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{{Short description|Mathematical program specifications}}
{{Short description|Mathematical program specifications}}
In [[computer science]], '''formal methods''' are [[mathematics|mathematically]] rigorous techniques for the [[formal specification|specification]], development, [[Program analysis|analysis]], and [[formal verification|verification]] of [[software]] and [[computer hardware|hardware]] systems.<ref name="butler">{{cite web| first=R. W. | last=Butler | title=What is Formal Methods? | url=http://shemesh.larc.nasa.gov/fm/fm-what.html|date=2001-08-06|access-date=2006-11-16}}</ref> The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design.<ref>{{cite journal| first=C. Michael | last=Holloway | title=Why Engineers Should Consider Formal Methods|url=http://klabs.org/richcontent/verification/holloway/nasa-97-16dasc-cmh.pdf|publisher=16th Digital Avionics Systems Conference (27–30 October 1997)|access-date=2006-11-16|url-status=dead|archive-url=https://web.archive.org/web/20061116210448/http://klabs.org/richcontent/verification/holloway/nasa-97-16dasc-cmh.pdf|archive-date=16 November 2006}}</ref>
In [[computer science]], '''formal methods''' are [[mathematics|mathematically]] rigorous techniques for the [[formal specification|specification]], development, [[Program analysis|analysis]], and [[formal verification|verification]] of [[software]] and [[computer hardware|hardware]] systems.<ref name="butler">{{cite web| first=R. W. | last=Butler | title=What is Formal Methods? | url=http://shemesh.larc.nasa.gov/fm/fm-what.html|date=2001-08-06|access-date=2006-11-16}}</ref> The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design.<ref>{{cite journal| first=C. Michael | last=Holloway | title=Why Engineers Should Consider Formal Methods|url=http://klabs.org/richcontent/verification/holloway/nasa-97-16dasc-cmh.pdf|publisher=16th Digital Avionics Systems Conference (27–30 October 1997)|access-date=2006-11-16|url-status=dead|archive-url=https://web.archive.org/web/20061116210448/http://klabs.org/richcontent/verification/holloway/nasa-97-16dasc-cmh.pdf|archive-date=16 November 2006}}</ref>


Formal methods employ a variety of [[theoretical computer science]] fundamentals, including [[logic in computer science|logic]] calculi, [[formal language]]s, [[automata theory]], [[control theory]], [[program semantics]], [[type systems]], and [[type theory]].<ref>Monin, pp.3-4</ref>
Formal methods employ a variety of [[theoretical computer science]] fundamentals, including [[logic in computer science|logic]] calculi, [[formal language]]s, [[automata theory]], [[control theory]], [[program semantics]], [[type systems]], and [[type theory]].<ref>Monin, pp.3-4</ref>

==Background==
⚫
Semi-formal methods are formalisms and languages that are not considered fully "formal". It defers the task of completing the semantics to a later stage, which is then done either by human interpretation or by interpretation through software like code or test case [[Generator (computer programming)|generators]].<ref>{{Cite book|title=X2R-2, deliverable D5.1}}</ref>

==Taxonomy==
{{unreferenced section|date=April 2022}}
⚫
Formal methods can be used at a number of levels:

* Level 0: [[Formal specification]] may be undertaken and then a program developed from this informally. This has been dubbed ''formal methods lite''. This may be the most cost-effective option in many cases.
* Level 1: [[Formal development]] and [[formal verification]] may be used to produce a program in a more formal manner. For example, [[formal proof|proof]]s of properties or [[program refinement|refinement]] from the [[formal specification|specification]] to a program may be undertaken. This may be most appropriate in [[High integrity software|high-integrity systems]] involving [[safety]] or [[security]].
* Level 2: [[Automated theorem prover|Theorem prover]]s may be used to undertake fully formal machine-checked proofs. Despite improving tools and declining costs, this can be very expensive and is only practically worthwhile if the cost of mistakes is very high (e.g., in critical parts of [[operating system]] or [[microprocessor]] design).

Further information on this is expanded [[#Uses|below]].

