Content deleted Content added
Tags: Mobile edit Mobile web edit |
m v2.05b - Bot T20 CW#61 - Fix errors for CW project (Reference before punctuation) |
||
Line 205:
Immutability of data can in many cases lead to execution efficiency by allowing the compiler to make assumptions that are unsafe in an imperative language, thus increasing opportunities for [[inline expansion]].<ref>{{cite journal |title=Immutability specification and its applications |author1=Igor Pechtchanski |author2=Vivek Sarkar |journal=Concurrency and Computation: Practice and Experience |volume=17 |issue=5–6 |pages=639–662 |year=2005 |doi=10.1002/cpe.853 |s2cid=34527406}}</ref> Even if the involved copying that may seem implicit when dealing with persistent immutable data structures might seem computationally costly, some functional programming languages, like [[Clojure]] solve this issue by implementing mechanisms for safe memory sharing between ''formally'' ''immutable'' data.<ref>{{Cite web |title=An In-Depth Look at Clojure Collections |url=https://www.infoq.com/articles/in-depth-look-clojure-collections/ |access-date=2024-04-29 |website=InfoQ |language=en}}</ref> [[Rust (programming language)|Rust]] distinguishes itself by it's approach to data immutability which involves immutable [[Reference (computer science)|references]]<ref>{{Cite web |title=References and Borrowing - The Rust Programming Language |url=https://doc.rust-lang.org/book/ch04-02-references-and-borrowing.html |access-date=2024-04-29 |website=doc.rust-lang.org}}</ref> and a concept called ''lifetimes.''<ref>{{Cite web |title=Validating References with Lifetimes - The Rust Programming Language |url=https://doc.rust-lang.org/book/ch10-03-lifetime-syntax.html |access-date=2024-04-29 |website=doc.rust-lang.org}}</ref>
Immutable data with separation of identity and state and [[Shared-nothing architecture|shared-nothing]] schemes can also potentially be more well-suited for [[Parallel computing|concurrent and parallel]] programming by the virtue of reducing or eliminating the risk of certain concurrency hazards, since concurrent operations are usually [[Linearizability|atomic]] and this allows eliminating the need for locks. This is how for example <code>java.util.concurrent</code> classes are implemented, where some of them are immutable variants of the corresponding classes that are not suitable for concurrent use.<ref>{{Cite web |title=Concurrent Collections (The Java™ Tutorials > Essential Java Classes > Concurrency) |url=https://docs.oracle.com/javase/tutorial/essential/concurrency/collections.html |access-date=2024-04-29 |website=docs.oracle.com}}</ref> Functional programming languages often have a concurrency model that instead of shared state and synchronization, leverages [[message passing]] mechanisms (such as the [[actor model]], where each actor is a container for state, behavior, child actors and a message queue).<ref>{{Cite web |date=2023-01-28 |title=Understanding The Actor Model To Build Non-blocking, High-throughput Distributed Systems - Scaleyourapp |url=https://scaleyourapp.com/actor-model/ |access-date=2024-04-29 |website=scaleyourapp.com |language=en-US}}</ref><ref>{{Cite book |last=Cesarini |first=Francesco |title=Erlang programming: a concurrent approach to software development |last2=Thompson |first2=Simon |publisher=O'Reilly Media, Inc. |year=2009 |isbn=0596555857, 9780596555856 |edition=1st |publication-date=2009-06-11 |page=6 |language=en}}</ref>
[[Lazy evaluation]] may also speed up the program, even asymptotically, whereas it may slow it down at most by a constant factor (however, it may introduce [[memory leak]]s if used improperly). Launchbury 1993<ref name=launchbury1993/> discusses theoretical issues related to memory leaks from lazy evaluation, and O'Sullivan ''et al.'' 2008<ref>{{cite web |url=http://book.realworldhaskell.org/read/profiling-and-optimization.html#x_eK1 |title=Chapter 25. Profiling and optimization |publisher=Book.realworldhaskell.org |access-date=2011-06-20}}</ref> give some practical advice for analyzing and fixing them.
