Download to read offline
![Our vision:
Aspect Oriented Model Driven Engineering
5
Distribution
Fault tolerance
Security
Functional behavior
Book
state : String
User
borrow
return
deliver
setDamaged
reser
ve
Use case model
Platform
Model
Design
Model
Code
Model
AOMDE = Pleonasm because
a Model is an Abstraction of an Aspect
of Reality for a given Purpose
Change one Aspect and
Automatically Re-Weave:
From Software Product Lines…
..to Dynamically Adaptive Systems
"DSLs are far more prevalent
than anticipated"
[Hutchinson et al., ICSE’11]](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-5-320.jpg)
![The Kermeta Language Workbench [SoSyM’13]
• Offer a generic solution covering most model manipulation needs
• Goals:
• Design of DSML: modular and safe
• Implementation of DSML: scalable, interoperable and efficient @ runtime
Editors
(textuals, graphicals, …)
Documentation generators
Test generators
Simulators
Analyzers
Refactoring
Checkers
(static & dynamics)
Translators
Compilers
Code generators
Etc.](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-6-320.jpg)
![The Kermeta Language Workbench [SoSyM’13]
• Modular design of DSMLs
• One meta-language per language concern (require)
• Ecore, OCL, Kermeta Action Language
• But also: QVTo, fUML, Alf, Ket, Xsd…
• Static introduction mechanism (aspect)
• Efficient implementation of DSMLs
• Mashup of the meta-languages to efficient bytecode
• Integrated with third-party tools (EMF compliant)
• Current investigations: precise metamodeling, modeling in the
large, language family, multi-platforms, model comprehension…
MDE for SLE; and SLE for MDE
-
7](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-7-320.jpg)
![Variability and SE
43
Component Based
Software Engineering
Dynamic Adaptation
Aspect-Oriented
Modeling
[Medvidovic et al’02]
[Kiczales et al’97]
OSGi, Fractal,!
OpenCOM, etc
[France et al’04]
[Rashid et al’02]
[Taylor et al’09]
[Garlan et al.'04]
[Oreizy et al.'98]
[Huebscher et al'08]
[Heineman
et al’01]
[Crnkovic et al’02]](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-43-320.jpg)
![=> Software Language Engineering
• The separation of concerns…
Modularization [Parnas72] to allow the structure of the product to resemble
the structure of the organization that designed it [Conway68]
• … at the language level
Domain-Specific (Modeling) Language (DSML) should serve to implement a
solution in terms of a problem (socio-technical coordination [Herbsleb07]).
• requires to manage the interactions between languages
to avoid social isolation and non sharing information (as observed for example
in the use of APIs [Souza04])
59](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-59-320.jpg)
![Across the software life cycle…
• Executable, Composable and Intuitive Models (i.e.,
runware) from design to run time
the two-way tunnel-digging
61
The tunnel digging analogy
[Harel et al., SoSyM’12]](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-61-320.jpg)
![Heterogeneity and SE
65
Metamodeling
Global Software Engineering
Models of
Computation
[Schmidt'06]
[Winskel’87]
[Karsai’03]
[Lee and
Sangiovanni’98]
[Eker et al.’03]
[Jantsch'04]
[Lédeczi'01]
[Clarke'02]
[Atkinson'06]
[Straw’04]
[Herbsleb'01]
[Souza'04]
[Conway’68]
[Boehm’84]](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-65-320.jpg)
![Ecology and SE
82
Randomization
Unsound transformations
SBSE
[Rinard’04]
[Misailovic’10]
[Berger’06]
[Demsky’06]
[Forrest’94]
[Forrest’97]
[Smith’93]
[Kc’03]
[Barrantes05]
[Hemmati’10]
[Harman’07]](https://image.slidesharecdn.com/ciel2013-combemale-160126120409/85/On-Modeling-and-Testing-When-Unpredictability-Becomes-the-Pattern-April-2nd-2013-82-320.jpg)
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Similar to On Modeling and Testing When Unpredictability Becomes the Pattern (April 2nd, 2013)
On Modeling and Testing When Unpredictability Becomes the Pattern (April 2nd, 2013)
- 1. 1 On Modeling andTesting! When Unpredictability Becomes the Pattern Benoit Baudry and Benoit Combemale (with the help and the slides of Mathieu Acher, Olivier Barais, Arnaud Blouin, Johann Bourcier, Jean-Marc Jézéquel, and Noël Plouzeau) Keynote at CIEL 2013, April 2nd, 2013 http://people.irisa.fr/Benoit.Combemale/ciel2013
- 2. Triskell research group 2 Triskellteam (env. 40 people) - 8 faculty members - 1 Research Engineer - ~20 PhD students - ~3 Software Engineers - ~2 Post doc
- 3. 3 meta-meta OSGi requirements Arduino access control deadline CSU ICSE Kermeta deadline proposal zimbra café? café? cloud NESSoS CIFRE deadline MODELS pattern process ESIR seminar SVN AOC contrat doctoral INRIA ISTIC model runtime semantics café? deadline capitalize &co. proceedings thesis meta IRISA Git MDE MDE GEMOC model Diversity ACO MDE!
