-­‐BASED	
  DERIVATION	
  OF	
  PRODUCT]	
  Model-­‐based	
  
variability	
  engineering:	
  examples,	
  support	
  and	
  open	
  issues	
  
(45’)	
  
156	
  
Plan	
  
Variability	
  AbstracCon	
  
Model	
  (VAM)	
  
ConfiguraCon	
  
(resoluCon	
  model)	
  
Domain	
  Artefacts	
  
(e.g.,	
  models)	
  
SoSware	
  Generator	
  
(derivaCon	
  engine)	
  
ü	
   ü	
  
Variability	
  
RealizaCon	
  
Model	
  
(VRM)	
  
Configurations
Derivation
Process
Models of
the
“system”
Feature
Model
How to
realize the
variability
Printer
´Blockª
mainSupply:MainPower1
Attributes
Operations
powerCtrl
emgSupply:EmgPower1
Attributes
threshold:int
Operations
powerCtrl
inputSection1
highSpeedConnector1
Attributes
Operations
MainPowerCtrl EmgPowerCtrl
MainPower
´Blockª
Values
Operations
powerCtrl
EmgPower
´Blockª
Values
threshold:int
powerCtrl
VariaCon	
  Points	
  over	
  base	
  model	
  
:ObjectExistence	
   :SlotValueAssignment	
  
CVL variation points
SYSML (base model) elements
:ObjectExistence	
   :ObjectExistence	
  
§  Variability	
  in	
  this	
  example:	
  
  Part	
  EmergencySupply	
  is	
  
opWonal	
  
  Part	
  HighSpeedConnector	
  is	
  
opWonal	
  
  Port	
  EmgPowerCtrl	
  on	
  block	
  
Printer	
  is	
  opWonal	
  
  Value	
  of	
  abribute	
  threshold	
  in	
  
block	
  EmergencyPower	
  is	
  
variable	
  
Adapted	
  from	
  the	
  CVL	
  tutorial	
  at	
  SPLC’12	
  by	
  Oystein	
  Haugen,	
  Andrezj	
  Wasowski,	
  Krzysztof	
  
Czarnecki	
  	
  
Printer
´Blockª
mainSupply:MainPower1
Attributes
Operations
powerCtrl
emgSupply:EmgPower1
Attributes
threshold:int
Operations
powerCtrl
inputSection1
highSpeedConnector1
Attributes
Operations
MainPowerCtrl EmgPowerCtrl
MainPower
´Blockª
Values
Operations
powerCtrl
EmgPower
´Blockª
Values
threshold:int
powerCtrl
(Aiributed)	
  
Feature	
  Model	
  	
  
Printer	
  
EmergencyPower	
  
threshold:Int	
  
Variation
points
HighSpeed	
  &	
  	
  threshold>100	
  	
  
	
  EmergencyPower	
  
HighSpeed	
  
:ObjectExistence	
   :SlotValueAssignment	
  :ObjectExistence	
   :ObjectExistence	
  
Based	
  Model	
  	
  
Adapted	
  from	
  the	
  CVL	
  tutorial	
  at	
  SPLC’12	
  by	
  Oystein	
  Haugen,	
  Andrezj	
  Wasowski,	
  Krzysztof	
  
Czarnecki	
  	
  
Variability	
  RealizaCon	
  Layer	
  
VariaCon	
  points	
  in	
  CVL	
  
•  VariaWon	
  Points	
  refer	
  to	
  Base	
  objects	
  
•  VariaWon	
  Points	
  define	
  the	
  base	
  model	
  
modificaWons	
  precisely	
  
•  There	
  are	
  different	
  kinds	
  of	
  VariaWon	
  Points	
  
– Existence	
  (object	
  or	
  link)	
  
– Value	
  assignment	
  
– SubsWtuWon	
  
– Opaque	
  variaWon	
  point	
  
– Configurable	
  Unit	
  
Adapted	
  from	
  the	
  CVL	
  tutorial	
  at	
  SPLC’12	
  by	
  Oystein	
  Haugen,	
  Andrezj	
  Wasowski,	
  Krzysztof	
  
Czarnecki	
  	
  
Derivation of Traffic Lights
Models
Joao	
  Bosco	
  Ferreira	
  
Filho	
  (PhD	
  student)	
  
Traffic Lights
. Traffic Lights' behaviour can be modelled using Finite
State Machines
Traffic Lights FSM
Traffic Lights FSM
OBJECTIVE:
Produce the finite state machine associated with
each traffic light configuration
. Simplification:
- Green Light
- Red Light
- Yellow Light
Base model
. Define the DSL:
1. Create an Ecore modelling project
2. Define the metamodel
3. Generate the model, the edit and the editor code
4. Export them as plugins
DSL metamodel
Base model
. Create the base model:
1. Create a Modelling project
2. Create a new model in the DSL
Base model
. Create the base model:
1. Create a Modelling project
2. Create a new model in the DSL
CVL model
. Create the CVL model:
1. Create a new CVL model in the modelling project.
Select VPackage as the Model object
2. Right click on the project, select Viewpoints selection.
Check the three of them
3. Define the VAM, Resolution model and VRM
VAM
Resolution model
Resolution model
VRM
VRM
Product derivation
Derived FSM
Visualisation of products in a
web configurator
Marianela Ciolfi Felice
(MSc student) 	
  
Ec2013 tutorial-mb variability-final
Marks	
  &	
  Spencer	
  web	
  configurator	
  
§  High visual quality
§  Coherence and stability
§  Interactiveness
§  Performance
§  Automatic and comprehensive
update method
Marianela Ciolfi Felice and Joao Bosco Ferreira Filho and Mathieu Acher and Arnaud
Blouin and Olivier Barais « Interactive Visualisation of Products in Online Configurators:
A Case Study for Variability Modelling Technologies » MAPLESCALE’13 (to appear)
Anticipating all possible
combinations
§  10 configuration options
§  10 possible values for each of
them
10.000.000.000 combinations!
Composing the
visualisation
PRODUCT CONFIGURATION VISUAL REPRESENTATION
Models	
  
HTML	
  
jpg,	
  png,	
  ...,	
  files	
  
SVG	
  files	
  
Javascript	
  
3D	
  
models	
  
Feature	
  
models	
  
Configurations
Derivation
Process
Visual
representation
of a product
Feature
Model
How to
realize the
variability
Visual
elements
. Simplification:
- Fabric
- Collar
- Pocket (optional)
- Handkerchief (optional)
	
  	
  
Shirts web configurator
Shirts web configurator
OBJECTIVE:
Produce the visual representation associated with
each shirt configuration
. Simplification:
- Fabric
- Collar
- Pocket (optional)
- Handkerchief (optional)
	
  	
  
