Introduction to the Center for
Systems and Software Engineering
XTEAM: Automated Synthesis of
Domain-Specific Code Generators
George Edwards
[email protected]
Brief Introduction to CSSE
• Established in 1993 as CSE
– Merged in 2006 with SAE to form CSSE
• Focus on research and teaching
– MSCS with emphasis in SE
– Graduate Certificate in SAE
– Two Certificate and Advanced Degree programs
• Objective is to solve scientific problems with
industrial relevance
CSSE Affiliates
• 22 industrial affiliates
– 8 from aerospace industry
– 12 from other industries
– 2 international
• 12 government affiliates
– 6 government agencies
• incl. US Army TACOM and Research Labs
– 6 FFRDCs and consortia
• 7 academic affiliates
– 5 universities
– 2 research centers
• 3 visiting associates
Research Focus Areas
•
•
•
•
Architecture
Economics
Process
Testing & analysis
Software Architecture Research
•
•
•
•
•
•
•
•
Modeling
Analysis
Implementation
Deployment
Dynamic adaptation
Architectural styles
Software connectors
Architectural recovery
XTEAM Project Overview
• Processes, notations, tools, and designs that
enable automated synthesis of end-to-end
domain-specific toolsets for software
architecture modeling, analysis, and code
generation
• Example application areas:
– Systems-of-systems and ultra-large-scale systems
– Safety- and mission-critical systems
– Cloud and grid systems
•
Domain-Specific Languages
(DSLs)
Customized for a particular
family of problems
(the domain)
• Concise and intuitive
– No missing or extra
features
– Capture patterns
– Enforce constraints
– Use native symbols and
terms
• Can be modified, evolved,
and composed
Model-Driven Engineering (MDE)
• MDE leverages DSLs for architecture modeling
– Metamodels define DSL syntax (types, properties, views, and constraints)
– Model interpreters define DSL semantics (analysis, code generation, etc.)
• MDE platforms provide (some) tool support
– Metamodel editor with built-in metamodeling language
– Metamodel interpreter that configures a metaprogrammable model
editor
Off-theshelf
Metamodel
Editor
Metaprogrammable
Model Editor
Auto
generated
Metamodeling
Domain-Specific
Language
Language
Built by
engineer
Metamodel
Interpreter
Metamodel
Domain-Specific
Domain-Specific
Domain-Specific
Model
Model
Model
8
Model Execution
Environment
(Semantic
Domain)
Model
Interpreter
Executable
Executable
Executable
Model
Model
Model
Problems with MDE
• Building and maintaining
code generators for DSLs
is inherently difficult
– High design complexity
– Disproportionate
maintenance and evolution
costs
– Hard to verify correctness
– Redundant development
effort
– Opaque semantics
embedded in source code
“The difficulty of building and
“There is a fundamental problem
maintaining
DSM solution
“Checkinga mathematical
in keeping
the
model interpreters
“The
state-of-the-art
model
stems
essentially
from
theof
properties
like
correctness
or
“Writing
translators
by
hand...
up to
date withwriting
metamodel
interpreter
needs
to be
complexity
of theof
mapping
completeness
transformations
in
addition
to
being
inefficient,
has
changes
... Current
practice
advanced
to
enhance
the
between
concept
instances
based
on
common
programming
yetthe
another
serious
drawback:
requires
each
model
interpreter
toofthe
reusability
and
maintainability
expressed
in the
DSML
and
the
languages
is very
difficult...”
semantic
mapping
between
be modified
manually
after
each the
this
software...”
code that
hasand
to the
be generated.”
input
output
is vaguely
metamodel
schema
change.
This
I. Malavolta,
H.
Muccini,
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Pelliccione,
specified...[Building
modelandof
be
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very
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G.
Karsai.
Structured
Specification
A.can
L.and
Santos
D.
et
al.
Automating
Providing
the
Architectural
interpreters]
is
the
most
time
Model
Interpreters.
Engineering
of
error
prone
task
for Interoperability
complex model
Construction
Languages
ofand
Domain-Specific
Tools
consuming
and
error prone
Computer-Based
1999.
interpreters
of considerable
size.”phase
Modeling
through
Languages
Model
Transformation
forSystems,
Object-Oriented
of theJournal
MIC
approach...”
Frameworks.
Technologies.
IEEE
ofTransactions
Software and
on
Systems,
Jing
Software
Zhang.
2010.
Engineering,
Metamodel-Driven
2009. Model
G. Karsai,
A. Agrawal,
F. Shi, J.on
Sprinkle.