- 4. Triskell’s Research Foundations/ Topics 4 MDE RE, runtime V&V
- 5. Our vision: Aspect OrientedModel Driven Engineering 5 Distribution Fault tolerance Security Functional behavior Book state : String User borrow return deliver setDamaged reser ve Use case model Platform Model Design Model Code Model AOMDE = Pleonasm because a Model is an Abstraction of an Aspect of Reality for a given Purpose Change one Aspect and Automatically Re-Weave: From Software Product Lines… ..to Dynamically Adaptive Systems "DSLs are far more prevalent than anticipated" [Hutchinson et al., ICSE’11]
- 6. The Kermeta LanguageWorkbench [SoSyM’13] • Offer a generic solution covering most model manipulation needs • Goals: • Design of DSML: modular and safe • Implementation of DSML: scalable, interoperable and efficient @ runtime Editors (textuals, graphicals, …) Documentation generators Test generators Simulators Analyzers Refactoring Checkers (static & dynamics) Translators Compilers Code generators Etc.
- 7. The Kermeta LanguageWorkbench [SoSyM’13] • Modular design of DSMLs • One meta-language per language concern (require) • Ecore, OCL, Kermeta Action Language • But also: QVTo, fUML, Alf, Ket, Xsd… • Static introduction mechanism (aspect) • Efficient implementation of DSMLs • Mashup of the meta-languages to efficient bytecode • Integrated with third-party tools (EMF compliant) • Current investigations: precise metamodeling, modeling in the large, language family, multi-platforms, model comprehension… MDE for SLE; and SLE for MDE - 7
- 8. Triskell’s Software development 8 Kermetaworkbench - Kermeta language, model typing, compiler - IDE - MDKs (e.g., KET, Kompren) Pramana, Pacogen Kompose, GEMOC (with CSU) KCVL, Kevoree IoT / IoS, cloud, requirements, security, process, home automation, software product lines, interoperability
- 9.
- 10.
- 11.
- 12. Open environments Heterogeneous environments Distributed systems Dynamic systems Software intensive systems Context 12 Which models? Which formalisms? Whichprocesses? Which theories? Which experiments?
- 13. Context • Complex (Adaptive) Software-intensiveSystems • Cyber-Physical Systems, • System of Systems, Ultra Large-scale System, • Smart City, Smart Building, Home automation, • Internet of Services, and Internet of Things… Openness (from requirements to runtime) The whole life cycle of systems are unpredictable! How fit systematic “patterns” introduced by SE approaches? Future of Modeling and Testing? 13
- 14.
- 15. The vision shaped! 15 "InYellowstone's geyser basins, unpredictability is the pattern. Old Faithful's relatively predictable intervals are the exception."
- 16. Objectives of thetalk • Propose a vision for modeling and testing, where unpredictability IS the pattern • Explore the relationships between research fields and provide an original corresponding survey • Present some of the current relative challenges, projects, initiatives, standards, etc. 16 Subjective authors' point of view * !! * No possible damage for your health
- 17. On Modeling andTesting! When Unpredictability Becomes the Pattern 17 Unpredictability as a Pattern Imposed Unpredictability Heterogeneity Management Variability Management Chosen Unpredictability Software Diversification
- 18. Variability Management! From SPLto DAS using MDE
- 19. Model Driven Engineering… 19 Distribution «Service Provider Manager » Notification Alternate Manager « Recovery Block Manager » Complaint Recovery Block Manager « Service Provider Manager » Notification Manager « Service Provider Manager » Complaint Alternate Manager « Service Provider Manager » Complaint Manager « Acceptance Test Manager » Notification Acceptance Test Manager « Acceptance Test Manager » Complaint Acceptance Test Manager « Recovery Block Manager » Notification Recovery Block Manager « Client » User Citizen Manager Fault tolerance Roles Activities Views Contexts Security Functional behavior Book state : StringUser borrow return deliver setDamaged reser ve Use case model Platform Model Design Model Code Model
- 20. MDE… to SupportVariability @ Design Time 20 Distribution « Service Provider Manager » Notification Alternate Manager « Recovery Block Manager » Complaint Recovery Block Manager « Service Provider Manager » Notification Manager « Service Provider Manager » Complaint Alternate Manager « Service Provider Manager » Complaint Manager « Acceptance Test Manager » Notification Acceptance Test Manager « Acceptance Test Manager » Complaint Acceptance Test Manager « Recovery Block Manager » Notification Recovery Block Manager « Client » User Citizen Manager Fault tolerance Roles Activities Views Contexts Security Functional behavior Book state : StringUser borrow return deliver setDamaged reser ve Use case model Platform Model Design Model Code Model
- 22.