As with [[Formal semantics of programming languages|programming language semantics]], styles of formal methods may be roughly classified as follows:

* [[Denotational semantics]], in which the meaning of a system is expressed in the mathematical theory of [[domain theory|domains]]. Proponents of such methods rely on the well-understood nature of domains to give meaning to the system; critics point out that not every system may be intuitively or naturally viewed as a function.
* [[Operational semantics]], in which the meaning of a system is expressed as a sequence of actions of a (presumably) simpler [[computational model]]. Proponents of such methods point to the simplicity of their models as a means to expressive clarity; critics counter that the problem of semantics has just been delayed (who defines the semantics of the simpler model?).
* [[Axiomatic semantics]], in which the meaning of the system is expressed in terms of [[precondition]]s and [[postcondition]]s that are true before and after the system performs a task, respectively. Proponents note the connection to classical [[logic]]; critics note that such semantics never really describe what a system ''does'' (merely what is true before and afterwards).

⚫
===Lightweight formal methods===
⚫
Some practitioners believe that the formal methods community has overemphasized full formalization of a specification or design.<ref>[[Daniel Jackson (computer scientist)|Daniel Jackson]] and [[Jeannette Wing]], [http://people.csail.mit.edu/dnj/publications/ieee96-roundtable.html "Lightweight Formal Methods"], ''IEEE Computer'', April 1996</ref><ref>Vinu George and Rayford Vaughn, [http://www.stsc.hill.af.mil/crosstalk/2003/01/George.html "Application of Lightweight Formal Methods in Requirement Engineering"] {{webarchive|url=https://web.archive.org/web/20060301022259/http://www.stsc.hill.af.mil/crosstalk/2003/01/George.html |date=2006-03-01 }}, ''Crosstalk: The Journal of Defense Software Engineering'', January 2003</ref> They contend that the [[Expressive power (computer science)|expressiveness]] of the languages involved, as well as the complexity of the systems being modelled, make full formalization a difficult and expensive task. As an alternative, various ''lightweight'' formal methods, which emphasize partial specification and focused application, have been proposed. Examples of this lightweight approach to formal methods include the [[Alloy language|Alloy]] object modelling notation,<ref>Daniel Jackson, [http://people.csail.mit.edu/dnj/publications/alloy-journal.pdf "Alloy: A Lightweight Object Modelling Notation"], ''ACM Transactions on Software Engineering and Methodology (TOSEM)'', Volume 11, Issue 2 (April 2002), pp. 256-290</ref> Denney's synthesis of some aspects of the [[Z notation]] with [[use case]] driven development,<ref>Richard Denney, ''Succeeding with Use Cases: Working Smart to Deliver Quality'', Addison-Wesley Professional Publishing, 2005, {{ISBN|0-321-31643-6}}.</ref> and the CSK [[Vienna Development Method|VDM]] Tools.<ref>Sten Agerholm and Peter G. Larsen, [http://home0.inet.tele.dk/pgl/fmtrends98.pdf "A Lightweight Approach to Formal Methods"] {{webarchive|url=https://web.archive.org/web/20060309041943/http://home0.inet.tele.dk/pgl/fmtrends98.pdf |date=2006-03-09 }}, In ''Proceedings of the International Workshop on Current Trends in Applied Formal Methods'', Boppard, Germany, Springer-Verlag, October 1998</ref>


==Uses==
==Uses==
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===Specification===
===Specification===
{{Main|Formal specification}}
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, or formalising system requirements by expressing them in a formal language with a precise and unambiguously defined syntax and semantics.
Formal methods may be used to give a formal description of the system to be developed, at whatever level of detail desired. Further formal methods may depend on this specification to synthesize a program or to verify the correctness of a system.


Alternatively, specification may be the only stage in which formal methods is used. By writing a specification, ambiguities in the informal requirements can be discovered and resolved. Additionally, engineers can use a formal specification as a reference to guide their development processes.<ref>{{cite journal|last1=Utting|first1=Mark|last2=Reeves|first2=Steve|date=August 31, 2001|title=Teaching formal methods lite via testing|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/stvr.223|journal=Software Testing, Verification and Reliability|volume=11|issue=3|doi=10.1002/stvr.223}}</ref>
⚫
The need for formal specification systems has been noted for years. In the [[ALGOL 58]] report,<ref>{{cite conference | first = J.W. | last = Backus | title = The Syntax and Semantics of the Proposed International Algebraic Language of Zürich ACM-GAMM Conference | book-title = Proceedings of the International Conference on Information Processing | publisher = UNESCO | year = 1959 }}</ref> [[John Backus]] presented a formal notation for describing [[Syntax (programming languages)|programming language syntax]], later named [[Backus normal form]] then renamed [[Backus–Naur form]] (BNF).<ref>[[Donald Knuth|Knuth, Donald E.]] (1964), Backus Normal Form vs Backus Naur Form. ''[[Communications of the ACM]]'', 7(12):735–736.</ref> Backus also wrote that a formal description of the meaning of syntactically valid ALGOL programs was not completed in time for inclusion in the report. "Therefore the formal treatment of the semantics of legal programs will be included in a subsequent paper." It never appeared.