Feature model
- Implicit boolean attribute existence
- No constraints
Base model
. Define the DSL:
1. Create an Ecore modelling project
2. Define the metamodel
3. Generate the model, the edit and the editor code
4. Export them as a plugin
DSL metamodel
Base model
. Create the base model:
1. Create a Modelling project
2. Create a new model in the DSL
Base model
. Create the base model:
1. Create a Modelling project
2. Create a new model in the DSL
CVL model
. Create the CVL model:
1. Create a new CVL model in the modelling project. Select VPackage as the Model
object
2. Right click on the project. Select Viewpoints selection. Check the three of them
3. Define the VAM, Resolution model and VRM
VAM
VAM
VAM
Suggestion:
Set the choices' default resolution
to:
- True for mandatory features
- False for optional features
Resolution model
Resolution model
VRM
VRM
Product derivation
Product derivation
Summary:	
  Variability	
  Model	
  Management	
  
202	
  202	
  202	
  
[MOTIVATION/PROBLEM]	
  Why	
  modeling	
  and	
  managing	
  Variability	
  
does	
  and	
  will	
  maber	
  (30’)	
  
[SOLUTION	
  FOR	
  MANAGING	
  FEATURE	
  MODELS]	
  Managing	
  Variability	
  
Models	
  with	
  FAMILIAR	
  (1h45’)	
  
	
  
	
  
[SOLUTION	
  FOR	
  MODEL-­‐BASED	
  DERIVATION	
  OF	
  PRODUCT]	
  Model-­‐based	
  
variability	
  engineering:	
  examples,	
  support	
  and	
  open	
  issues	
  
(45’)	
  
203	
  
Key	
  Insights	
  
(ongoing)	
  Comprehensive	
  model-­‐based	
  
product	
  line	
  support	
  
	
  
Reverse	
  engineering	
  
Automated	
  Analysis	
  
Languages,	
  API/DSLs	
  
EvaluaCon	
  (European	
  projects,	
  long-­‐term	
  collaboraCon	
  with	
  Thales,	
  open	
  source	
  
systems)	
  
	
  
204	
  
204	
  
 	
  
	
  	
  
	
  	
   	
  	
  
	
  	
  
?	
  
205	
  

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Ec2013 tutorial-mb variability-final