- 24.
- 26. 26" Hierarchy:"rooted"tree"" Variability:** • mandatory,"" • op/onal,"" • Groups:"exclusive"or"inclusive"features" • Cross;tree"constraints" Optional Mandatory Xor-Group Or-Group Orthogonal*Variability*Modeling:* Feature'Models'
- 27.
- 28.
- 29.
- 30. FAMILIAR"(FeAture"Model"scrIpt"Language"for"manIpula/on"and"Automa/c"Reasoning)"" impor9ng,*expor9ng,*composing,*decomposing,*edi9ng,*configuring,* reverse*engineering,*compu9ng*"diffs",*refactoring,*tes9ng,** and*reasoning*about*(mul9ple)*variability*models* not, and, or,implies φTVL DIMACS hPp://familiar3project.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"""
- 31. (Orthogonal?) Variability Modeling:! Feature Models 31"
- 32. DSL* Variability* model* CVL* Base** model* Generic"&"" Standardized" resolu9on* models* Focused"on"" a"domain" Execute'CVL' ' ' Resolved** models* Descrip/on"of" possible" varia/ons"in" the"system" Domain" model"of"a" par/cular" family"of" system" Selec/on"of"a"set" of"op/ons"in"the" varia/on"model" Family"of"systems"fully" described"in"the" domain"specific" language." All"regular"DSL"tools"can" be"applied"to"these" models" Common Variability Language(CVL) 32 Realiza9on* model* Cf. http://www.omgwiki.org/variability
- 33. CVL in OMG 33 Late""2009,"Request"for"" Proposals""(RFP)" Late""2010,"Ini/al"Submission" September"2012"Revised"submission" Spring2013, Finalization? JOINT*SUBMISSION*TEAM* ini9ators*from*the*MoSiS*project* research*ins9tutes*and*universi9es* tool*vendors* users*&*consultants*
- 34. MDE… to SupportVariability @ Run Time 34 Distribution « Service Provider Manager » Notification Alternate Manager « Recovery Block Manager » Complaint Recovery Block Manager « Service Provider Manager » Notification Manager « Service Provider Manager » Complaint Alternate Manager « Service Provider Manager » Complaint Manager « Acceptance Test Manager » Notification Acceptance Test Manager « Acceptance Test Manager » Complaint Acceptance Test Manager « Recovery Block Manager » Notification Recovery Block Manager « Client » User Citizen Manager Fault tolerance Roles Activities Views Contexts Security Functional behavior Book state : StringUser borrow return deliver setDamaged reser ve Use case model Platform Model Design Model Code Model Change one Aspect and Automatically Re-Weave: From AORE, SPL to DAS
- 35. Example of Home-automation! ManyDifferent Needs 1/2 Picture(from(http://www.apt.gc.ca( • Living(at(home( • Motion(troubles( • Memory(loss( • Speaks(French((only)( • Home(equiped(with(:( • LonWorks((lights)( • Velux((shutters)( Mrs. Dupont 35
- 36.
