Verimag

SMI

Symbolic Model Interface

With SMI, a system is described as a network of communicating processes, each process being an extended finite state automaton. Given the system textual description, the SMI routines build an equivalent symbolic representation using decision diagrams. This representation can be the starting point in the development of more customized applications, e.g. model checking for different temporal logics or symbolic minimization with respect to equivalence relations.

Principles

The input language

The primary purpose of the SMI input language is to allow a natural and concise description of processes and their communications. Secondly, this description must be simple enough to be used for the construction of a symbolic representation using decision diagrams(DD). Some of the input language concepts are sketched in the following.

A process encapsulates data and behavior. It is specified by its variables, its communication ports and one or more control threads.

Variables are used to store local information about the process. Currently, only variables with simple finite domains are allowed: booleans, bounded naturals and other finite sets. The scope of a variable is the process definition,i.e. variables cannot be shared between different processes.

A thread is defined as a finite state automaton whose transitions can test and assign process variables. Furthermore, a transition can contain a message emission/receptionto/from one communication port. If a process contains more than one thread, they are completely asynchronous. The process executes a step by non-deterministically choosing a thread, then executing one of its enabled transitions. Note however that different threads can share the same process variables.

A protocol is specified by a composition expression whose ground terms are processes. Two operators are provided, one for parallel composition with synchronization by message emissions and receptions, and the other for abstractionof communication at some ports. The synchronization forces two or more transitions from different processes to be combined and executed simultaneously (rendez-vous). The abstraction hides or ignores the communication at some ports.

The symbolic model

The protocol model is a labeled transition system (Q, Act, (T_a | a in Act), Qo). Q is a finite set of states, Act is a set of actions, T_a subset of Q x Q is the transition relation labeled by a and Qo subset of Q is the set of initial states. Usually, such model underlies the protocol verification algorithms. Given a protocol described in our input language, our aim is to build and to handle efficiently its corresponding model.

The symbolic model interface was designed to allow the manipulation of model state sets and transitions, symbolically represented by decision diagrams (DDs).

The symbolic model is builded from a protocol described using the input language. More precisely, the protocol transition relations Ta are encoded using DDs. The encoding process can take into account a number of parameters. For example, the parallel composition and abstraction semantics can be considered CSP-like (with binary rendez-vous and CSP restriction) or CCS-like (with n-ary rendez-vous and CCS abstraction). We can also impose the computation of reachable states Acc - some verification algorithms are more efficient when the reachable states are a priori known.

Basic operations on sets, such as union, intersection or complementation are directly mapped to DDs functions. The inclusion or the equality test are straightforward using DDs. Some specialized functions which perform model exploration, e.g. to compute the initial state set Qo, or the successors/predecessors for a given state set, Post and Pre are also provided.

Finally, SMI is not based on one particular DD implementation, thus it can be used with any DDs and only a minimal interface is required.

Applications

Mu-Calculus Model-Checker

The model checker performs the backward evaluation of alternating free mu-calculus formulae over symbolic model representations.

Intuitively, the semantics of a formula P represents the set of states which satisfy it and is noted by P. The model checking algorithm for a formula Po works in two steps:

  • the set Po is constructed recursively over the formula structure.
  • a decision procedure is invoked :
    — standard evaluation -:- checks if Qo is subset of Po
    — forward analysis -:- checks if Acc intersected with Po is not empty
    — invariant checking -:- checks if Qo is subset of Po and Post(Po) is subset of Po

Minimal Model Generator

Given a labeled transition system(LTS) the minimal model generator(MMG) generates an equivalent minimal LTS. The minimality is relative to a bisimulation equivalence. A precise and complete description of the MMG algorithm can be found in Bouajjani-Fernandez-Halbwachs-90.

Briefly, the principle of the MMG algorithm is to refine an initial partition of the state space until a reachable and stable partition is obtained. It can be also defined as a computation of the greatest fixed point of a splitfunction defined over partitions. Different reductions (by strong, weak, branching,... bisimulation) are obtained considering an appropriate splitfunction.

The algorithm can work with the symbolic model representations. More precisely, a symbolic representation of partitions can be used, i.e. representing each equivalence class by a decision diagram. All partition transformations are then reduced to classical operations on decision diagrams. Currentlly, an operational version of this algorithm works with the SMI library.


Examples

Alternating Bit Protocol

The alternating bit protocol is part of the 4th OSI transport layer. It allows the exchange of messages betweeen two entities, a transmitter and a receiver, linked by unreliable communication channels.

The protocol is composed by four asynchronous processes: a transmitter, a receiver and the two communication channels between them. The communication is performed via 6 ports, which link the processes and their environnment. The SMI description of this protocol is given in the following files:

bitalt.exp

Lotos-Behavior

hide SEND, RECEIVE, ACK, SENDACK in

(transmitter.aut ||| receiver.aut )

|[ SEND, RECEIVE, ACK, SENDACK]|

( medium1.aut ||| medium2.aut )

bitalt.types

nat 30

bitalt.order

transmitter : 0 transmitter : ce transmitter : be transmitter : me

medium1 : 0 medium1 : b1 medium1 : m1

receiver : 0 receiver : me receiver : br receiver : cr

medium2 : 0 medium2 : b2

transmitter.aut

be, ce : bool

me : nat

des (0, 5, 3)

( 0, be:=false ce:=true, 1)

( 1, receive ACCEPT ?me, 2)

( 2, [ (be <=> ce)] send SEND !me !be, 2)

( 2, [ (be <=> ce)] receive ACK ?ce, 2)

( 2, [be <=> ce] be:= be, 1)

medium1.aut

b1 : bool

m1 : nat

des ( 0, 3, 2)

( 0, receive SEND ?m1 ?b1, 0)

( 0, receive SEND ?m1 ?b1, 1)