⚫
The need for formal specification systems has been noted for years. In the [[ALGOL 58]] report,<ref>{{cite conference | first = J.W. | last = Backus | title = The Syntax and Semantics of the Proposed International Algebraic Language of Zürich ACM-GAMM Conference | book-title = Proceedings of the International Conference on Information Processing | publisher = UNESCO | year = 1959 }}</ref> [[John Backus]] presented a formal notation for describing [[Syntax (programming languages)|programming language syntax]], later named [[Backus normal form]] then renamed [[Backus–Naur form]] (BNF).<ref>[[Donald Knuth|Knuth, Donald E.]] (1964), Backus Normal Form vs Backus Naur Form. ''[[Communications of the ACM]]'', 7(12):735–736.</ref> Backus also wrote that a formal description of the meaning of syntactically valid ALGOL programs was not completed in time for inclusion in the report. "Therefore the formal treatment of the semantics of legal programs will be included in a subsequent paper." It never appeared.{{citation needed}}
===Development===
Formal development is the use of formal methods as an integrated part of a tool-supported system development process.


===Synthesis===
Once a formal specification has been produced, the specification may be used as a guide while the concrete system is [[Software development|developed]] during the [[Software design|design]] process (i.e., realized typically in [[software]], but also potentially in [[Computer hardware|hardware]]). For example:
{{Main|Program synthesis}}

Program synthesis is the process of automatically creating a program that conforms to a specification. Deductive synthesis approaches rely on a complete formal specification of the program, whereas inductive approaches infer the specification from examples. Synthesizers perform a search over the space of possible programs to find a program consistent with the specification. Because of the size of this search space, developing efficient search algorithms is one of the major challenges in program synthesis.<ref>{{cite journal|last1=Gulwani|first1=Sumit|last2=Polozov|first2=Oleksandr|last3=Singh|first3=Rishabh|date=2017|title=Program Synthesis|url=https://www.nowpublishers.com/article/Details/PGL-010|journal=Foundations and Trends in Programming Languages|volume=4|issue=1-2}}</ref>
* If the formal specification is in operational semantics, the observed behavior of the concrete system can be compared with the behavior of the specification (which itself should be executable or simulatable). Additionally, the operational commands of the specification may be amenable to direct translation into executable code.
* If the formal specification is in axiomatic semantics, the preconditions and postconditions of the specification may become [[assertion (computing)|assertion]]s in the executable code.


===Verification===
===Verification===
{{Main|Formal verification}}

Formal verification is the use of software tools to prove properties of a formal specification, or to prove that a formal model of a system [[implementation]] satisfies its specification.
Formal verification is the use of software tools to prove properties of a formal specification, or to prove that a formal model of a system [[implementation]] satisfies its specification.


Line 50: Line 29:


==== Sign-off verification ====
==== Sign-off verification ====
Sign-off verification is the use of a formal verification tool that is highly trusted. Such a tool can replace traditional verification methods (the tool may even be certified).
Sign-off verification is the use of a formal verification tool that is highly trusted. Such a tool can replace traditional verification methods (the tool may even be certified).{{citation needed}}


====Human-directed proof====
====Human-directed proof====
Line 70: Line 49:


The main feature of the abstract interpretation approach is that it provides a sound analysis, i.e. no false negatives are returned. Moreover, it is efficiently scalable, by tuning the abstract domain representing the property to be analyzed, and by applying widening operators<ref>A. Cortesi and M. Zanioli, [http://www.dsi.unive.it/~cortesi/paperi/CL_2011.pdf Widening and Narrowing Operators for Abstract Interpretation]. Computer Languages, Systems and Structures. Volume 37(1), pp. 24–42, Elsevier, {{ISSN|1477-8424}} (2011).</ref> to get fast convergence.
The main feature of the abstract interpretation approach is that it provides a sound analysis, i.e. no false negatives are returned. Moreover, it is efficiently scalable, by tuning the abstract domain representing the property to be analyzed, and by applying widening operators<ref>A. Cortesi and M. Zanioli, [http://www.dsi.unive.it/~cortesi/paperi/CL_2011.pdf Widening and Narrowing Operators for Abstract Interpretation]. Computer Languages, Systems and Structures. Volume 37(1), pp. 24–42, Elsevier, {{ISSN|1477-8424}} (2011).</ref> to get fast convergence.