- 37. " Software Product Lines(SPL) Their needs Medical/technical(staff(should(be(able(to( • Check(their(health(state( • Check(home(configuration((shutters,(lights,(heaters…)( Both( Mrs.(Dupont( Mr.(Doe( Some(daily(tasks(should(be( automated((motion( troubles)(or(reminded( (memory(loss).( Would(like(to(control( everything(remotely,(with( a(unified(protocol( 37
- 38. Different variability dimensions • Protocols • Low-levelprotocols: KNX, X2D, X10, etc • High-level protocols: http, UPnP, DPWS, etc • Devices • Lights, heaters, shutters, etc • Web services • GoogleAgenda, skype, WeatherForecast, MSN • PaaS: Nurse as a Service, Food Delivery, Ooshop • Adaptation to handicap/current health state • Motion, memory, perception, etc " Dynamic reconfiguration => DAS 38
- 39. Other Domain: TacticalInformation System 39
- 40. Towards more complexDDAS • Distributed Dynamic Adaptive Software (DDAS) development: • Adaptation logic often embedded into application logic • Adaptation logic hard-coded using low-level APIs • Readability, maintainability, and communication with other stakeholder not easy • Exponential growth of possible configurations • Convergence with Dynamic Software Product Lines • N features, N tending to be larger and larger • 2N potential program configurations, 2N x (2N-1) transitions 40
- 41. " Explosion of thenumber of possible configurations of Entimid # 1014 possible configurations! $ 1028 transitions! " Dynamic Adaptation # Evolution of the handicap # Houses should be configured remotely # No service interruption " Reliability # Safe migration path from a valid configuration to another valid configuration # Performance issue (time) not critical Challenges 41
- 42. • Focus on variability,not on configurations • Build (derive) configurations when needed • JIT, On demand at runtime, caching… • Validate configurations before actual adaptation • Automate the reconfiguration process Hyper-Agility with a DSPL Approach 42
- 43. Variability and SE 43 ComponentBased Software Engineering Dynamic Adaptation Aspect-Oriented Modeling [Medvidovic et al’02] [Kiczales et al’97] OSGi, Fractal,! OpenCOM, etc [France et al’04] [Rashid et al’02] [Taylor et al’09] [Garlan et al.'04] [Oreizy et al.'98] [Huebscher et al'08] [Heineman et al’01] [Crnkovic et al’02]
- 44. Handling Variability withMDE • (D)SPL approach to tame • The combinatorial explosion of configurations • The quadratic explosion of transitions • AOM to automatically build configuration • Runtime validation before adapting the running system • Simple roll-back • Models@Runtime to automate reconfiguration • Generation of safe reconfiguration scripts 44
- 45. Big picture Device controllers Light Shutter Target configuration Model @runtime Running system Metamodel EnTiMid Picture(from(http://www.apt.gc.ca( Hada flu last week $ stayed in bed $ a nurse every day Now in a better shape Derivation AOM Design-time Validation Runtime Validation Script Generator 45
- 46. 46 Architecture Metamodel - component,port, binding, etc - invariants Reflection model (source) Woven model (target) Conforms to Analyzer The running system adapts Strong synchronization introspection + listeners Delayed synchronization Validation Reasoning) Context info. Context model Design- models Models@runtime: ! Using MDE technology at runtime
- 47. (FP7 STREP) DiVATechnical Approach • Separate the application-specific functionality from the adaptation concerns in requirements: (D)SPL • Feature Model, decorated with Quality Attributes • Reasoner works with (context x Feature Model QA) • Associate fragments of architecture to Features • aka advice, + where it can be woven: aka pointcut • Model driven techniques • used to raise the level of abstraction of the model of the context • updated with CEP • model composition (aspect weaving) • To compose new architectures on the fly • Model Based Validation • automatic generation of platform reconfiguration script 47
- 48. % Heterogeneity managementwith notion of NodeType % Java Node, Dalvik Node, Arduino Node, Cloud Node (Jails/*BSD, JCloud, mini- cloud, EC2) % Component-based % Component, Port, Channel, Node, Group, ... % Actor semantics on each port to separate component behavior % Communication semantics between components using channels % Hot (re-)deploy & provisioning % Models@Runtime in a Distributed Context % Shared model representation for distributed nodes % Offline & online operation, compute@Model level, apply @Runtime % Reconfiguration using platform mecanisns, from classLoader, DLL to reflashing % Publications % A Dynamic Component Model for Cyber Physical Systems François Fouquet; Olivier Barais; Noël Plouzeau; Jean-Marc Jézéquel; Brice Morin; Franck Fleurey 15th Int. ACM SIGSOFT Symposium on Component Based Software Engineering, Jul 2012, Italy. % Dissemination of reconfiguration policies on mesh networks François Fouquet; Erwan Daubert; Noël Plouzeau; Olivier Barais; Johann Bourcier; Jean-Marc Jézéquel DAIS 2012, Jun 2012, Stockholm, Sweden. 48 Model@Runtime platform ! for distributed dynamic adaptive system (kevoree.org)
- 49. Model@Runtime platform ! fordistributed dynamic adaptive system • From low power nodes… • Arduino • … to Clouds • EC2 etc. • DAUM platform • Tactical Information System • for civil security • Sensors on firefighters, tablets, cloud… Triskell private heterogeneous cloud 49 (kevoree.org)
- 50.
