Software development has been characterized by disconnects between activities. Abstract Throughout its short history, software development has been characterized by harmful disconnects between important activities such as planning, development and implementation. The problem is further exacerbated by the episodic and infrequent performance of activities such as planning, testing, integration and releases. Several emerging phenomena reflect attempts to address these problems.
Specification[ edit ] Formal methods may be used to give a description of the system to be developed, at whatever level s of detail desired.
This formal description can be used to guide further development activities see following sections ; additionally, it can be used to verify that the requirements for the system being developed have been completely and accurately specified.
The need for formal specification systems has been noted for years. Development[ edit ] Once a formal specification has been produced, the specification may be used as a guide while the concrete system is developed during the design process i.
If the formal specification is in an operational semantics, the observed behavior of the concrete system can be compared with the behavior of the specification which itself should be executable or simulateable.
Additionally, the operational commands of the specification may be amenable to direct translation into executable code. If the formal specification is in an axiomatic semantics, the preconditions and postconditions of the specification may become assertions in the executable code.
Verification[ edit ] Once a formal specification has been developed, the specification may be used as the basis for proving properties of the specification and hopefully by inference the developed system. Human-directed proof[ edit ] Sometimes, the motivation for proving the correctness of a system is not the obvious need for reassurance of the correctness of the system, but a desire to understand the system better.
Consequently, some proofs of correctness are produced in the style of mathematical proof: A "good" proof is one which is readable and understandable by other human readers. Critics of such approaches point out that the ambiguity inherent in natural language allows errors to be undetected in such proofs; often, subtle errors can be present in the low-level details typically overlooked by such proofs.
Additionally, the work involved in producing such a good proof requires a high level of mathematical sophistication and expertise. Automated proof[ edit ] In contrast, there is increasing interest in producing proofs of correctness of such systems by automated means.
Automated techniques fall into three general categories: Automated theorem provingin which a system attempts to produce a formal proof from scratch, given a description of the system, a set of logical axioms, and a set of inference rules.
Model checkingin which a system verifies certain properties by means of an exhaustive search of all possible states that a system could enter during its execution.
Abstract interpretationin which a system verifies an over-approximation of a behavioural property of the program, using a fixpoint computation over a possibly complete lattice representing it. Some automated theorem provers require guidance as to which properties are "interesting" enough to pursue, while others work without human intervention.
Model checkers can quickly get bogged down in checking millions of uninteresting states if not given a sufficiently abstract model. Proponents of such systems argue that the results have greater mathematical certainty than human-produced proofs, since all the tedious details have been algorithmically verified.
The training required to use such systems is also less than that required to produce good mathematical proofs by hand, making the techniques accessible to a wider variety of practitioners. Critics note that some of those systems are like oracles: There is also the problem of " verifying the verifier "; if the program which aids in the verification is itself unproven, there may be reason to doubt the soundness of the produced results.
Some modern model checking tools produce a "proof log" detailing each step in their proof, making it possible to perform, given suitable tools, independent verification.
The main feature of the abstract interpretation approach is that it provides a sound analysis, i. Moreover, it is efficiently scalable, by tuning the abstract domain representing the property to be analyzed, and by applying widening operators  to get fast convergence.
Applications[ edit ] Formal methods are applied in different areas of hardware and software, including routers, Ethernet switches, routing protocols, and security applications.
There are several examples in which they have been used to verify the functionality of the hardware and software used in DCs[ clarification needed ]. Intel uses such methods to verify its hardware and firmware permanent software programmed into a read-only memory [ citation needed ].
Dansk Datamatik Center used formal methods in the s to develop a compiler system for the Ada programming language that went on to become a long-lived commercial product. There are many areas of hardware, where Intel have used FMs to verify the working of the products, such as parameterized verification of cache coherent protocol,  Intel Core i7 processor execution engine validation  using theorem proving, BDDsand symbolic evaluationoptimization for Intel IA architecture using HOL light theorem prover,  and verification of high performance dual-port gigabit Ethernet controller with a support for PCI express protocol and Intel advance management technology using Cadence.
Formal methods are most likely to be applied to safety-critical or security-critical software and systems, such as avionics software. For sequential software, examples of formal methods include the B-Methodthe specification languages used in automated theorem provingRAISEand the Z notation.
In functional programmingproperty-based testing has allowed the mathematical specification and testing if not exhaustive testing of the expected behaviour of individual functions. The Object Constraint Language and specializations such as Java Modeling Language has allowed object-oriented systems to be formally specified, if not necessarily formally verified.
For concurrent software and systems, Petri netsprocess algebraand finite state machines which are based on automata theory - see also virtual finite state machine or event driven finite state machine allow executable software specification and can be used to build up and validate application behavior.
Another approach to formal methods in software development is to write a specification in some form of logic—usually a variation of first-order logic FOL —and then to directly execute the logic as though it were a program.
There is also work on mapping some version of English or another natural language automatically to and from logic, and executing the logic directly. Examples are Attempto Controlled Englishand Internet Business Logic, which do not seek to control the vocabulary or syntax.
A feature of systems that support bidirectional English-logic mapping and direct execution of the logic is that they can be made to explain their results, in English, at the business or scientific level. You can help by converting this section to prose, if appropriate.
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The software engineer creates formal specifications for this model. These methods minimize specification errors and this result in fewer errors when the user begins using the system. Formal methods comprise formal specification using mathematics to specify the desired properties of the system.