Editing Lazy evaluation (section)

==Performance==
The number of beta reductions to reduce a lambda term with call-by-need is no larger than the number needed by call-by-value or [[call-by-name]] reduction.<ref>{{cite book |last1=Niehren |first1=Joachim |title=Proceedings of the 23rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages - POPL '96 |chapter=Functional computation as concurrent computation |date=1996 |pages=333–343 |doi=10.1145/237721.237801 |isbn=0897917693 |s2cid=7332050 |url=https://hal.inria.fr/inria-00536819/file/POPL96.pdf |chapter-url=https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/25024/1/RR_95_14.pdf}}</ref><ref>{{cite journal |last1=Niehren |first1=Joachim |title=Uniform confluence in concurrent computation |journal=Journal of Functional Programming |date=September 2000 |volume=10 |issue=5 |pages=453–499 |doi=10.1017/S0956796800003762 |s2cid=66013 |url=https://hal.inria.fr/inria-00536801/document |access-date=7 January 2022}}</ref> And with certain programs the number of steps may be much smaller, for example a specific family of lambda terms using [[Church numeral]]s take an infinite amount of steps with call-by-value (i.e. never complete), an exponential number of steps with call-by-name, but only a polynomial number with call-by-need. Call-by-need embodies two optimizations - never repeat work (similar to call-by-value), and never perform unnecessary work (similar to call-by-name).<ref name=Stelle>{{cite thesis |last1=Stelle |first1=George Widgery |title=Shared-Environment Call-by-Need |date=July 2019 |url=https://digitalrepository.unm.edu/cgi/viewcontent.cgi?article=1099&context=cs_etds#page=23 |access-date=8 January 2022|publisher=University of New Mexico|type=PhD|pages=11–12}}</ref> 
Lazy evaluation can also lead to reduction in [[memory footprint]], since values are created when needed.<ref name="Smith2009">{{cite book|author=Chris Smith|title=Programming F#|url=https://books.google.com/books?id=gzVdyw2WoXMC&pg=PA79|access-date=31 December 2010|date=22 October 2009|publisher=O'Reilly Media, Inc.|isbn=978-0-596-15364-9|page=79}}</ref>

In practice, lazy evaluation may cause significant performance issues compared to eager evaluation. For example, on modern computer architectures, delaying a computation and performing it later is slower than performing it immediately. This can be alleviated through [[strictness analysis]].<ref name=Stelle/> Lazy evaluation can also introduce [[memory leak]]s due to unevaluated expressions.{{sfn|Launchbury|1993}}<ref>Edward Z. Yang. [http://blog.ezyang.com/2011/05/space-leak-zoo/ "Space leak zoo"].</ref>