  • 1. Mathieu  Acher,  Benoit  Combemale,  Olivier  Barais   Model-­‐Based     Variability  Management    
  • 2. 2   Research  in  so6ware   engineering.   -­‐  8  faculty  members   -­‐  35  researchers  and   engineers  on  projects  
  • 3. We’re  hiring!     engineers,  PhD  students,  post-­‐docs   Variability  /  Product  lines     Model-­‐driven  Engineering   Language  Engineering  (e.g.,  DSLs)   Scala   3   3   European  Projects       Industrial  CollaboraCons     Academics  partners  
  • 4. Acknowledgments  (la  famille)   Marianela  Ciolfi  Felice     Joao  Bosco  Ferreira  Filho   Guillaume  Bécan   Suresh  Pilay     Sana  Ben  Nasr   (MSc/PhD  students,     University  of  Rennes  1)     Prof.  Philippe  Collet   Prof.  Philippe  Lahire     (University  of  Nice  Sophia  AnWpolis)     Prof.  Robert  B.  France     (Colorado  State  University)     Prof.  Patrick  Heymans     (University  of  Namur)  
  • 5. Audience   •  No  pre-­‐requisite  background!   •  Targeted  Audience   •  Academics  or  pracWWoners     •  Curious  guys:  e.g.,  PhD  students  or  modellers  unaware  of…     –  Variability  and  so6ware  product  lines  (SPLs)   –  Variability  modelling     –  ConfiguraWon   •  MDE  guys:  people  involved  or  interested  in  the  development  of   model  management  tools   –  e.g.,  model  composiWon/decomposiWon   •  SPL  guys:  advances  that  want  to  learn  new  techniques   5  
  • 6. At  the  end  of  the  tutorial…   •  You  will  have  an  overview  of  what’s  going  on  in  the  field  of     variability  and  model-­‐based  so6ware  product  line  engineering   •  You  will  be  able  to  go  further  with  the  languages  and  modelling   techniques   •  so  to  reuse  them  in  pracWcal  or  academic  contexts     •  SupporWng  material:   hbps://github.com/FAMILIAR-­‐project/familiar-­‐documentaWon/blob/ master/presentaWons/EC2013/README.md     •  slides  of  the  tutorial   •  related  arWcles,     •  FAMILIAR  scripts,   •  CVL  models,   •  and  packaged  tools  to  interacWvely  play  with  the  models  during  the   tutorial   6  
  • 7. Differences  with  previous  tutorials  at   SPLC’12  /  MODELS’12   •  Larger  perspecWve/moWvaWon   •  Including  modelling/language/architectural  examples     •  Not  only  about  feature  models   •  not  only  about  FAMILIAR   •  but  new  techniques  for  reverse  engineering  (VaMoS’13)  and  composing   (MODELS’13)  feature  models  will  be  presented     •  Model-­‐based  product  line  engineering   •  Common  Variability  Language  (CVL)   FAMILIAR  is  now  a  project    not  only  a  language  for  managing  feature  models!   7  
  • 8. [MOTIVATION/PROBLEM]  Why  modeling  and  managing  Variability   does  and  will  maber  (30’)   [SOLUTION  FOR  MANAGING  FEATURE  MODELS]  Managing  Variability   Models  with  FAMILIAR  (1h45’)       [SOLUTION  FOR  MODEL-­‐BASED  DERIVATION  OF  PRODUCT]  Model-­‐based   variability  engineering:  examples,  support  and  open  issues   (45’)   8   Plan  
  • 9. [MOTIVATION/PROBLEM]  Why  modeling  and  managing  Variability   does  and  will  maber  (30’)   [SOLUTION  FOR  MANAGING  FEATURE  MODELS]  Managing  Variability   Models  with  FAMILIAR  (1h45’)       [SOLUTION  FOR  MODEL-­‐BASED  DERIVATION  OF  PRODUCT]  Model-­‐based   variability  engineering:  examples,  support  and  open  issues   (45’)   9   Plan  
  • 10. 10   So6ware-­‐intensive  systems   come  in  many  variants    
  • 11. 11  
  • 15. Features  in  MicrosoS  Office   15  
  • 17. 17  
  • 18. Variability     “the  ability  of  a  system  to  be  efficiently  extended,   changed,  customized  or  configured  for  use  in  a   parCcular  context”     Mikael  Svahnberg,  Jilles  van  Gurp,  and  Jan  Bosch  (2005)  
  • 19. «  A  set  of  programs  is  considered  to  consWtute   a  family,  whenever  it  is  worthwhile  to  study   programs  from  the  set  by  first  studying  the   common  properCes  of  the  set  and  then   determining  the  special  properCes  of  the   individual  family  members  »             David  L.  Parnas  —  ‘‘On  the  design  and  development  of  program   families’’  in  TransacCons  on  SoSware  Engineering,  SE-­‐2(1):1–9,  1976    19   aka  Variability  
  • 20. Variability     “the  ability  of  a  system  to  be  efficiently   extended,  changed,  customized  or   configured  for  use  in  a  parCcular  context”     Mikael  Svahnberg,  Jilles  van  Gurp,  and  Jan  Bosch  (2005)       20  
  • 21. 21  21   Extensible  architectures   (eg  plugins-­‐based)   ConfiguraCon   files   System   Preferences   Configurators   Source  code   Build   systems   Comparison  of  *   Structural  or  behavorial     models   External  Variability   Internal  Variability   Variability  @  run.Cme  
  • 22. 22   «  Feature  Model  ExtracWon  from  Large  CollecWons  of  Informal  Product  DescripWons  »     Jean-­‐Marc  Davril,  Edouard  Delfosse,  Negar  Hariri,  Mathieu  Acher,  Jane  Cleland-­‐Huang,  Patrick   Heymans  (ESEC/FSE’13)  
  • 23. 23   «  The  Anatomy  of  a  Sales  Configurator:  An  Empirical  Study  of  111  Cases  »  Ebrahim  Khalil  Abbasi,   Arnaud  Hubaux,  Mathieu  Acher,  QuenWn  Boucher,  and  Patrick  Heymans  (CAiSE’13)  
  • 24. 24   «  ExtracWon  and  EvoluWon  of  Architectural  Variability  Models  in  Plugin-­‐based  Systems  »       Mathieu  Acher,  Anthony  Cleve,  Philippe  Collet,  Philippe  Merle,  Laurence  Duchien,  Philippe   Lahire  ECSA/SoSyM’13  
  • 25. If  you’re  able  to  master  variability…   •  Reduce  development  costs     •  Reduce  cerWficaWon  costs     •  Shorten  Wme-­‐to-­‐market     •  But,  are  you  able?     – developing,  verifying,  cerWfying  billions  of  variants  is   challenging!     25  
  • 26. Variability = Complexity ChrisWan  Kästner  slide  
  • 27. a  unique  variant  for  every   person  on  this  planet   33  features   opWonal,  independent   ChrisWan  Kästner  slide  
  • 28. 320  features     more  variants  than  esWmated      atoms  in  the  universe   opWonal,  independent  
  • 29. 2000  features   10000   features   ChrisWan  Kästner  slide  
  • 30. 30       Avoid  solving  the  same  problem!        2,  3…n  Cmes     AutomaCon?  
  • 33.     Goal:  So6ware  mass  customizaWon     /  AdapWve  and  configurable  systems     Problem:  Variability  =  Complexity     Approach:  Model-­‐based  variability  management   33   Why  managing  Variability     does  (and  will)  maier  
  • 34. 34   So6ware-­‐intensive  systems   come  in  many  variants     Model-­‐based     Variability  Management  