- 51. Heterogeneity Management! On theGlobalization of Modeling Languages 51
- 52. Complex Software-Intensive Systems • deal with multiple concerns require global analysis and execution • integrate heterogeneous parts require global service • manage evolution of concerns and the emergence of new concerns require evolution and creation of tools and methods for software development 52
- 53.
- 54.
- 55.
- 56. MDE… to SupportHeterogeneity Distribution « Service Provider Manager » Notification Alternate Manager « Recovery Block Manager » Complaint Recovery Block Manager « Service Provider Manager » Notification Manager « Service Provider Manager » Complaint Alternate Manager « Service Provider Manager » Complaint Manager « Acceptance Test Manager » Notification Acceptance Test Manager « Acceptance Test Manager » Complaint Acceptance Test Manager « Recovery Block Manager » Notification Recovery Block Manager « Client » User Citizen Manager Fault tolerance Roles Activities Views Contexts Security Functional behavior Book state : StringUser borrow return deliver setDamaged reser ve Use case model Platform Model Design Model Code Model Change one Aspect and Automatically Re-Weave: From AORE, SPL to DAS 56 AOMDE = Pleonasm because a Model is an Abstraction of an Aspect of Reality for a given Purpose
- 57. Aspect Oriented Modeling • Separationof concerns in a model • A concern is not necessarily cross-cutting • Model composition • Build a global view from a set of concern models • AOM is a wide domain • Captures a large variety of modeling practices • A large number of composition approaches (e.g., Kompose, ModMap, Geko, SmartAdapter@Runtime…)
- 58. (Naive) MDA vs.(AO) MDE • From Transformation to Composition • Similar to goto vs. proper loop concept in language • Or assembly language vs. high-level languages
- 59. => Software LanguageEngineering • The separation of concerns… Modularization [Parnas72] to allow the structure of the product to resemble the structure of the organization that designed it [Conway68] • … at the language level Domain-Specific (Modeling) Language (DSML) should serve to implement a solution in terms of a problem (socio-technical coordination [Herbsleb07]). • requires to manage the interactions between languages to avoid social isolation and non sharing information (as observed for example in the use of APIs [Souza04]) 59
- 60. At some pointin the software lifecycle… • Interoperable and Collaborative Models 60 The Village Metaphor A. Vallecillo. “A Journey through the Secret Life of Models“. Dagstuhl seminar on Model Engineering of Complex Systems (MECS), Aug. 2008.
- 61. Across the softwarelife cycle… • Executable, Composable and Intuitive Models (i.e., runware) from design to run time the two-way tunnel-digging 61 The tunnel digging analogy [Harel et al., SoSyM’12]
- 62. Challenges • Model Driven Engineering & Software Language Engineering • Language relationships should be capitalized from transformation to composition • Global model coordination and analysis from design to runtime 62
- 63. Executable Metamodeling • Effective environmentsfor the design and implementation of executable domain specific languages (e.g., Kermeta at Inria) • BUT these environments do not allow the integration of heterogeneous models of computation (concurrence, communication…) 63
- 64. Models of Computation • Effectiveenvironments to deal with the execution and analysis of models based on heterogeneous models of computation (e.g., Ptolemy at UC Berkeley, ModHel’X at Supélec) • BUT these environments do not allow adaptation to specific business/application domains 64
- 65. Heterogeneity and SE 65 Metamodeling Global Software Engineering Models of Computation [Schmidt'06] [Winskel’87] [Karsai’03] [Lee and Sangiovanni’98] [Eker et al.’03] [Jantsch'04] [Lédeczi'01] [Clarke'02] [Atkinson'06] [Straw’04] [Herbsleb'01] [Souza'04] [Conway’68] [Boehm’84]
- 66. On the Globalization of Modeling Languages!