==Techniques==
{{Expand section}}
⚫
Formal methods includes a number of different techniques.

===Specification languages===
{{Main|Specification language}}
The design of a computing system can be expressed using a specification language, which is a formal language that includes a proof system. Using this proof system, formal verification tools can reason about the specification and establish that a system adheres to the specification.<ref>{{cite book|last1=Bjørner|first1=Dines|last2=Henson|first2=Martin C.|date=2008|title=Logics of Specification Languages|pages=VII–XI}}</ref>

===SAT solvers===
{{Main|SAT solver}}



==Applications==
==Applications==
Line 91: Line 82:


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]]—and then to directly execute the logic as though it were a program. The [[Web Ontology Language|OWL]] language, based on [[description logic]], is an example. There is also work on mapping some version of English (or another natural language) automatically to and from logic, as well as executing the logic directly. Examples are [[Attempto Controlled English]], and 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.{{citation needed|date=June 2016}}
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]]—and then to directly execute the logic as though it were a program. The [[Web Ontology Language|OWL]] language, based on [[description logic]], is an example. There is also work on mapping some version of English (or another natural language) automatically to and from logic, as well as executing the logic directly. Examples are [[Attempto Controlled English]], and 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.{{citation needed|date=June 2016}}

⚫
==Semi-formal methods==
⚫
Semi-formal methods are formalisms and languages that are not considered fully "formal". It defers the task of completing the semantics to a later stage, which is then done either by human interpretation or by interpretation through software like code or test case [[Generator (computer programming)|generators]].<ref>{{Cite book|title=X2R-2, deliverable D5.1}}</ref>

⚫
Some practitioners believe that the formal methods community has overemphasized full formalization of a specification or design.<ref>[[Daniel Jackson (computer scientist)|Daniel Jackson]] and [[Jeannette Wing]], [http://people.csail.mit.edu/dnj/publications/ieee96-roundtable.html "Lightweight Formal Methods"], ''IEEE Computer'', April 1996</ref><ref>Vinu George and Rayford Vaughn, [http://www.stsc.hill.af.mil/crosstalk/2003/01/George.html "Application of Lightweight Formal Methods in Requirement Engineering"] {{webarchive|url=https://web.archive.org/web/20060301022259/http://www.stsc.hill.af.mil/crosstalk/2003/01/George.html |date=2006-03-01 }}, ''Crosstalk: The Journal of Defense Software Engineering'', January 2003</ref> They contend that the [[Expressive power (computer science)|expressiveness]] of the languages involved, as well as the complexity of the systems being modelled, make full formalization a difficult and expensive task. As an alternative, various ''lightweight'' formal methods, which emphasize partial specification and focused application, have been proposed. Examples of this lightweight approach to formal methods include the [[Alloy language|Alloy]] object modelling notation,<ref>Daniel Jackson, [http://people.csail.mit.edu/dnj/publications/alloy-journal.pdf "Alloy: A Lightweight Object Modelling Notation"], ''ACM Transactions on Software Engineering and Methodology (TOSEM)'', Volume 11, Issue 2 (April 2002), pp. 256-290</ref> Denney's synthesis of some aspects of the [[Z notation]] with [[use case]] driven development,<ref>Richard Denney, ''Succeeding with Use Cases: Working Smart to Deliver Quality'', Addison-Wesley Professional Publishing, 2005, {{ISBN|0-321-31643-6}}.</ref> and the CSK [[Vienna Development Method|VDM]] Tools.<ref>Sten Agerholm and Peter G. Larsen, [http://home0.inet.tele.dk/pgl/fmtrends98.pdf "A Lightweight Approach to Formal Methods"] {{webarchive|url=https://web.archive.org/web/20060309041943/http://home0.inet.tele.dk/pgl/fmtrends98.pdf |date=2006-03-09 }}, In ''Proceedings of the International Workshop on Current Trends in Applied Formal Methods'', Boppard, Germany, Springer-Verlag, October 1998</ref>