  • 35.   Modeling  Variability     CommunicaCve     AnalyCc     GeneraCve     35  
  • 36. 36  
  • 38. 38   Factoring  out  commonaliCes    for  Reuse  [Krueger  et  al.,  1992]  [Jacobson  et  al.,  1997]               Managing  variabiliCes      for  So6ware  Mass  CustomizaCon  [Bass  et  al.,  1998]  [Krueger  et  al.,  2001],  [Pohl  et  al.,  2005]      
  • 39. Mobile 3G+ 3G GPS Maps Camera ü   ü   ü   Mobile 3G+ 3G GPS Maps Camera Domain/Variability  Model   ConfiguraCon   SoSware  Generator   Domain  Artefacts       Domain     Engineering   ApplicaCon     Engineering   «  the  investments  required  to  develop  the  reusable  arBfacts  during   domain  engineering,  are  outweighed  by  the  benefits  of  deriving  the   individual  products  during  applica.on  engineering  »   Jan  Bosch  et  al.  (2004)      
  • 40. 40   99%  domain  engineering,     1%  applicaCon  engineering?   –  specifies  what  you  want  (click,  click,  click)  a  customized   product  is  automaWcally  built  for  you   –  Iterate  the  process  for  n  products   Amount of effort Application Engineering More Sophisticated Technology Domain Engineering
  • 41. Variability  AbstracCon   Model  (VAM)   ConfiguraCon   (resoluCon  model)   Domain  Artefacts   (e.g.,  models)   SoSware  Generator   (derivaCon  engine)   ü   ü   Variability   RealizaCon   Model   (VRM)  
  • 42. 42  
  • 44. (another  research  area/applicaWon:   adapWve  systems  aka  dynamic  so6ware  product  lines   Models@run.Wme)   hip://www.kevoree.org   from  Cloud  stack  to   embedded  devices  
  • 46. Variability  Handling  in  AUTOSAR   Body   control   Low-­‐end  light-­‐ control   AdapWve-­‐curve   light-­‐control   Feature  Modeling   (Variability  abstracWon)   Generic  Template   (Variability  RealizaWon)   LightType   …   System   constant   Low  End   High  End   Car   1..1 Feature   v.  4.04  (upcoming)   v.  4.03   Low  End  ==  1   High  End  ==  1   VariaWon   point   Adapted  from  the  CVL  tutorial  at  SPLC’12  by  Oystein  Haugen,  Andrezj  Wasowski,  Krzysztof  Czarnecki    
  • 47. Variability  Handling  in  AUTOSAR  (2)   Feature  Modeling   (Variability  abstracWon)   Generic  Template   (Variability  RealizaWon)   Low  End   High  End   Car   1..1 Body   control   Low-­‐end   light-­‐control  
  • 48. VariaCon  Point  Types   •  Variability  is  applied  to  different  parts  of  the   metamodel   – AggregaWon,  associaWon,  abribute  value,  property   set   •  ResulWng  variability   – OpWonal  component   – OpWonal  port   – OpWonal  connector   – Parameter  variability   Component   Port   Adapted  from  the  CVL  tutorial  at  SPLC’12  by  Oystein  Haugen,  Andrezj  Wasowski,  Krzysztof  Czarnecki    
  • 49. 49   «  Mapping  Features  to  Models:  A  Template  Approach  Based  on  Superimposed  Variants»   Krzysztof  Czarnecki  and  Michal  Antkiewicz  GPCE’05  
  • 50. 50   «  Mapping  Features  to  Models:  A  Template  Approach  Based  on  Superimposed  Variants»   Krzysztof  Czarnecki  and  Michal  Antkiewicz  GPCE’05  
  • 51. 51   «  Mapping  Features  to  Models:  A  Template  Approach  Based  on  Superimposed  Variants»   Krzysztof  Czarnecki  and  Michal  Antkiewicz  GPCE’05  
  • 52. 52   «  Mapping  Features  to  Models:  A  Template  Approach  Based  on  Superimposed  Variants»   Krzysztof  Czarnecki  and  Michal  Antkiewicz  GPCE’05  
  • 53. Safe  composiWon?  No!   53   «Verifying  Feature-­‐Based  Model  Templates  Against   Well-­‐Formedness  OCL  Constraints  »  Krzysztof  Czarnecki  Krzysztof  Pietroszek  GPCE’06  
  • 54. Ooops   54   «Verifying  Feature-­‐Based  Model  Templates  Against   Well-­‐Formedness  OCL  Constraints  »  Krzysztof  Czarnecki  Krzysztof  Pietroszek  GPCE’06  
  • 55. Another  approach   55   «  Reconciling  AutomaWon  and  Flexibility  in  Product  DerivaWon  »  Gilles  Perrouin,  Jacques  Klein,   Nicolas  Guelfi,  Jean-­‐Marc  Jézéquel  SPLC’08  
  • 56. 56   «  Reconciling  AutomaWon  and  Flexibility  in  Product  DerivaWon  »  Gilles  Perrouin,  Jacques  Klein,   Nicolas  Guelfi,  Jean-­‐Marc  Jézéquel  SPLC’08   Merging-­‐based  DerivaCon  of  Product  
  • 58. Variability  at  the  language  level     58 Variability  in   Metamodeling   •  SemanWc  variaWon  point   •  DSML  Families   •  Knowledge  capitalizaWon   •  Language  Engineering     Variability  in   Modeling   Variability Variability
  • 59.                Engineering  SemanCcs  in  Modeling  Languages   59 Abstract Syntax (AS) Concrete Syntax (CS) Semantics Domain (SD) Mac Mas •  Variability  in  metamodeling  (DSML  families,  variaWon  point...):   –  Abstract  syntax:  staWc  introducWon  (AOM),  inheritance  (OOP)   –  Concrete  syntax:  view  point  (OBEO  Designer)   –  SemanWcs:  sWll  a  problem!  how  to  define  and  manage  semanBc   variability  (in  the  DSML  and  the  associated  tools)?  
  • 60. DSL4   DSL3  DSL2   DSL1   Language  Family   (expresiveness,  semanWc  variaWon  point,     implementaWon  variaWon  point,  viewpoints,  tooling,  etc.)   RM   dsl1   RM   dsl2   RM   dsl3  RM   dsl4   Challenge1:  Modular   Language  Design   Challenge3:   Language   ComposiWon   Challenge2:   Variability  Modeling   «  Variability  Management  in  Modeling  Languages  »  Suresh  Pilay  PhD  thesis  (ongoing)  
  • 61. DSL   Variability   model   CVL   Base     model   Generic  &     Standardized   resoluCon   models   Focused  on     a  domain   Execute  CVL       Resolved     models   DescripWon  of   possible   variaWons  in   the  system   Domain   model  of  a   parWcular   family  of   system   SelecWon  of  a  set   of  opWons  in  the   variaWon  model   Family  of  systems  fully   described  in  the   domain  specific   language.   All  regular  DSL  tools   can  be  applied  to  these   models   61   RealizaCon   model   Language Units Language Features how to realize the features Configuration of languages Derivation Process Languages «  Variability  Management  Modeling  Languages  »  Suresh  Pilay  PhD  thesis  (ongoing)  
  • 63. 63   «  ExtracWon  and  EvoluWon  of  Architectural  Variability  Models  in  Plugin-­‐based  Systems  »       Mathieu  Acher,  Anthony  Cleve,  Philippe  Collet,  Philippe  Merle,  Laurence  Duchien,  Philippe   Lahire  ECSA/SoSyM’13  
  • 64. 64   «  ExtracWon  and  EvoluWon  of  Architectural  Variability  Models  in  Plugin-­‐based  Systems  »       Mathieu  Acher,  Anthony  Cleve,  Philippe  Collet,  Philippe  Merle,  Laurence  Duchien,  Philippe   Lahire  ECSA/SoSyM’13   FraSCAti SCAParser Java Compiler JDK6 JDT Optional Mandatory Alternative- Group Or-Group Assembly Factory resthttp Binding MMFrascati Component Factory Metamodel MMTuscany constraints rest requires MMFrascati http requires MMTuscany FM1 Variability  Model  
