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Formal Specification - Techniques for the unambiguous specification of software

Formal Specification - Techniques for the unambiguous specification of software

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## Formal Specification - Techniques for the unambiguous specification of software

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**Formal Specification - Techniques for the unambiguous**specification of software Objectives: • To explainwhy formal specification techniques help discover problems in system requirements • To describe the use of • algebraic techniques (for interface specification) and • model-based techniques(for behavioural specification) • To introduce Abstract State Machine Model**Formal methods**• Formal specification is part of a more general collection of techniques that are known as ‘formal methods’ These are all based on mathematical representation and analysis of software • Formal methods include • Formal specification • Specification analysis and proof • Transformational development • Program verification**Notations For Formal Specification**• Any notation with precise semantics can be used • Formalism typically applied to just part of a specification • Notations use discrete mathematics, some with graphics • Several notations are sometimes used in the same specification: • Z or VDM for data manipulation • Statecharts for system states and transitions • Natural language for non-functional specifications**Formal Specification**• Goals of formal specification: • Complete • Consistent • Concise • Unambiguous • Valid—state exactly what the user wants • Specifications based on formal semantic model • What is/are semantics? • What is a formal semantic model?**Formal Semantics**• Semantics means “meaning” • Formal semantics: • Meaning expressed in mathematics • Formal semantic model: • Complete semantic definition of a language in mathematics • What mathematics? • Discrete mathematics! • Formal semantics permit dependable communication between all parties**Types Of Languages**• Procedural: • Computation defined by desired sequence of actions computer is to perform • Most high-level languages are procedural • Declarative: • Computation defined by desired state that computer should be in • Many specification languages are declarative • Functional: • Computation defined as desired function computer is to evaluate • Most functional languages derive from LISP**Types Of Languages**• High-level language programs are actually specifications! • Compilers write the program for you • So you have been specifying programs, not writing them • The big difference in languages is: • Declarative: • Says nothing about HOW, just WHAT • Procedural: • Says nothing about WHAT, just HOW**Types Of Languages—Examples**• Procedural: read (x); y := x; while y**2 > x loop y := y – 1; end loop; print (y); • Declarative: y**2 <= x AND (y+1)**2 > x**Formal Methods Activities**• Write a specification using a formal notation • Validate the specification • Inspect it with domain experts • Perform automated analysis to prove theorems • Refine the specification to an implementation • Semantics-preserving transformations to code • Verify that the implementation matches the spec • Mathematical argument**Library Example: Informal Statement**• A book can either be in the stacks, on reserve, or loaned out • If a book is in the stacks or on reserve, then it can be requested • We want to • formalize the concepts and the statements • prove some theorems to gain confidence that the spec is correct**Library Example: Formalization (1/2)**• First let’s formalize some concepts • S: the book is in the stacks • R: the book is on reserve • L: the book is on loan • Q: the book is requested**Library Example: Formalization (2/2)**If a book is requested, then it is on the shelf or on reserve**Use of formal methods**• Their principal benefits are in reducing the number of errors in systems so their main area of applicability is critical systems: • Air traffic control information systems, • Railway signalling systems • Spacecraft systems • Medical control systems • In this area, the use of formal methods is most likely to be cost-effective • Formal methods have limited practical applicability**Use of formal specification**• Formal specification involves investing more effort in the early phases of software development This reduces requirements errors as it forces a detailed analysis of the requirements • Incompleteness and inconsistencies can be discovered and resolved !!! Hence, savings as made as the amount of rework due to requirements problems is reduced**Acceptance of formal methods**• Formal methods have not become mainstream software development techniques as was once predicted • Other software engineering techniques have been successful at increasing system quality. Hence the need for formal methods has been reduced • Market changes have made time-to-market rather than software with a low error count as the key factor. Formal methods do not reduce time to market • The scope of formal methods is limited. They are not well-suited to specifying and analysing user interfaces and user interaction • Formal methods are hard to scale up to large systems**Two specification techniques**• Algebraic approach • The system is specified in terms of its operations and their relationships • Model-based approach • The system is specified in terms of a state model that is constructed using mathematical constructs such as sets and sequences. • Operations are defined by modifications to the system’s state**Interface specification**• Large systems are decomposed into subsystems with well-defined interfaces between these subsystems • Specification of subsystem interfacesallows independent development of the different subsystems • Interfaces may be defined as abstract data types or object classes The algebraic approach to formal specification is particularly well-suited to interface specification**The structure of an algebraic specification**< SPECIFICA TION NAME > (Gener ar ameter) ic P sort < name > imports < LIST OF SPECIFICA TION NAMES > Inf or mal descr iption of the sor t and its oper ations Oper ation signatures setting out the names and the types of the parameters to the operations defined over the sort Axioms defining the operations over the sort. Axioms relate the operations used to construct entities with operations used to inspect their values.