1. Generic Language Technology (2IS15) Dynamic Semantics
dr. Suzana Andova

2. Dynamic Semantics Definition of a (programming) language involves:
abstract syntax, so-called signature
concrete syntax:
textual syntax
graphical syntax
semantics:
static semantics
dynamic semantics
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3. Dynamic Semantics
Semantics represents the intended meaning of a language and language constructs Semantics is a means to represent our understanding of a model/program (what is does) and To communicate our understanding to other entities To understand what happens in a computer/machine when a program/model is executed
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4. Dynamic Semantics
Not any language is suitable for description of dynamic semantics
Dynamic semantics ideally is described in a formal language (formal semantics) because:
ambiguities and inconsistencies can be detected in a (modeling) language which appears to be pretty “ok”
this is the basis for analysis, validation and verification, but also implementation
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5. Dynamic Semantics in practice
Hardly any modeling language used in industry has formal sematics
The semantics of languages is often defined by translation or interpretation
Languages evolve and more ambiguities are introduced
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6. Dynamic Semantics in practice
(domain) model
(DS) Language
(implementation)
engine
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7. Dynamic Semantics in practice?
Ambiguous representation and miscommunication
different understandings of models
(domain) model a c b d e
start-start
(DS) Language
(implementation)
engine
how many execution sequences one can think of?
 “total” representation required!
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8. Dynamic Semantics in practice
Model to implementation inconsistency
- SW constructs do not use semantics, only syntax
Code is manually added in the parts generated
Cognitive feedback Gap between Modeling and Model/Implementation Debugging
no possibility to transfer results of execution/debugging back to the original model
Lack of Early Design
correctness analysis
(domain) model
(DS) Language
(implementation)
engine
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9. Dynamic Semantics in practice
simulation
model
perform.
ana.
model
test
model
transformations
(DSL) model
Transformation from one env to another
- Semantic transformation gap
- Model transformation correctness reasoning
(DS) Language
(implementation)
engine
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10. Dynamic Semantics in practice?
(DSL) model 1
(DS) Language
(implementation)
engine1
simulation
model
perform.
ana.
test
transformations
(DSL) model 2
(DS) Language
(implementation)
engine2
simulation
model
perform.
ana.
test
transformations
Multi-disciplinary project
- Semantic gap between models
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11. Describing Dynamic Semantics
(Reference) Implementation
- Model/program is executed
- Conclusions about the behaviour based
on observations
Translational
- Select target language(s)
- Model based in most of the cases
Interpretation
Formal semantics
- structural operational semantics (SOS, MSOS)
- denotational semantics
- axiomatic
- algebraic
- game semantics
- …
(DSL) model
(DS) Language
(implementation)
engine
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12. Describing Dynamic Semantics
(Reference) Implementation
- Model/program is executed
- Conclusions about the behaviour based on observations
- if the code is complex (as usual) no behavioural analysis
(DSL) model
(DS) Language
(implementation)
engine
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13. Describing Dynamic Semantics
(DSL) model
(DSL) Language
(implementation)
engine
Model
Target
language
formal
semantics
direct translation
(properties preservation?)
Translational semantics
- Model based
- Ad-hoc Syntactic mapping
- No semantical mapping -> no ambiguities detection
- No support for language evolution
- Inconsistency and Properties preservation?
- Traceability/reverse mapping

14. Describing Dynamic Semantics
(DSL) model
(DSL) Language
(implementation)
engine
Model
Target
language
formal
semantics
direct
translation
Translational semantics
- Ad-hoc Semantical mapping
- No semantical mapping -> no ambiguities detection
- No support for language evolution
- Inconsistency and Properties preservation?
- Traceability/reverse mapping

15. Describing Dynamic Semantics
(domain) model
Target model
translation for free!
correct by construction!
DSL
formal
semantics
formal
semantics
Target language
(implementation)
engine
engine
design
decision?