  • 65. 65   Variability  Model   FraSCAti SCAParser Java Compiler JDK6 JDT Optional Mandatory Alternative- Group Or-Group Assembly Factory resthttp Binding MMFrascati Component Factory Metamodel MMTuscany constraints rest requires MMFrascati http requires MMTuscany FM1 FraSCAC  Architecture   Set  of    Safe   Variants   authorized  by   FraSCAC   Scope  is   too  large  
  • 66. Illegal    Variant     66  
  • 67. 67   FraSCAC  Architecture   FraSCAti SCAParser Java Compiler JDK6 JDT Optional Mandatory Alternative- Group Or-Group Assembly Factory resthttp Binding MMFrascati Component Factory Metamodel MMTuscany constraints rest requires MMFrascati http requires MMTuscany FM1 Feature  Model   FraSCAti SCAParser Java Compiler JDK6 JDT Optional Mandatory Alternative- Group Or-Group Assembly Factory resthttp Binding MMFrascati Component Factory Metamodel MMTuscany constraints rest requires MMFrascati http requires MMTuscany FM1 ConfiguraCon   Derived  FraSCAC  Architecture  
  • 68. [MOTIVATION/PROBLEM]  Why  modeling  and  managing  Variability   does  and  will  maber  (30’)   [SOLUTION  FOR  MANAGING  FEATURE  MODELS]  Managing  Variability   Models  with  FAMILIAR  (1h45’)       [SOLUTION  FOR  MODEL-­‐BASED  DERIVATION  OF  PRODUCT]  Model-­‐based   variability  engineering:  examples,  support  and  open  issues   (45’)   68   Plan  
  • 69. Variability  Model   ConfiguraCon   Domain  Artefacts  (e.g.,  source  code)   SoSware  Generator   Modeling   variability     is  crucial   ü   ü  
  • 72. 72  72   Extensible  architectures   (plugins-­‐based)   ConfiguraCon   files   System   Preferences   Configurators   Source  code   Build  systems   Comparison  of  Product  
  • 73.   Variability  AbstracCon  Model   (VAM)     CommunicaCve     AnalyCc     GeneraCve     73   not, and, or, implies
  • 74. Variability  Model   Feature  Model:  de  facto  standard   •  Research     –  2500+  citaWons  of  [Kang  et  al.,  1990]  on  Google  Scholar     –  Central  to  many  generaWve  approaches   •  at  requirements  or  code  level   –  Tools  &  Languages  (GUIDSL/FeatureIDE,  SPLOT,  FaMa,   etc.)   •  Industry     –  Tools  (Gears,  pure::variants),     •  Common  Variability  Language  (CVL)   74  
  • 77. Feature  Models  (Background)   77   Hierarchy:  rooted  tree     Variability:     •  mandatory,     •  opWonal,     •  Groups:  exclusive  or  inclusive  features   •  Cross-­‐tree  constraints   Optional Mandatory Xor-Group Or-Group
  • 78. 78   Hierarchy  +  Variability     =     set  of  valid  configuraCons   {CarEquipment,  Comfort,  DrivingAndSafety,  Healthing,  AirCondiWoning,  FrontFogLights}   configuraCon  =  set  of  features  selected   Optional Mandatory Xor-Group Or-Group
  • 79. 79   Hierarchy  +  Variability     =     set  of  valid  configuraCons   {CarEquipment,  Comfort,  DrivingAndSafety,  Healthing,  AirCondiWoning}   configuraCon  =  set  of  features  selected   Optional Mandatory Xor-Group Or-Group
  • 80. 80   Hierarchy  +  Variability     =     set  of  valid  configuraCons   Optional Mandatory Xor-Group Or-Group {CarEquipment,  Comfort,  DrivingAndSafety,  Healthing,  AirCondiWoning,   AutomaWcHeadLights}   configuraCon  =  set  of  features  selected   ü   ü   ü   ü   ü   ü  
  • 81. 81   Hierarchy  +  Variability     =     set  of  valid  configuraCons   Optional Mandatory Xor-Group Or-Group {AirCondiWoning,  FrontFogLights}   {AutomaWcHeadLights,  AirCondiWoning,  FrontFogLights}   {AutomaWcHeadLights,  FrontFogLights,  AirCondiWoningFrontAndRear}   {AirCondiWoningFrontAndRear}   {AirCondiWoning}   {AirCondiWoningFrontAndRear,  FrontFogLights}   {CarEquipment,  Comfort,   DrivingAndSafety,   Healthing}   X
  • 84.  (FeAture  Model  scrIpt  Language  for  manIpulaWon  and  AutomaWc  Reasoning)     not, and, or, implies φTVL DIMACS hip://familiar-­‐project.github.com/   Mathieu  Acher,  Philippe  Collet,  Philippe  Lahire,  Robert  B.  France  «  A  Domain-­‐Specific  Language  for  Large-­‐ Scale  Management  of  Feature  Models  »  Science  of  Computer  Programming  (SCP),  2013  
  • 87. 87   Optional Mandatory Xor-Group Or-Group {AirCondiWoning,  FrontFogLights}   {AutomaWcHeadLights,  AirCondiWoning,   FrontFogLights}   {AutomaWcHeadLights,  FrontFogLights,   AirCondiWoningFrontAndRear}   {AirCondiWoningFrontAndRear}   {AirCondiWoning}   {AirCondiWoningFrontAndRear,  FrontFogLights}   {CarEquipment,  Comfort,   DrivingAndSafety,   Healthing}   X
  • 88. 88  
  • 90.  (FeAture  Model  scrIpt  Language  for  manIpulaWon  and  AutomaWc  Reasoning)     imporCng,  exporCng,  composing,  decomposing,  ediCng,  configuring,   reverse  engineering,  compuCng  "diffs",  refactoring,  tesCng,     and  reasoning  about  (mulCple)  variability  models   not, and, or, implies φTVL DIMACS hip://familiar-­‐project.github.com/   Mathieu  Acher,  Philippe  Collet,  Philippe  Lahire,  Robert  B.  France  «  A  Domain-­‐Specific  Language  for  Large-­‐ Scale  Management  of  Feature  Models  »  Science  of  Computer  Programming  (SCP),  2013  
  • 92. #2  MulCple  Feature  Models   92  
  • 93. 93  93   MulC-­‐*  variability           *systems,  perspecCves,  or  stakeholders  
  • 94. •  #1  Automated  analysis     –  Aka  support  to  beber  understand  and  play  with  your  feature   model  (TVL  model)   •  #2  Managing  mulCple  feature  models   –  Composing  /  Decomposing  /  Diff  and  Reasoning  about  their   relaWonships   –  Combining  these  operators   94   Two  Key  Requirements  
  • 95. language  and  environment                 And-Group Optional Mandatory Xor-Group Or-Group constraints …….. DirectX V10 V10.1 v11 Outputs VIVO DVI HDMI S-Video Composite VGA GraphicCard And-Group Optional Mandatory Xor-Group Or-Group TV output constraints VGA excludes TV output HDMI implies v10.1 or v11 constraints …….. constraints …….. constraints …….. //  foo.fml   fm1  =  FM  (“foo1.tvl”)   fm2  =  FM  (“foo2.m”)   fm3  =  merge  intersecCon  {  fm1  fm2  }   c3  =  counCng  fm3   renameFeature  fm3.TV  as  “OutputTV”   fm5  =  aggregate  {  fm3  FM  (“foo4.xml”)  }   assert  (isValid  fm5)       fm6  =  slice  fm5  including  fm5.TV.*     export  fm6     True/False   8759   “OutputTV”,  “TV”     Interoperability   Language  faciliCes   Environment  
