Relevant bibliographies by topics / Programming functions

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Programming functions'

Author: Grafiati
Published: 28 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Programming functions"

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Neralić, Luka, and Sanjo Zlobec. "LFS functions in multi-objective programming." Applications of Mathematics 41, no. 5 (1996): 347–66. http://dx.doi.org/10.21136/am.1996.134331.

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Turner, D. "Total Functional Programming." JUCS - Journal of Universal Computer Science 10, no. (7) (2004): 751–68. https://doi.org/10.3217/jucs-010-07-0751.

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The driving idea of functional programming is to make programming more closely related to mathematics. A program in a functional language such as Haskell or Miranda consists of equations which are both computation rules and a basis for simple algebraic reasoning about the functions and data structures they define. The existing model of functional programming, although elegant and powerful, is compromised to a greater extent than is commonly recognised by the presence of partial functions. We consider a simple discipline of total functional programming designed to exclude the possibility of non
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Odersky, Martin. "Programming with variable functions." ACM SIGPLAN Notices 34, no. 1 (1999): 105–16. http://dx.doi.org/10.1145/291251.289433.

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Rhodes, Frank, and H. Paul Williams. "Discrete subadditive functions as Gomory functions." Mathematical Proceedings of the Cambridge Philosophical Society 117, no. 3 (1995): 559–74. http://dx.doi.org/10.1017/s0305004100073370.

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Our aim, in this paper, is to study a class of functions which occurs in pure integer programming, and to investigate conditions under which discrete subadditive functions belong to that class. The inspiration for the paper was the problem of classifying discrete metrics used in pattern recognition, while the methods of proof of the main theorem are those of pure integer programming.
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Nigiyan, S. A. "$ \lambda $-DEFINABILITY OF BUILT-IN McCARTHY FUNCTIONS AS FUNCTIONS WITH INDETERMINATE VALUES OF ARGUMENTS." Proceedings of the YSU A: Physical and Mathematical Sciences 53, no. 3 (250) (2019): 191–202. http://dx.doi.org/10.46991/pysu:a/2019.53.3.191.

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The built-in functions of programming languages are functions with indeterminate values of arguments. The built-in McCarthy functions $ car $, $ cdr $, $ cons $, $ null $, $ atom $, $ if $, $ eq $, $ not $, $ and $, $ or $, are used in all functional programming languages. In this paper we show the $ \lambda $-definability of the built-in McCarthy functions as functions with indeterminate values of arguments. This result is necessary when translating typed functional programming languages into untyped functional programming languages.
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Baykasoğlu, Adil, and Sultan Maral. "Fuzzy functions via genetic programming." Journal of Intelligent & Fuzzy Systems 27, no. 5 (2014): 2355–64. http://dx.doi.org/10.3233/ifs-141205.

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Chou, J. H., Wei-Shen Hsia, and Tan-Yu Lee. "Convex programming with set functions." Rocky Mountain Journal of Mathematics 17, no. 3 (1987): 535–44. http://dx.doi.org/10.1216/rmj-1987-17-3-535.

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Savage, Neil. "Using functions for easier programming." Communications of the ACM 61, no. 5 (2018): 29–30. http://dx.doi.org/10.1145/3193776.

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Wang, Chung-lie, and An-qing Xing. "Dynamic programming and penalty functions." Journal of Mathematical Analysis and Applications 150, no. 2 (1990): 562–73. http://dx.doi.org/10.1016/0022-247x(90)90123-w.

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Weir, T. "Programming with semilocally convex functions." Journal of Mathematical Analysis and Applications 168, no. 1 (1992): 1–12. http://dx.doi.org/10.1016/0022-247x(92)90185-g.

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Dissertations / Theses on the topic "Programming functions"

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Christiansen, Jan [Verfasser]. "Investigating Minimally Strict Functions in Functional Programming / Jan Christiansen." Kiel : Universitätsbibliothek Kiel, 2012. http://d-nb.info/1024079805/34.

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Sharifi, Mokhtarian Faranak. "Mathematical programming with LFS functions." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=56762.

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Differentiable functions with a locally flat surface (LFS) have been recently introduced and studied in convex optimization. Here we extend this motion in two directions: to non-smooth convex and smooth generalized convex functions. An important feature of these functions is that the Karush-Kuhn-Tucker condition is both necessary and sufficient for optimality. Then we use the properties of linear LFS functions and basic point-to-set topology to study the "inverse" programming problem. In this problem, a feasible, but nonoptimal, point is made optimal by stable perturbations of the parameters.
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Trujillo-Cortez, Refugio. "LFS functions in stable bilevel programming." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ37171.pdf.

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Ahluwalia, Manu. "Co-evolving functions in genetic programming." Thesis, University of the West of England, Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322427.