==Formal methods and notations==
==Formal methods and notations==

Revision as of 03:57, 20 June 2024

In computer science, formal methods are mathematically rigorous techniques for the specification, development, analysis, and verification of software and hardware systems.[1] The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design.[2]

Formal methods employ a variety of theoretical computer science fundamentals, including logic calculi, formal languages, automata theory, control theory, program semantics, type systems, and type theory.[3]

Uses

Formal methods can be applied at various points through the development process.

Specification

Main article: Formal specification

Formal methods may be used to give a formal description of the system to be developed, at whatever level of detail desired. Further formal methods may depend on this specification to synthesize a program or to verify the correctness of a system.

Alternatively, specification may be the only stage in which formal methods is used. By writing a specification, ambiguities in the informal requirements can be discovered and resolved. Additionally, engineers can use a formal specification as a reference to guide their development processes.[4]

The need for formal specification systems has been noted for years. In the ALGOL 58 report,[5] John Backus presented a formal notation for describing programming language syntax, later named Backus normal form then renamed Backus–Naur form (BNF).[6] Backus also wrote that a formal description of the meaning of syntactically valid ALGOL programs was not completed in time for inclusion in the report. "Therefore the formal treatment of the semantics of legal programs will be included in a subsequent paper." It never appeared.[citation needed]

Synthesis

Main article: Program synthesis

Program synthesis is the process of automatically creating a program that conforms to a specification. Deductive synthesis approaches rely on a complete formal specification of the program, whereas inductive approaches infer the specification from examples. Synthesizers perform a search over the space of possible programs to find a program consistent with the specification. Because of the size of this search space, developing efficient search algorithms is one of the major challenges in program synthesis.[7]

Verification

Main article: Formal verification

Formal verification is the use of software tools to prove properties of a formal specification, or to prove that a formal model of a system implementation satisfies its specification.

Once a formal specification has been developed, the specification may be used as the basis for proving properties of the specification, and by inference, properties of the system implementation.

Sign-off verification

Sign-off verification is the use of a formal verification tool that is highly trusted. Such a tool can replace traditional verification methods (the tool may even be certified).[citation needed]

Human-directed proof

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: handwritten (or typeset) using natural language, using a level of informality common to such proofs. A "good" proof is one that 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

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 proving, in 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 checking, in 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 interpretation, in 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: they make a pronouncement of truth, yet give no explanation of that truth. There is also the problem of "verifying the verifier"; if the program that 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.e. no false negatives are returned. Moreover, it is efficiently scalable, by tuning the abstract domain representing the property to be analyzed, and by applying widening operators[8] to get fast convergence.

Techniques

Formal methods includes a number of different techniques.

Specification languages

Main article: Specification language

The design of a computing system can be expressed using a specification language, which is a formal language that includes a proof system. Using this proof system, formal verification tools can reason about the specification and establish that a system adheres to the specification.[9]

SAT solvers

Main article: SAT solver


Applications

Formal methods are applied in different areas of hardware and software, including routers, Ethernet switches, routing protocols, security applications, and operating system microkernels such as seL4. There are several examples in which they have been used to verify the functionality of the hardware and software used in data centres. IBM used ACL2, a theorem prover, in the AMD x86 processor development process.[citation 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 1980s to develop a compiler system for the Ada programming language that went on to become a long-lived commercial product.[10][11]

There are several other projects of NASA in which formal methods are applied, such as Next Generation Air Transportation System[citation needed], Unmanned Aircraft System integration in National Airspace System,[12] and Airborne Coordinated Conflict Resolution and Detection (ACCoRD).[13] B-Method with Atelier B,[14] is used to develop safety automatisms for the various subways installed throughout the world by Alstom and Siemens, and also for Common Criteria certification and the development of system models by ATMEL and STMicroelectronics.