  • 96. 96   Interoperability   fm1  =  FM(“foo.tvl”)   fm2  =  FM  (“foo.m”)     serialize  fm4  into  SPLOT   serialize  fm1  into  featureide  fm3  =  FM  (“foo.xmi”)   fm4  =  FM  (A  :  B  ….)        De/ComposiCon   merge                        diff                        intersecWon                        sunion       aggregate    map    unmap   extract                                                      slicing   EdiCng   renameFeature    removeFeature   accessors      copy                 Reasoning     counWng   configs   isValid   deads  cores   falseOpWonals   cleanup   configuraWon      select    deselect    asFM  compare   setOpWonal                          setMandatory   setAlternaWves      setOr      Language  FaciliCes   fm1.*   fm1.B   modular  mechanisms       restricted  set  of  types   iterator/condiWonal   asserWon   insert   features  
  • 97. Hello  World   97   helloworld.fml   Optional Mandatory Xor-Group Or-Group
  • 98. Typed  language     •  Domain-­‐specific  types   –  Feature  Model,     –  ConfiguraWon,     –  Feature,     –  Constraint     •  Other  types  include     –  Set   –  String     –  Boolean,     –  Enum,     –  Integer  and  Real.     •  A  set  of  operaWons,  called  operators,  are  defined  for  a  given  type.     98   basics2.fml  
  • 99. Typed  language     99   basics2.fml  
  • 100. Typed  language     100   basics2.fml   Optional Mandatory Xor-Group Or-Group
  • 101. ImporCng/ExporCng  feature  models   101   FAMILIAR S2T2 TVL feature-model-synthesis (visual configurator) (language) (language)FaMa Internal  notaWon  or  by  “filename  extensions”     basics3.fml  
  • 102. Feature  Accessors  (1)   102   6Accessors.fml   Optional Mandatory Xor-Group Or-Group
  • 103. Other  constructs   103   6Accessors2.fml   Optional Mandatory Xor-Group Or-Group
  • 104. ConfiguraCon   104   conf.fml   Optional Mandatory Xor-Group Or-Group
  • 105. 105   φ FM A  ^   A  ó  B  ^     C  =>  A  ^   D  =>  A     Optional Mandatory Xor-Group Or-Group
  • 106. OperaCons  for  Feature  Models  (1)   106   φ operatorsFM.fml   Optional Mandatory Xor-Group Or-Group
  • 107. OperaCons  for  Feature  Models  (2)   107   φ operatorsFM2.fml   Optional Mandatory Xor-Group Or-Group
  • 108. OperaCons  for  Feature  Models  (3)   108   operatorsFM3.fml   Optional Mandatory Xor-Group Or-Group
  • 109.                                                                                 SoC  support  =  ComposiCon/DecomposiCon   for  managing   large,  complex  and  mulCple   feature  models   FORM  1998,  Tun  et  al.  2009  (SPLC),  Hartmann  2008  (SPLC),  Lee  et  al.  2010,  Czarnecki  2005,  Reiser  et  al.  2007  (RE  journal),  Hartmann   et  al.  2009  (SPLC),  Thuem  et  al.  2009  (ICSE),  Classen  et  al.  2009  (SPLC),  Mendonca  et  al.  2010  (SCP),  Dunghana  et  al.  2010,  Hubaux  et   al.  2011  (SoSyM),  Zaid  et  al.  2010  (ER),  She  et  al.,  2011  (ICSE),  etc.  
  • 110. Composing  Feature  Models  (1)   110   aggregateBasics.fml   Optional Mandatory Xor-Group Or-Group
  • 111. Composing  Feature  Models  (2)   111   aggregate1.fml   Previous   version   Optional Mandatory Xor-Group Or-Group
  • 112. Composing  Feature  Models  (3)   112   mergeMI.fml   Mathieu  Acher,  Philippe  Collet,  Philippe  Lahire,  Robert  B.  France  «  Comparing  Approaches  for   ImplemenWng  Feature  Model  ComposiWon  »  ECMFA’10  
  • 113. see  also  Thuem,  Kastner  and  Batory,  ICSE’09   Comparing  Feature  Models   113   compare.fml   Optional Mandatory Xor-Group Or-Group
  • 115. Merge  IntersecCon:  Available  Suppliers   115   ∩   ∩   A  customer   has  some   requirements   Suppliers?   Products?  
  • 116. In  FAMILIAR   116   suppliersExample0.fml  
  • 117. Merge  Union:  Availability  Checking   117   Can  suppliers  provide  all  products?   Yes!   “compare”         ∩   Optional Mandatory Xor-Group Or-Group
  • 118. In  FAMILIAR   118   suppliersExample.fml  
  • 119. Merging  operaCon:    implementaCon  issues   119   How  to  synthesise  a  feature  model  that  represents   the  union  of  input  sets  of  configuraCons?   Optional Mandatory Xor-Group Or-Group T2 MRI Medical Image HeaderAnonymized T1 DICOM Header excludes DICOM Header implies Anonymized Anonymized v Header v ~DICOM v ~T1 v ~T2 Anonymized v Header v DICOM v ~T1 v ~T2
  • 120. 120   Merging  operaCon:  semanCc  issues  (2)   φ Union   IntersecWon     Diff     How  to  synthesise  a  feature  model  that  represents   the  union  of  input  sets  of  configuraCons?  
  • 121. Merging  operaCon:  algorithm   121   φ1 φ2 φ3 φ123 merged  proposiWonal  formula   T2 MRI Medical Image HeaderAnonymized T1 DICOM merged  hierarchy   +   Set  mandatory  features   Detect  Xor  and  Or-­‐groups   Compute  “implies/excludes”   constraints   How  to  synthesise  a  feature   model  that  represents  the   union  of  input  sets  of   configuraCons?   see  also  [Czarnecki  SPLC’07  or  SPLC’12]   Optional Mandatory Xor-Group Or-Group
  • 122. Merging  operaCon:  back  to  hierarchy   122   mergeNonPC.fml   >  configs  fm4   res12:  (SET)  {{C;A};{A;B};{A};{A;B;C}}   ?  Mathieu  Acher,  Benoit  Combemale,  Philippe  Collet,  Olivier  Barais,  Philippe  Lahire,  Robert  B.   France  «  Composing  your  ComposiWons  of  Variability  Models  »  MODELS’13   Optional Mandatory Xor-Group Or-Group
  • 123. see  also  [Acher  et  al.,  ECMFA’10  /  MODELS’13]   – Well-­‐defined  semanWcs   – Guarantee  semanWcs  properWes  by  construcWon   – More  compact  feature  models  than  reference-­‐based   techniques  [Schobbens  et  al.,  2007],  [Hartmann  et  al.,  2007]   •  Easier  to  understand   •  Easier  to  analyze  (e.g.,  compare  with  another)   – Applicable  to  any  proposiWonal  feature  models     •  Full  support  of  proposiWonal  constraints     •  Different  hierarchies  [Van  Den  Broek  et  al.,  SPLC’2010/2012]   – SyntacWcal  strategies  fail  [Alves  et  al.,  2006],  [Segura  et  al.,  2007]   123   Related  Works  
  • 125. 125   Problem:  mulCple  „car  models“    
  • 126. 126   Problem:  mulCple  „car  models“    
  • 127. 127   Problem:  mulCple  „car  models“    
  • 128. 128   Problem:  mulCple  „car  models“       #2  –  boiom-­‐up:  elaborate  a  feature  model  for  each  model  line  and  merge  them   Two  modeling  approaches   #1  –  top-­‐down:  specify  constraints  (e.g.,  excludes)  of  all  model  lines  upfront    
  • 130. 130   #1  boiom-­‐up   FM_1   FM_2   FM_3   FM_r  merge  
  • 131. 131   #1  boiom-­‐up  (FAMILIAR)   FM_1   FM_2   FM_3   FM_r  merge   audiMerge.fml  
  • 133. 133   Building  “views”  of  a  feature  model  