Line 327:
Functional programming has been employed in a wide range of industrial applications. For example, [[Erlang (programming language)|Erlang]], which was developed by the [[Sweden|Swedish]] company [[Ericsson]] in the late 1980s, was originally used to implement [[Fault tolerance|fault-tolerant]] [[telecommunication]]s systems,<ref name="armstrong2007"/> but has since become popular for building a range of applications at companies such as [[Nortel]], [[Facebook]], [[Électricité de France]] and [[WhatsApp]].<ref name="erlang-faq"/><ref name="larson2009"/><ref>{{cite conference |last=Piro |first=Christopher |title=Functional Programming at Facebook |url=http://cufp.galois.com/2009/abstracts.html#ChristopherPiroEugeneLetuchy |year=2009 |conference=CUFP 2009 |access-date=2009-08-29 |archive-url=https://web.archive.org/web/20091017070140/http://cufp.galois.com/2009/abstracts.html#ChristopherPiroEugeneLetuchy |archive-date=2009-10-17 |url-status=dead}}</ref><ref name="Sim-Diasca"/><ref name="whatsapp.blog.2012">[http://blog.whatsapp.com/index.php/2012/01/1-million-is-so-2011/ 1 million is so 2011] {{Webarchive|url=https://web.archive.org/web/20140219234031/http://blog.whatsapp.com/index.php/2012/01/1-million-is-so-2011/ |date=2014-02-19}} // WhatsApp blog, 2012-01-06: "the last important piece of our infrastracture is Erlang"</ref> [[Scheme (programming language)|Scheme]], a dialect of [[Lisp (programming language)|Lisp]], was used as the basis for several applications on early [[Apple Macintosh]] computers<ref name="clinger1987"/><ref name="hartheimer1987"/> and has been applied to problems such as training-[[Computer simulation|simulation software]]<ref name="kidd2007"/> and [[telescope]] control.<ref name="cleis2006"/> [[OCaml]], which was introduced in the mid-1990s, has seen commercial use in areas such as financial analysis,<ref name="minksy2008"/> [[software driver|driver]] verification, industrial [[robot]] programming and static analysis of [[embedded software]].<ref name="leroy2007"/> [[Haskell]], though initially intended as a research language,<ref name="hudak2007"/> has also been applied in areas such as aerospace systems, hardware design and web programming.<ref name="haskell-industry"/><ref name="hudak2007"/>
Other functional programming languages that have seen use in industry include [[Scala (programming language)|Scala]],<ref>{{cite conference |last=Momtahan |first=Lee |title=Scala at EDF Trading: Implementing a Domain-Specific Language for Derivative Pricing with Scala |url=http://cufp.galois.com/2009/abstracts.html#LeeMomtahan |year=2009 |conference=CUFP 2009 |access-date=2009-08-29 |archive-url=https://web.archive.org/web/20091017070140/http://cufp.galois.com/2009/abstracts.html#LeeMomtahan |archive-date=2009-10-17 |url-status=dead}}</ref> [[F Sharp (programming language)|F#]],<ref name='quantFSharp'/><ref name='businessAppsFSharp'/> [[Wolfram Language]],<ref name="reference.wolfram.com"/> [[Lisp (programming language)|Lisp]],<ref>{{cite web |last=Graham |first=Paul |title=Beating the Averages |url=http://www.paulgraham.com/avg.html |year=2003 |access-date=2009-08-29}}</ref> [[Standard ML]]<ref>{{cite conference |last=Sims |first=Steve |title=Building a Startup with Standard ML |url=http://cufp.galois.com/2006/slides/SteveSims.pdf |year=2006 |conference=CUFP 2006 |access-date=2009-08-29}}</ref><ref>{{cite conference |last=Laurikari |first=Ville |title=Functional Programming in Communications Security. |url=http://cufp.galois.com/2007/abstracts.html#VilleLaurikari |year=2007 |conference=CUFP 2007 |access-date=2009-08-29}}</ref> and Clojure.<ref>{{cite web |url=http://www.infoq.com/news/2009/01/clojure_production |last=Lorimer |first=R. J. |title=Live Production Clojure Application Announced |date=19 January 2009|work=InfoQ}}</ref> Scala has been widely used in [[Data science]],<ref>{{Cite book |last=Bugnion |first=Pascal |title=Scala for Data Science |publisher=[[Packt]] |year=2016 |isbn=9781785281372 |edition=1st |language=en-US}}</ref>
Functional "platforms" have been popular in finance for risk analytics (particularly with large investment banks). Risk factors are coded as functions that form interdependent graphs (categories) to measure correlations in market shifts, similar in manner to [[Gröbner basis]] optimizations but also for regulatory frameworks such as [[Comprehensive Capital Analysis and Review]]. Given the use of OCaml and [[Caml]] variations in finance, these systems are sometimes considered related to a [[categorical abstract machine]]. Functional programming is heavily influenced by [[category theory]].{{Citation needed|date=August 2022}}
| |||