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Stark, Ian David Bede. "Names and higher-order functions." Thesis, University of Cambridge, 1994. https://www.repository.cam.ac.uk/handle/1810/251879.

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Many functional programming languages rely on the elimination of 'impure' features: assignment to variables, exceptions and even input/output. But some of these are genuinely useful, and it is of real interest to establish how they can be reintroducted in a controlled way. This dissertation looks in detail at one example of this: the addition to a functional language of dynamically generated names. Names are created fresh, they can be compared with each other and passed around, but that is all. As a very basic example of state, they capture the graduation between private and public, local and
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Shapiro, David. "Compiling Evaluable Functions in the Godel Programming Language." PDXScholar, 1996. https://pdxscholar.library.pdx.edu/open_access_etds/5101.

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We present an extension of the Godel logic programming language code generator which compiles user-defined functions. These functions may be used as arguments in predicate or goal clauses. They are defined in extended Godel as rewrite rules. A translation scheme is introduced to convert function definitions into predicate clauses for compilation. This translation scheme and the compilation of functional arguments both employ leftmost-innermost narrowing. As function declarations are indistinguishable from constructor declarations, a function detection method is implemented. The ultimate goal o
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Edwards, Teresa Dawn. "The box method for minimizing strictly convex functions over convex sets." Diss., Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/30690.

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Chen, Jein-Shan. "Merit functions and nonsmooth functions for the second-order cone complementarity problem /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/5782.

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Ferris, Michael Charles. "Weak sharp minima and penalty functions in mathematical programming." Thesis, University of Cambridge, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292969.

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Schanzer, Emmanuel Tanenbaum. "Algebraic Functions, Computer Programming, and the Challenge of Transfer." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:16461037.

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Students' struggles with algebra are well documented. Prior to the introduction of functions, mathematics is typically focused on applying a set of arithmetic operations to compute an answer. The introduction of functions, however, marks the point at which mathematics begins to focus on building up abstractions as a way to solve complex problems. A common refrain about word problems is that “the equations are easy to solve - the hard part is setting them up!” A student of algebra is asked to identify functional relationships in the world around them - to set up the equations that describe a sy
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Books on the topic "Programming functions"

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Burstall, R. M. Inductively defined functions in functional programming languages. University of Edinburgh, Laboratory for Foundations of Computer Science, 1987.

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Doug, DeGroot, and Lindstrom Gary, eds. Logic programming: Functions, relations, andequations. Prentice-Hall, 1986.

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Doug, DeGroot, and Lindstrom Gary, eds. Logic programming, functions, relations, and equations. Prentice-Hall, 1986.

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Li, Lan. Studying functions and limits through programming. typescript, 1992.

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Henglein, Fritz. Programming with structures, functions, and objects. Courant Institute of Mathematical Sciences, New York University, 1991.

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Bobak, Angelo. Programming Microsoft SQL Server 2022 Aggregate Functions. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0862-3.

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Davis, Alan M. Software requirements: Objects, functions and states. Prentice-Hall International, 1993.

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Reddy, Uday Sankara. Logic languages based on functions: Semantics and implementation. Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1986.

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Kibzun, A. I. Stochastic programming problems with probability and quantile functions. Wiley, 1996.

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Bobak, Angelo. Programming Microsoft Analytical Functions with SQL Server 2022. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-1012-1.

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Book chapters on the topic "Programming functions"

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Jungck, Peder, Ralph Duncan, and Dwight Mulcahy. "Functions." In packetC Programming. Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-4159-1_7.

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Sharma, Vijay Kumar, Vimal Kumar, Swati Sharma, and Shashwat Pathak. "Functions." In Python Programming. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003185505-7.

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Jena, Sisir Kumar. "Functions." In C Programming. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003188254-9.

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Oza, K. S., S. R. Patil, and R. K. Kamat. "Programming for Functional Functions." In 'C' Programming in an Open Source Paradigm. River Publishers, 2022. http://dx.doi.org/10.1201/9781003337461-4.

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Rolland, F. D. "Functions." In Programming with VDM. Macmillan Education UK, 1992. http://dx.doi.org/10.1007/978-1-349-12692-7_3.

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Rothwell, William “Bo.” "Functions." In Beginning Perl Programming. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5055-6_12.

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Upadhyaya, Bhim P. "Functions." In Programming with Scala. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69368-2_9.

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Ettinger, Jean. "Functions." In Programming in C++. Macmillan Education UK, 1994. http://dx.doi.org/10.1007/978-1-349-23304-5_5.

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Nagar, Sandeep. "Functions." In Beginning Julia Programming. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3171-5_10.

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Gazi, Orhan. "Functions." In Modern C Programming. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45361-8_9.