  • 134. •  Problem:  given  a  feature  model,  how  to   decompose  it  into  smaller  feature  models?   •  SemanWcs?   – What’s  the  hierarchy   – What’s  the  set  of  configuraWons?   134   Building  “views”  of  a  feature  model  
  • 135. A  first  try   A3 => P1 P2 => A5 R A2 A5 A6 A1 A3 A4 A fm0 P3P2P1 P P1 => P2 A2 A5 A6 A1 A3 A4 A fmExtraction1 A2 A5 A6 A1 A3 A4 A fmExtraction2 A3 => A5 A4 => A6 Problem:  You  can  select  A3  without  A5   Hierarchy  and  ConfiguraCon  maier!   135  
  • 136. Slicing  Operator   W constraints E implies D R implies E D excludes F S implies (F and not E) P R S fm1 AV T U B C D E F Optional Mandatory Xor-Group Or-Group T S E D constraints E implies D D implies E slicing  criterion  :  an  arbitrary  set  of  features,  relevant  for  a  feature  model  user   slice  :  a  new  feature  model,  represenWng  a  projected  set  of  configuraWons     136  
  • 137. Slicing  operator:  going  into  details   projected  set  of  configuraCons   137   fm1  =  {     {A,B,C,D,E,P,R,T,U,W},     {A,B,C,F,P,S,T,U,W},     {A,B,C,D,E,P,R,T,W},     {A,B,C,F,P,S,T,V,W},     {A,B,C,F,P,S,T,U,V,W},     {A,B,C,F,P,S,T,W},     {A,B,C,D,E,P,R,T,V,W},     }   fm1  =  {     {A,B,C,D,E,P,R,T,U,W},     {A,B,C,F,P,S,T,U,W},     {A,B,C,D,E,P,R,T,W},     {A,B,C,F,P,S,T,V,W},     {A,B,C,F,P,S,T,U,V,W},     {A,B,C,F,P,S,T,W},     {A,B,C,D,E,P,R,T,V,W},     }   fm1p  =  {     {D,E,T},     {S,T},     {D,E,T},     {S,T},     {S,T},     {S,T},     {D,E,T}   }   fm1p  =  {     {D,E,T},     {S,T},     }   W constraints E implies D R implies E D excludes F S implies (F andnot E) P R S fm1 AV T U B C D E F Optional Mandatory Xor-Group Or-Group
  • 138. +   T S E D constraints E implies D D implies E φs1 existenBal   quanBficaBon   of  features   not  included   in  the  slicing   criterion   138   fm1p  =  {     {D,E,T},     {S,T}   }   Slicing  operator:  going  into  details   synthesizing  the  corresponding  feature  model   S   E   D   T   W constraints E implies D R implies E D excludes F S implies (F andnot E) P R S fm1 AV T U B C D E F φ1 Mathieu  Acher,  Philippe  Collet,  Philippe  Lahire,  Robert  B.  France  «  SeparaWon  of  Concerns  in   Feature  Modeling:  Support  and  ApplicaWons  »  AOSD’12   Optional Mandatory Xor-Group Or-Group
  • 139. T S E D constraints E implies D D implies E 139   Slicing  operator  with  FAMILIAR  (1)   W constraints E implies D R implies E D excludes F S implies (F andnot E) P R S fm1 AV T U B C D E F slicingOp2.fml   Optional Mandatory Xor-Group Or-Group
  • 140. 140   Slicing  with  FAMILIAR  (2)   slicingOp.fml  
  • 141. From  marke.ng,   customers,  product   management     From  exis.ng  so@ware   assets    (technical  variability)   Metzger,  Heymans  et  al.  “DisambiguaBng  the  DocumentaBon  of  Variability  in  Sofware  Product   Lines:  A  SeparaBon  of  Concerns,  FormalizaBon  and  Automated  Analysis“  (RE’07)  
  • 142. V1 ⬄ f1 V2 ⬄ f2 V3 ⬄ f3 From  marke.ng,   customers,  product   management     From  exis.ng   so@ware  assets     realizability   usefulness   Optional Mandatory Xor-Group Or-Group
  • 143. Realizability  checking   aggregate   {{V1,V3,V2,VP1},   {V1,VP1},   {V3,VP1},     {VP1}}     merge  diff   (“unrealizable  products”   φ 1 slice  (“realizable  part”)   2 3 compare   4   Mathieu  Acher,  Philippe  Collet,  Philippe  Lahire,  Robert  B.  France  «  SeparaWon  of  Concerns  in   Feature  Modeling:  Support  and  ApplicaWons  »  AOSD’12     Optional Mandatory Xor-Group Or-Group
  • 144. With  FAMILIAR   144   realizibility.fml  
  • 146. 146   RevisiCng  Merge:     Aggregate  +  Slice   Optional Mandatory Xor-Group Or-Group
  • 147. 147   RevisiCng  Aggregate,     Merge  and  Slice:       mergeWithAggregateMI.fml   Mathieu  Acher,  Benoit  Combemale,  Philippe  Collet,  Olivier  Barais,  Philippe  Lahire,  Robert  B.   France  «  Composing  your  ComposiWons  of  Variability  Models  »  MODELS’13   Optional Mandatory Xor-Group Or-Group
  • 148. 148   Mathieu  Acher,  Benoit  Combemale,  Philippe  Collet,  Olivier  Barais,  Philippe  Lahire,  Robert  B.   France  «  Composing  your  ComposiWons  of  Variability  Models  »  MODELS’13  
  • 149. 149   φ FM             Feature  Model  Synthesis  Problem   [Czarnecki  et  al.,  SPLC’07]   [She  et  al.,  ICSE’11]   [Andersen  et  al.,  SPLC’12]   A  ^   A  ó  B  ^     C  =>  A  ^   D  =>  A    
  • 150. φ               « How to synthesise an accurate (w.r.t. the set of constraints/configurations) meaningful (maintainable by a user), and unique feature model? »  hip://familiar-­‐project.github.com/  
  • 151. φ(SAT solvers or Binary Decision Diagrams) The  knowledge  can  be:       inconsistent  (e.g.,  root  feature  specified  is  not  possible)   consistent  and  incomplete  (i.e.,  synthesis  algorithm  needs   addiWonal  informaWon)   consistent,  «  parCal  »  (e.g.,  not  all  the  hierarchy  is  specified)  and   actually  complete     Mathieu  Acher,  Patrick  Heymans,  Anthony  Cleve,  Jean-­‐Luc  Hainaut,  Benoit  Baudry  «  Support  for   Reverse  Engineering  and  Maintaining  Feature  Models  »  VaMoS’13  
  • 152. #1  Reverse  Engineering  Scenarios   •  [Haslinger  et  al.,  WCRE’11],  [Acher  et  al.,  VaMoS’12]   φ V DAd OT M KAe CP R S C requires T Ae requires T S equals M V DAd OT KAe SP R M C requires T S equals M C 0..1
  • 153. #2  Refactoring   •  [Alves  et  al.,  GPCE’06],  [Thuem  et  al.,  ICSE’09]   φ V DAd OT M KAe CP R S C requires T Ae requires T S equals M
  • 154. #3  Re-­‐Engineering  Feature  Models  of           repository   •  For  each  FM  we  execute  the  following  FAMILIAR  script…     •  …  And  we  «compare»  syntacWcally  fm1  and  fm2   •  semanWcal  comparison  is  not  needed:  we  know  that  they  are  refactoring  by   construcWon  (good  test  case  though  ;-­‐))   •  Results:   –  147  synthesised  FMs  (69  %)  were  exactly  the  same  as  input  FMs  ;     –  40  synthesised  FMs  (19%)  were  correcWons  of  input  FMs  ;     –  24  synthesised  FMs  (12%)  were  different  (knowledge  needed)   •  another  set  of  cross-­‐tree  constraints  was  synthesised.     •  feature  group  conflicts  in  six  cases   SpecificaCon  of  the  hierarchy  is  the  main  issue   φ
  • 155. φ             FAMILIAR   « Give me a formula and some knowledge, I will synthesise an accurate, meaningful, unique feature model »  #1  Breathing  knowledge  into  feature  model  synthesis    formal  specificaWon  (consistency  and  completeness)    concrete  syntax  and  tooling  suport   #2  PracCcal  applicaCons    reverse  engineering,  refactoring/re-­‐engineering  of  feature  models       hip://familiar-­‐project.github.com/   Automated  support  is  highly   needed  (ongoing  work)  