**Specification components**• Introduction • Defines the sort (the type name) and declares other specifications that are used • Description • Informally describes the operations on the type • Signature • Defines the syntax of the operations in the interface and their parameters • Axioms • Defines the operation semantics by defining axioms which characterise behaviour**Specification operations**• Constructor operations. Operations which create entities of the type being specified • Inspection operations. Operations which evaluate entities of the type being specified • To specify behaviour, define the inspector operations for each constructor operation**Interface specification in criticalsystems**• Consider an air traffic control system where aircraft fly through managed sectors of airspace • Each sector may include a number of aircraft but, for safety reasons, these must be separated • In this example, a simple vertical separation of 300m is proposed • The system should warn the controller if aircraft are instructed to move so that the separation rule is breached**A sector object**• Critical operations on an object representing a controlled sector are • Enter. Add an aircraft to the controlled airspace • Leave. Remove an aircraft from the controlled airspace • Move. Move an aircraft from one height to another • Lookup. Given an aircraft identifier, return its current height**Primitive operations**• It is sometimes necessary to introduce additional operations to simplify the specification • The other operations can then be defined using these more primitive operations • Primitive operations • Create. Bring an instance of a sector into existence • Put. Add an aircraft without safety checks • In-space. Determine if a given aircraft is in the sector • Occupied. Given a height, determine if there is an aircraft within 300m of that height**Behavioural specification**• Algebraic specificationcan be cumbersome when the object operations are not independent of the object state • Model-based specificationexposes the system state and defines the operations in terms of changes to that state**Abstract State Machine Language (AsmL)**• AsmL is an executable specification language for modelling the structure and behaviour of digital systems • AsmL can be used to faithfully capture the abstract structure and step-wise behaviour of any discrete systems, including very complex ones such as: Integrated circuits, software components, and devices that combine both hardware and software**Abstract State**• An AsmL modelis said to be abstractbecause it encodes only those aspects of the system’s structure that affect the behaviour being modelled The goal is to use the minimum amount of detail that accurately reproduces (or predicts) the behaviour of the system • Abstractionhelps us reduce complex problems into manageable units and prevents us from getting lost in a sea of details AsmL provides a variety of features that allow you to describe the relevant state of a system in a very economical, high-level way**Abstract State Machine and Turing Machine**• An abstract state machine is a particular kind of mathematical machine, like the Turing machine (TM) • But unlike a TM, ASMs may be defined a very high level of abstraction • An easy way to understand ASMs is to see them as defining a succession of states that may follow an initial state**paint in green**A B paint in red State transitions • The behaviour of a machine (its run) can always be depicted as a sequence of states linked by state transitions • Moving from state A to state B is a state transition**Configurations**• Each state is a particular “configuration” of the machine • The state may be simple or it may be very large, with complex structure • But no matter how complex the state might be, each step of the machine’s operation can be seen as a well-defined transition from one particular state to another**paint in green**A B paint in red Evolution of state variables We can view any machine’s state as a dictionary of (Name, Value) pairs, called state variables (Colour, Red) is a variable, where “Colour” is the name of variable, “Red” is the value**Evolution of state variables**• Names are given by the machine’s symbolic vocabulary • Valuesare fixed elements, like numbers and strings of characters The run of a machine is a series of states and state transitions that results form applying operations to each state in succession**S1**Mode = “Initial” Orders = 0 Balance = £0 S3 Mode = “Final” Orders = 0 Balance = £500 S2 Mode = “Active” Orders = 2 Balance = £200 Initialise Process All Orders Example Diagram shows the run of a machine that models how orders might be processed • Each transition operation: • can be seen as the result of invoking the machine’s control logicon the current state • calculates the subsequence state as output**Control Logic**The machine’s control logic behaves like a fix set of transition rules that say how state may evolve Typical form of the operational text is: “ if condition then update ” We can think of the control logic as a text that precisely specifies, for any given state, what the values of the machine’s variables will be in the following step**The Machine’s Control Logic**… if mode = “Initial” then mode := “Active” Control Logic as a Black Box • The machine control logic is a black box that takes as input a state dictionary S1 and gives as output a new dictionary S2 • The two dictionaries S1 and S2 have the same set of keys, but the values associated with each variable name may differ between S1 and S2 input output**Run of the Machine**• The run of the machine can be seen as what happens when the control logic is applied to each state in turn • The run starts form initial state S1 S2 S3 … S1 is given to the black box yielding S2, processing S2 results in S3, and so on … • When no more changes to state are possible, the run is complete**Update operations**• We use the symbol “: =” (reads as “gets”) to indicate the value that a name will have in the resulting state For example: mode:=“Active” • Update can be seen only during the following step (this is in contrast to Java, C, Pascal, …) • All changes happen simultaneously, when you moving from one step to another. Then, all updates happen at once.(atomic transaction)**Programs**Example 1. Hello, world Main() step WriteLine(“hello, world!”) ASML uses indentations to denote block structure, and blocks can be places inside other blocks Statement block affect the scope of variables Whitespace includes blanks and new-line character, ASML does not recognize tab character for indentation !!!!!!! Main() is like main() in Java and C**Example 2. Reading a file**var F as File? = undef var Fcontents as String = “” var Mode as String = “Initial” Main() step until fixpoint if Mode = “Initial” then F :=open(“mfile.txt”) Mode :=“Reading” if Mode = “Reading” and length(FContents) =0 then FContents :=fread (F,1) if Mode = “Reading” and length(FContents) =1 then FContents := FContents + fread (F,1) if Mode = “Reading” and length(FContents) >1 then WriteLine (FContents) Mode :=“Finished”**S1**F= undef Fcontents =“” Mode = Initial S3 F= <open file 1> Fcontents =“a” Mode = Reading S2 F= <open file 1> Fcontents =“” Mode = Reading S4 F= <open file 1> Fcontents =“ab” Mode = Reading S5 F= <open file 1> Fcontents =“ab” Mode = Finished Example 2. Graph representation Step 1 Step 2 Step 3 Step5 Step 4**Key points**• Formal system specification complements informal specification techniques • Formal specifications are precise and unambiguous. They remove areas of doubt in a specification • Formal specification forces an analysis of the system requirements at an early stage. Correcting errors at this stage is cheaper than modifying a delivered system**Key points**• Formal specification techniques are most applicable in the development of critical systems and standards. • Algebraic techniques are suited to interface specification where the interface is defined as a set of object classes • Model-based techniques model the system using sets and functions. This simplifies some types of behavioural specification