( 1, send RECEIVE !m1 !b1, 0)

medium2.aut

b2 : bool

des (0, 3, 2)

( 0, receive SENDACK ?b2, 0)

( 0, receive SENDACK ?b2, 1)

( 1, send ACK !b2, 0)

receiver.aut

br, cr : bool

mr : nat

des (0, 4, 2)

( 0, br:=true cr:=false, 1)

( 1, [ (br<=>cr)] send SENDACK !br, 1)

( 1, [ (br<=>cr)] send RECEIVE ?mr ?br, 1)

( 1, [br <=>cr] send TRANSMIT !mr cr:= cr, 1)

Fischer Mutual Exclusion Protocol


Manual Pages

Description

The SMI library provides an interface to access finite models builded from Networks of Extended Automata. The models are represented symbolically using Decision Diagrams(DDs). The SMI implements functions to handle model state sets and model transitions. The SMI library use exactly one of the following DD implementation at time:

  • BMDDs - Binary Multivalued Decision Diagrams (local)
  • Cudds - Colorado University Decision Diagram
  • TiGeR - TiGeR Binary Decision Diagrams
  • Bdds - Binary Decision Diagrams (local)

We have been developped two applications using the SMI libraries: evaluator which evaluate mu-calculus formulae on the model and mmg which generate the minimal model w.r.t. some bisimulations. The SMI libraries and the applications are available for SunOS and HP-UX platforms.

Synopsis

  • evaluator [smi-options] [eval-option] name[.exp] [name2]
  • mmg [smi-options] [mmg-options] name[.exp]

The name denotes the use of the followings files to build the symbolic model representation:

  • name.exp-:- model definition
  • name.types -:- model types
  • name.order-:- model variables order

The name2 denote an optionally mu-calculus formula file.

The smi-options available are:

  • -stat print various statistics during computation (not a default option)
  • -mem n allocate n MB of memory for DDs (default n = 8 )
  • -vars v use at maximum v DD variables (default v = 48 )
  • -sift enable the DD variables automatic reordering (not a default option)
  • -sim use the simultaneous composition of automata (not a default option)
  • -front frontier strategy for the computation of reachable states (not a default option)
  • -noreach not compute the reachable states (not a default option)

The eval-options might be one of the following:

  • -eval formula backward evaluation (default option)
  • -path extract an execution path to a satisfying state (not a default option)
  • -inv simple invariant checking (not a default option)

For the mmg-options see Aldebaran manual page.

Syntax for Extended Automata

The extended automata are described using the following context-free grammar :

Ext-Aut ::= [Var-Decl-List] [Ctrl-Thread-List]
Var-Decl-List ::= Var-Decl-List Var-Decl
Ctrl-Thread-List ::= Ctrl-Thread-List Ctrl-Thread

Variable declarations

Var-Decl ::= Var-List ’:’ Type-Name
Var-List ::= Var-List ’,’ Var-Name |Var-Name

Control threads

Ctrl-Thread ::= Thread-Descr [Thread-Trans-List]
Thread-Descr ::= ’des’ ’(’ Init-State ’,’ Trans-Number ’,’States-Number ’)’
Thread-Trans-List ::= Thread-Trans-List Thread-Trans

Thread transitions

Thread-Trans ::= ’(’ Start-State ’,’ [Guard] [Action] [Assign] ’,’ Final-State ’)’
Guard ::= ’[’ Bool-Expr ’]’
Action ::= ’send’ Gate-Name [Out-Expr-List]
’receive’ Gate-Name [In-Var-List]
’i’
Out-Expr-List ::= Out-Expr-List ’!’ Expr
In-Var-List ::= In-Var-List ’?’ Var-Name
Assign ::= Var-Name ’:=’ Expr
Assign Assign | Assign ’;’ Assign | ’{’ Assign ’}’

Expressions

Expr ::= Bool-Expr | Nat-Expr | Enum-Expr
Bool-Expr ::= Var-Name | ’ ’ Bool-Expr
Bool-Expr Bool-Op Bool-Expr | Enum-Expr Rel-Op Enum-Expr | Nat-Expr Rel-Op Nat-Expr
Nat-Expr ::= Var-Name | Nat-Number | Nat-Expr Nat-Op Nat-Expr
Enum-Expr ::= Var-Name | Enum-Item-Name | Enum-Op Enum-Expr

Operators

Bool-Op ::= ’\/’ ’/\’ ’=>’ ’<=>’
Rel-Op ::= ’=’ ’<=’ ’>=’ ’>’ ’<’ ’<>’
Nat-Op ::= ’+’ ’-’ ’*’ ’/’ ’%’
Enum-Op ::= ’succ’ ’pred’

Syntax for Data Types

Type-Defs ::= [Nat-Def] [Enum-Def-List]
Nat-Def ::= ’nat’ ’{’ Nat-Range ’}’
Nat-Range ::= Nat-Number
Enum-Def-List ::= Enum-Def-List Enum-Def
Enum-Def ::= ’enum’ Enum-Name ’{’ Enum-Item-List ’}’
Enum-Item-List ::= Enum-Item-List ’,’ Enum-Item-Name| Enum-Item-Name ’,’ Enum-Item-Name
Enum-Name ::= Identifier
Enum-Item-Name ::= Identifier

Syntax for Variable Ordering

The variables and thread control states order used to build the symbolic model can be specified using an external file, which must respect the following syntax :

Order ::= [ Order-Item-List ]
Order-Item-List ::= Order-Item-List Order-Item
Order-Item ::= Aut-Name ’:’ Var-Name | Aut-Name ’:’ Thread-Id
Aut-Name ::= Identifier
Var-Name ::= Identifier
Thread-Id ::= Nat-Number

Contact

For more information, contact Marius Dorel Bozga


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