Formal verification has been frequently used in hardware by most of the well-known hardware vendors, such as IBM, Intel, and AMD. There are many areas of hardware, where Intel have used formal methods to verify the working of the products, such as parameterized verification of cache-coherent protocol,[15] Intel Core i7 processor execution engine validation [16] (using theorem proving, BDDs, and symbolic evaluation), optimization for Intel IA-64 architecture using HOL light theorem prover,[17] and verification of high-performance dual-port gigabit Ethernet controller with support for PCI express protocol and Intel advance management technology using Cadence.[18] Similarly, IBM has used formal methods in the verification of power gates,[19] registers,[20] and functional verification of the IBM Power7 microprocessor.[21]

In software development

In software development, formal methods are mathematical approaches to solving software (and hardware) problems at the requirements, specification, and design levels. Formal methods are most likely to be applied to safety-critical or security-critical software and systems, such as avionics software. Software safety assurance standards, such as DO-178C allows the usage of formal methods through supplementation, and Common Criteria mandates formal methods at the highest levels of categorization.

For sequential software, examples of formal methods include the B-Method, the specification languages used in automated theorem proving, RAISE, and the Z notation.

In functional programming, property-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 nets, process algebra, and 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 behaviour.

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—and then to directly execute the logic as though it were a program. The OWL language, based on description logic, is an example. There is also work on mapping some version of English (or another natural language) automatically to and from logic, as well as executing the logic directly. Examples are Attempto Controlled English, and 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.[citation needed]

Semi-formal methods

Semi-formal methods are formalisms and languages that are not considered fully "formal". It defers the task of completing the semantics to a later stage, which is then done either by human interpretation or by interpretation through software like code or test case generators.[22]

Some practitioners believe that the formal methods community has overemphasized full formalization of a specification or design.[23][24] They contend that the expressiveness of the languages involved, as well as the complexity of the systems being modelled, make full formalization a difficult and expensive task. As an alternative, various lightweight formal methods, which emphasize partial specification and focused application, have been proposed. Examples of this lightweight approach to formal methods include the Alloy object modelling notation,[25] Denney's synthesis of some aspects of the Z notation with use case driven development,[26] and the CSK VDM Tools.[27]

Formal methods and notations

There are a variety of formal methods and notations available.

Specification languages

Model checkers

Main article: List of model checking tools
  • ESBMC[28]
  • MALPAS Software Static Analysis Toolset – an industrial-strength model checker used for formal proof of safety-critical systems
  • PAT – a free model checker, simulator and refinement checker for concurrent systems and CSP extensions (e.g., shared variables, arrays, fairness)
  • SPIN
  • UPPAAL

Solvers and competitions

Many problems in formal methods are NP-hard, but can be solved in cases arising in practice. For example, the boolean satisfiability problem is NP-complete by the Cook–Levin theorem, but SAT solvers can solve a variety of large instances. There are "solvers" for a variety of problems that arise in formal methods, and there are many periodic competitions to evaluate the state-of-the-art in solving such problems.[29]

Organizations

Main page: Category:Formal methods organizations

See also

References

  1. ^ Butler, R. W. (2001-08-06). "What is Formal Methods?". Retrieved 2006-11-16.
  2. ^ Holloway, C. Michael. "Why Engineers Should Consider Formal Methods" (PDF). 16th Digital Avionics Systems Conference (27–30 October 1997). Archived from the original (PDF) on 16 November 2006. Retrieved 2006-11-16. {{cite journal}}: Cite journal requires |journal= (help)
  3. ^ Monin, pp.3-4
  4. ^ Utting, Mark; Reeves, Steve (August 31, 2001). "Teaching formal methods lite via testing". Software Testing, Verification and Reliability. 11 (3). doi:10.1002/stvr.223.
  5. ^ Backus, J.W. (1959). "The Syntax and Semantics of the Proposed International Algebraic Language of Zürich ACM-GAMM Conference". Proceedings of the International Conference on Information Processing. UNESCO.
  6. ^ Knuth, Donald E. (1964), Backus Normal Form vs Backus Naur Form. Communications of the ACM, 7(12):735–736.
  7. ^ Gulwani, Sumit; Polozov, Oleksandr; Singh, Rishabh (2017). "Program Synthesis". Foundations and Trends in Programming Languages. 4 (1–2).
  8. ^ A. Cortesi and M. Zanioli, Widening and Narrowing Operators for Abstract Interpretation. Computer Languages, Systems and Structures. Volume 37(1), pp. 24–42, Elsevier, ISSN 1477-8424 (2011).
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Further reading

Archival material
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