  • 156. [MOTIVATION/PROBLEM]  Why  modeling  and  managing  Variability   does  and  will  maber  (30’)   [SOLUTION  FOR  MANAGING  FEATURE  MODELS]  Managing  Variability   Models  with  FAMILIAR  (1h45’)       [SOLUTION  FOR  MODEL-­‐BASED  DERIVATION  OF  PRODUCT]  Model-­‐based   variability  engineering:  examples,  support  and  open  issues   (45’)   156   Plan  
  • 157. Variability  AbstracCon   Model  (VAM)   ConfiguraCon   (resoluCon  model)   Domain  Artefacts   (e.g.,  models)   SoSware  Generator   (derivaCon  engine)   ü   ü   Variability   RealizaCon   Model   (VRM)  
  • 159. Printer ´Blockª mainSupply:MainPower1 Attributes Operations powerCtrl emgSupply:EmgPower1 Attributes threshold:int Operations powerCtrl inputSection1 highSpeedConnector1 Attributes Operations MainPowerCtrl EmgPowerCtrl MainPower ´Blockª Values Operations powerCtrl EmgPower ´Blockª Values threshold:int powerCtrl VariaCon  Points  over  base  model   :ObjectExistence   :SlotValueAssignment   CVL variation points SYSML (base model) elements :ObjectExistence   :ObjectExistence   §  Variability  in  this  example:     Part  EmergencySupply  is   opWonal     Part  HighSpeedConnector  is   opWonal     Port  EmgPowerCtrl  on  block   Printer  is  opWonal     Value  of  abribute  threshold  in   block  EmergencyPower  is   variable   Adapted  from  the  CVL  tutorial  at  SPLC’12  by  Oystein  Haugen,  Andrezj  Wasowski,  Krzysztof   Czarnecki    
  • 160. Printer ´Blockª mainSupply:MainPower1 Attributes Operations powerCtrl emgSupply:EmgPower1 Attributes threshold:int Operations powerCtrl inputSection1 highSpeedConnector1 Attributes Operations MainPowerCtrl EmgPowerCtrl MainPower ´Blockª Values Operations powerCtrl EmgPower ´Blockª Values threshold:int powerCtrl (Aiributed)   Feature  Model     Printer   EmergencyPower   threshold:Int   Variation points HighSpeed  &    threshold>100      EmergencyPower   HighSpeed   :ObjectExistence   :SlotValueAssignment  :ObjectExistence   :ObjectExistence   Based  Model     Adapted  from  the  CVL  tutorial  at  SPLC’12  by  Oystein  Haugen,  Andrezj  Wasowski,  Krzysztof   Czarnecki    
  • 161. Variability  RealizaCon  Layer   VariaCon  points  in  CVL   •  VariaWon  Points  refer  to  Base  objects   •  VariaWon  Points  define  the  base  model   modificaWons  precisely   •  There  are  different  kinds  of  VariaWon  Points   – Existence  (object  or  link)   – Value  assignment   – SubsWtuWon   – Opaque  variaWon  point   – Configurable  Unit   Adapted  from  the  CVL  tutorial  at  SPLC’12  by  Oystein  Haugen,  Andrezj  Wasowski,  Krzysztof   Czarnecki    
  • 162. Derivation of Traffic Lights Models Joao  Bosco  Ferreira   Filho  (PhD  student)  
  • 164. . Traffic Lights' behaviour can be modelled using Finite State Machines Traffic Lights FSM
  • 165. Traffic Lights FSM OBJECTIVE: Produce the finite state machine associated with each traffic light configuration . Simplification: - Green Light - Red Light - Yellow Light
  • 166. Base model . Define the DSL: 1. Create an Ecore modelling project 2. Define the metamodel 3. Generate the model, the edit and the editor code 4. Export them as plugins
  • 168. Base model . Create the base model: 1. Create a Modelling project 2. Create a new model in the DSL
  • 169. Base model . Create the base model: 1. Create a Modelling project 2. Create a new model in the DSL
  • 170. CVL model . Create the CVL model: 1. Create a new CVL model in the modelling project. Select VPackage as the Model object 2. Right click on the project, select Viewpoints selection. Check the three of them 3. Define the VAM, Resolution model and VRM
  • 171. VAM
  • 174. VRM
  • 175. VRM
  • 178. Visualisation of products in a web configurator Marianela Ciolfi Felice (MSc student)  
  • 180. Marks  &  Spencer  web  configurator  
  • 181. §  High visual quality §  Coherence and stability §  Interactiveness §  Performance §  Automatic and comprehensive update method Marianela Ciolfi Felice and Joao Bosco Ferreira Filho and Mathieu Acher and Arnaud Blouin and Olivier Barais « Interactive Visualisation of Products in Online Configurators: A Case Study for Variability Modelling Technologies » MAPLESCALE’13 (to appear)
  • 182. Anticipating all possible combinations §  10 configuration options §  10 possible values for each of them 10.000.000.000 combinations! Composing the visualisation
  • 183. PRODUCT CONFIGURATION VISUAL REPRESENTATION Models   HTML   jpg,  png,  ...,  files   SVG  files   Javascript   3D   models   Feature   models  
  • 185. . Simplification: - Fabric - Collar - Pocket (optional) - Handkerchief (optional)     Shirts web configurator
  • 186. Shirts web configurator OBJECTIVE: Produce the visual representation associated with each shirt configuration . Simplification: - Fabric - Collar - Pocket (optional) - Handkerchief (optional)    
  • 187. Feature model - Implicit boolean attribute existence - No constraints
  • 188. Base model . Define the DSL: 1. Create an Ecore modelling project 2. Define the metamodel 3. Generate the model, the edit and the editor code 4. Export them as a plugin
  • 190. Base model . Create the base model: 1. Create a Modelling project 2. Create a new model in the DSL
  • 191. Base model . Create the base model: 1. Create a Modelling project 2. Create a new model in the DSL
  • 192. CVL model . Create the CVL model: 1. Create a new CVL model in the modelling project. Select VPackage as the Model object 2. Right click on the project. Select Viewpoints selection. Check the three of them 3. Define the VAM, Resolution model and VRM
  • 193. VAM
  • 194. VAM
  • 195. VAM Suggestion: Set the choices' default resolution to: - True for mandatory features - False for optional features
  • 198. VRM
  • 199. VRM
  • 202. Summary:  Variability  Model  Management   202  202  202  
  • 203. [MOTIVATION/PROBLEM]  Why  modeling  and  managing  Variability   does  and  will  maber  (30’)   [SOLUTION  FOR  MANAGING  FEATURE  MODELS]  Managing  Variability   Models  with  FAMILIAR  (1h45’)       [SOLUTION  FOR  MODEL-­‐BASED  DERIVATION  OF  PRODUCT]  Model-­‐based   variability  engineering:  examples,  support  and  open  issues   (45’)   203   Key  Insights  
  • 204. (ongoing)  Comprehensive  model-­‐based   product  line  support     Reverse  engineering   Automated  Analysis   Languages,  API/DSLs   EvaluaCon  (European  projects,  long-­‐term  collaboraCon  with  Thales,  open  source   systems)     204   204  
  • 205.                     ?   205