- 67. An Initiative… Focuses onSLE tools and methods for interoperable, collaborative, and composable modeling languages 67
- 68. … Constantly Growing UnitedStates Canada 68
- 69. The GEMOC Initiativeis born! An open initiative to • coordinate (between members) • disseminate (on behalf the members) worldwide R&D efforts on the globalization of modeling languages http://gemoc.org • Funded by complementary and successive projects • IP left to PCA of each projects 69
- 70. ANR INS GEMOC(2012-2016) "A Language Workbench for Heterogeneous Modeling and Analysis of Complex Software-Intensive Systems » Tools and methods for the definition and coordination of executable heterogeneous modeling languages over heterogeneous models of computation http://gemoc.org/ins
- 71. GlobalDSL 2013 First InternationalWorkshop on The Globalization of Domain Specific Languages July 2nd, 2013, Montpellier, France co-located with ECMFA, ECOOP and ECSA 2013 • Topics of interest include composability, interoperability, modularity, reuse, and variability of programming/modeling languages • Submit on Easychair before April 8, 2013! http://gemoc.org/globaldsl2013 71
- 72. From imposed tochosen Unpredictability 72 Domain System Variability Domain Domain Domain System Heterogeneity Software diversification to operationalize unpredictability from design to runtime
- 73.
- 74. N-version programming 74 version 1 version2 version 3 version 1 version 2 version 3 input vote output Algirdas Avizienis: The N-Version Approach to Fault-Tolerant Software. IEEE Trans. Software Eng. 11(12): 1491-1501 (1985) Safety
- 75. Data diversity 75 execute P execute P x P(x) reexpression y=R(x) adjustfor re-expression A(P(y)) Paul Ammann, John C. Knight: Data Diversity: An Approach to Software Fault Tolerance. IEEE Trans. Computers 37(4): 418-425 (1988) Safety
- 76. Instruction set randomization 76 EncryptionKey Compile Load In memory Execution Decryption Key Randomized instruction set emulation! EG Barrantes, DH Ackley, S Forrest, D Stefanović! ACM Transactions on Information and System Security (TISSEC) 8 (1), 3-40 Security
- 77. Software product lines 77 X"X" Conflict" Requires" X" X" Functional Diversity
- 78. Loop perforation • unsound transformation • stilluseful 78 source code instrumented binary Compile In memory Execution Instrumentation running program Monitoring and perforation Sasa Misailovic, Stelios Sidiroglou, Henry Hoffmann, Martin C. Rinard Quality of service profiling. ICSE (1) 2010: 25-34 QoS
- 79. Test cases diversity • Ina large set of test cases • select the ones that are most diverse • intuition: they’re more likely to test different parts of the program • trade-off testing cost / bug detection 79 Hadi Hemmati, Lionel C. Briand, Andrea Arcuri, Shaukat Ali: An enhanced test case selection approach for model-based testing: an industrial case study. SIGSOFT FSE 2010: 267-276 Fault Detection
- 80.
- 81. Software diversity • is diverse • movesfrom static to dynamic diversity • expanding scope • from safety-critical systems • to open and flexible systems • but • diversification strategy is fixed at design time • diversity is local From Software Diversity to Software Diversification 81
- 82. Ecology and SE 82 Randomization Unsound transformations SBSE [Rinard’04] [Misailovic’10] [Berger’06] [Demsky’06] [Forrest’94] [Forrest’97] [Smith’93] [Kc’03] [Barrantes05] [Hemmati’10] [Harman’07]
- 83. DIVERSIFY • Can the theoriesof biodiversity emergence and organization support theories of software diversification? • Goal: analyze and operationalize automatic software diversification • In interaction with ecologists www.diversify-project.eu 83
- 84. Conclusion • Unpredictability should bea pattern in SE • Agile ( Software Development ) vs. ( Agile Software ) Development • Recent work on modeling and testing are going in this way ; in particular: • Variability modeling and model composition to manage unpredictability • software diversification to operationalize unpredictability 84
- 85. Our Vision 85 Modeling andTesting Foundations Diversity Heterogeneity Variability From Design to Runtime
- 86. Our Vision 86 Randomization Unsound Transformations Meta Modelisation Global SE MoC CBSE Dynamic Adaptation AOM SBSE On Modelingand Testing When Unpredictability Is the Pattern Variability Heterogeneity Diversity
- 87. Contacts: Benoit Combemale benoit.combemale@irisa.fr http://people.irisa.fr/Benoit.Combemale BenoitBaudry benoit.baudry@inria.fr http://people.irisa.fr/Benoit.Baudry Open positions: SE, PhD, Post-doc