16. Describing Dynamic Semantics
Formal semantics
structural operational semantics (SOS, MSOS)
describes the execution of the program on some
(very) abstract machine (G. Plotkin)
Denotational semantics:
mathematical definition of input/output relation of the program by induction on its syntactic structure (D. Scott, C. Strachey)
Axiomatic semantics
formalization of special properties of the program by logical formulae (assertions and proof rules; R. Floyd, T. Hoare)
- algebraic
- event structures
- ….
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18. Dynamic Semantics
Operational semantics: describes computation of the program on some
(very) abstract machine (G. Plotkin)
Denotational semantics: mathematical definition of input/output
relation of the program by induction on its syntactic
structure (D. Scott, C. Strachey)
Axiomatic semantics: formalization of special properties of the
program by logical formulae (assertions and proof rules;
R. Floyd, T. Hoare)
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19. Dynamic Semantics
. In practice, the design of complex software systems usually involves various types of domain specific (modeling) languages that cover different design aspects of the same system.
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20. Dynamic Semantics Integers and Strings can occur as values during
module Values
signature
Integer > VALUE
StrCon > VALUE
"nil-value" -> VALUE
Integers and Strings can
occur as values during
execution
nil-value denotes error values
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21. Dynamic Semantics Value environment Use Table again to get a mapping
module Value-environments
signature
Table[[PICO-ID, VALUE]] -> VENV
Use Table again to get a mapping
from PICO-ID to VALUE
Call it VENV: this represents the
Run-item values of variables (heap)
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22. Dynamic Semantics Pico-interpreter module Pico-interpreter signature
evp(PROGRAM) > VENV
evd(DECLS) > VENV
evits({ID-TYPE ","}*) > VENV
evs({STATEMENT ";"}*, VENV) -> VENV
evst(STATEMENT, VENV) > VENV
eve(EXP, VENV) > VALUE
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23. Dynamic Semantics Pico-interpreter Evaluate a program
equations
[Ev1] evp(program(Decls, Series)) = evs(Series, evd(Decls))
Evaluate the statements
Evaluate the declarations
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24. Dynamic Semantics Pico-interpreter
[Ev2] evd(decls(Id-type*)) = evits(Id-type*)
[Ev3] evits(id-type(Id:natural), Id-type*) = store(evits(Id-type*),Id,0)
[Ev4] evits(id-type(Id:string), Id-type*) = store(evits(Id-type*), Id,””)
[Ev5] evits() = []
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25. Dynamic Semantics Pico-interpreter [Ev6] Venv' := evst(Stat, Venv),
Venv'' := evs(Stat*, Venv')
=======================
evs(Stat ; Stat*, Venv) = Venv''
[Ev7] evs( , Venv) = Venv
[Ev8] evst(assign(Id, Exp), Venv) =
update(Id, eve(Exp, Venv), Venv)
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26. Dynamic Semantics Pico-interpreter [Ev9] eve(Exp, Venv) != 0
==================
evst(if(Exp, Series1, Series2), Venv) =
evs(Series1, Venv)
[Ev10] eve(Exp, Venv) == 0
evs(Series2, Venv)
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27. Dynamic Semantics Pico-interpreter [Ev11] eve(Exp, Venv) == 0
==================
evst(while(Exp, Series), Venv) = Venv
[Ev12] eve(Exp, Venv) != 0,
Venv' := evs(Series, Venv)
========================
evst(while(Exp, Series), Venv) =
evst(while(Exp, Series), Venv')
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28. Dynamic Semantics Pico-interpreter
[Ev13] eve(Id, Venv) = lookup(Venv, Id)
[Ev14] eve(Nat-con, Venv) = Nat-con
[Ev15] eve(Str-con, Venv) = Str-con
[Ev16] Nat1 := eve(Exp1, Venv),
Nat2 := eve(Exp2, Venv)
=======================
eve(plus(Exp1, Exp2), Venv) = Nat1 + Nat2
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29. Dynamic Semantics Pico-interpreter [Ev17] Nat1 := eve(Exp1, Venv),
========================
eve(min(Exp1 , Exp2), Venv) = Nat1 - Nat2
[Ev18] Str1 := eve(Exp1, Venv),
Str2 := eve(Exp2, Venv)
=======================
eve(conc(Exp1, Exp2), Venv) = Str1 || Str2
[default] eve(Exp,Venv) = nil-value
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30. Dynamic Semantics Pico-interpreter reduces to The term evp( )
begin declare input : natural,
output : natural,
repnr: natural,
rep: natural;
input := 14;
output := 1;
while input - 1 do
rep := output;
repnr := input;
while repnr - 1 do
output := output + rep;
repnr := repnr - 1
od;
input := input - 1 od
end
reduces to
The term
[<input,1>,
<repnr,1>,
<output, >,
<rep, >]
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31. Dynamic Semantics
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