Interpreter
Evolution.
Conference
the UseProgramming
of Graph Transformation
ObjectOn
Oriented
Systems in
the Formal
Specification2005.
of Model
Languages
and Applications,
Interpreters. Journal of Universal
Computer Science, 2003.
FCS: A Real World Example
• > $100 billion US Army program
• DSL with hundreds of types
– Modified on a daily basis
• Automated generation of:
–
–
–
–
Discrete event simulations
Middleware configuration files
Fault trees
Spreadsheets for documentation
Tool building and maintenance required approximately
five full-time MDE experts
XTEAM Solution Approach
Synthesize domain-specific code generators using the same
mechanisms that have proven successful for synthesizing
domain-specific model editors.
Model Editor
Framework
Metamodel Editor
Presentation
Semantics
Metamodel
Metamodel
Interpreter A
Presentation Rules
Presentation Logic
Types and Views
Application
Model
Presentation
Properties
(Abstract
Representation)
Platform
Properties
Metamodel
Interpreter B
Platform Semantics
Target Display
Model Interpreter
Framework
Code Generation
Logic
Code Generation
Rules
Visualized
Model
Target Platform
Executable
Model
Off-the-Shelf Component
XTEAM Toolset
XTEAM Component
Connector
Languages and Platforms
Repository
GME
Model Editor
Metainterpreter
XTEAM
Metalanguage
MS COM
GME
XDEVS MIF
Extensions
XDEVS
XDEVS
Simulations Discrete Event
(C++)
Simulation
Engine
XDEVS MIF
C++
XTEAM
DSLs
XDEVS
MS COM
XTEAM
Metamodels
(XML/HTTP)
GME
XTEAM
Model
Models
Fedora Linux (XML/HTTP) Editor
MS COM
SVN
Metainterpreter
Prism-MW
Metainterpreter
Windows/C++/Visual Studio
12
Prism-MW MIF
Extensions
Prism-MW MIF
Prism-MW
Applications
(Java)
Prism-MW
Lightweight
Architectural
Middleware
JVM
XTEAM Simulations
• Providing design
rationale
• Weighing architectural
trade-offs
• Discovering emergent
behavior of component
assemblies
• Validating component
implementations
13
Providing Design Rationale
– What architectural style to
use
– How to allocate functionality
among subsystems
– What types of connectors to
use
• XTEAM allows architects to
rationalize such decisions
with experimental evidence
– Model confidence level: Low
Peer-to-peer
Architecture
Potential
Workload
Request File Response Time
2500
Response Time (ms)
• Architects rely on intuition
and experience to make
important decisions early in
the design phase
Client-Server Architecture
2000
1500
1000
500
0
1
6
11 16 21
26 31 36
41 46 51
56 61 66
71
Invocation
76
81
86
91
96
Weighing Architectural Trade-offs
• Nearly all architectural decisions come down to trade-offs
between multiple desirable properties
– Emphasis on one system property may yield diminishing returns
• XTEAM allows architects to evaluate design alternatives in
terms of their impact on multiple non-functional properties
– Model confidence level: Medium
Decreases response time
Replication of components
Request File Response T ime
Response Time (ms)
2500
2000
1500
1000
500
0
1
6
11 16 21
26 31 36
41
46
51
56
Invocation
61
66
71
76
81
86
91
96
Consumes more battery power
Host A (iPAQ) Battery Power
Remaining Energy (mJ)
24000
23500
23000
22500
22000
0
58944 104612
175249 239514
287914 352870
415963 480308
Time (ms)
S…
529223
Evaluating Component Assemblies
• Contemporary large-scale distributed systems contain numerous off-theshelf components
– Detailed information about the behaviors and properties of individual
components may be known
– Component assemblies may exhibit unforeseen behavior due to subtle
interactions between constituent components
• XTEAM allows an architect to determine the emergent properties of a
composed system
– Model confidence level: High
Off-the-shelf components
Highly accurate parameterization
Determination of
emergent properties
Incremental System Validation
•
Individual component
implementations may
become available in a
piecemeal fashion
XTEAM allows architects to
•
1.
2.
–
Immediately incorporate
component implementations
into a simulated system,
increasing the accuracy of
analysis results
Rapidly test individual
components in the context of a
wide variety of operational
scenarios
Model confidence level: High
Component
implementation
available
Invoke implementation from behavior model
Integrated simulation and test environment
For More Information
• CSSE Website:
http://csse.usc.edu/csse/
• XTEAM Website:
http://www-scf.usc.edu/~gedwards/xteam.html