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Conference papers on the topic "Programming functions"

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He, Yifan, and Claus Aranha. "Evolving Benchmark Functions to Compare Evolutionary Algorithms via Genetic Programming." In 2024 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2024. http://dx.doi.org/10.1109/cec60901.2024.10611801.

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Dihel, Logan, and Nak-Seung Patrick Hyun. "Flexible Convergence Rate for Quadratic Programming-Based Control Lyapunov Functions." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10886305.

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Antoy, Sergio, and Michael Hanus. "Set functions for functional logic programming." In the 11th ACM SIGPLAN conference. ACM Press, 2009. http://dx.doi.org/10.1145/1599410.1599420.

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Odersky, Martin. "Programming with variable functions." In the third ACM SIGPLAN international conference. ACM Press, 1998. http://dx.doi.org/10.1145/289423.289433.

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Anwer, Bilal, Theophilus Benson, Nick Feamster, and Dave Levin. "Programming slick network functions." In SOSR 2015: ACM SIGCOMM Symposium on SDN Research. ACM, 2015. http://dx.doi.org/10.1145/2774993.2774998.

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Wright, Gregory. "Functions to Junctions." In ICFP08: ACM SIGPLAN International Conference on Functional Programming. ACM, 2008. http://dx.doi.org/10.1145/1411204.2181026.

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Stuart, David A. "Scripted signal functions." In ICFP '20: ACM SIGPLAN International Conference on Functional Programming. ACM, 2020. http://dx.doi.org/10.1145/3406088.3409016.

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Eichholz, Matthias, Guido Salvaneschi, and Mira Mezini. "Towards safe modular composition of network functions." In 2018: 2nd International Conference on the Art, Science, and Engineering of Programming 2018. ACM, 2018. http://dx.doi.org/10.1145/3191697.3213804.

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Schmidt, Michael Douglas, and Hod Lipson. "Solving iterated functions using genetic programming." In the 11th annual conference companion. ACM Press, 2009. http://dx.doi.org/10.1145/1570256.1570292.

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Abadi, Martín. "TensorFlow: learning functions at scale." In ICFP'16: ACM SIGPLAN International Conference on Functional Programming. ACM, 2016. http://dx.doi.org/10.1145/2951913.2976746.

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Reports on the topic "Programming functions"

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Royset, J. O. Optimality Functions in Stochastic Programming. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada513135.

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Shapiro, David. Compiling Evaluable Functions in the Godel Programming Language. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.6977.

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McCormick, Garth P., and Christoph Witzgall. On weakly analytic and faithfully convex functions in convex programming. National Institute of Standards and Technology, 2000. http://dx.doi.org/10.6028/nist.ir.6426.

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Vorvick, Janet. Evaluable Functions in the Godel Programming Language: Parsing and Representing Rewrite Rules. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.7071.

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HOLLOMEY, Clara, Piotr MAJDAK, and Robert BAUMGARTNER. The Auditory Modeling Toolbox 1.x. Verlag der Österreichischen Akademie der Wissenschaften, 2025. https://doi.org/10.1553/ica_2022_autitory-toolbox.

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The Auditory Modeling Toolbox (AMT) is an open source Matlab/Octave toolbox dedicated to promoting reproducible research in the hearing sciences. Through its unified interface, it provides access to implementations of auditory models written in various programming languages, to experimental data, and to code focusing on the reproduction of published results. An extensive in-code generated documentation and software demonstrations of the relevant aspects of the models assist in getting quickly familiar with their functioning. Moreover, the AMT 1.x comprises tools to facilitate the extension and
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Anderson, Loren James, and Marion Kei Davis. Functional Programming in Computer Science. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1237221.

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Birch, Izzy, Becky Carter, and Hassan-Alattar Satti. Effective Social Protection in Conflict: Findings from Sudan. Institute of Development Studies, 2024. http://dx.doi.org/10.19088/ids.2024.011.

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This paper explores the conflict sensitivity of social protection in Sudan in its various forms since the present war started in April 2023, from locally led mutual aid to the social assistance programming of international agencies. It considers how these various interventions are both responding to, and being changed by, the conflict and associated humanitarian crisis, as well as how they interrelate. Provision of social assistance leans heavily on humanitarian actors for now, and lessons from their practice may inform and enrich a future state-led social protection system when this is rebuil
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Talcott, Carolyn. Programming and Proving with Function and Control Abstractions,. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada324006.

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Voellmy, Andreas, Ashish Agarwal, and Paul Hudak. Nettle: Functional Reactive Programming for OpenFlow Networks. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada555162.

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Boggs, P. T., J. W. Tolle, and A. J. Kearsley. A merit function for inequality constrained nonlinear programming problems. National Institute of Standards and Technology, 1991. http://dx.doi.org/10.6028/nist.ir.4702.

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