This document discusses the differences between using yield and return in computation expressions in F#. It presents several implementations of computation expressions to demonstrate how yield and return can be distinguished. The key differences are:
- yield continues the remaining computation expression, while return stops any remaining expressions from executing.
- Several approaches are presented: using exceptions, a state field on the builder, and passing state as an argument. The state argument approach provides a clear separation of yield and return without sharing state between uses of the builder.
- Continuations are also proposed as an implementation, where yield calls the continuation and return discards it. This approach makes the symmetry between yield and return very clear.
This document discusses F# and FParsec. It provides examples of parsing expressions in FParsec using lazy evaluation and references, as opposed to NParsec which uses bindings. FParsec allows defining recursive parsers in a natural way in F#.
Introduction to ad-3.4, an automatic differentiation library in Haskellnebuta
Haskellの自動微分ライブラリ Ad-3.4 の紹介(の試み) If you don't see 21 slides in this presentation, try this one (re-uploaded): http://www.slideshare.net/nebuta/130329-ad-by-ekmett
Paradigmas de Linguagens de Programacao - Aula #5Ismar Silveira
The document discusses type systems in programming languages. It defines a type system as a method for proving the absence of certain program behaviors by classifying phrases based on the values they compute. Type systems can help detect errors, improve security, enable abstraction and verification, and aid in evolution and documentation. The document then discusses different characteristics of type systems such as being static or dynamic, strong or weak, manifest or implicit. It provides examples to illustrate these concepts in different programming languages like C, C#, Pascal, Lua, JavaScript, and Fortran.
This document provides instructions for implementing a basic four-function calculator using stacks and queues. It describes converting an infix expression to postfix notation, evaluating the postfix expression, and handling parentheses. Code is provided to get started, and the tasks are to complete functions to convert infix to postfix, evaluate postfix expressions, and update infix to postfix to handle parentheses. Test cases should be run to demonstrate the functionality.
I am Bernard. I am a C Assignment Expert at programminghomeworkhelp.com. I hold a Ph.D. in Programming from, University of Leeds, UK. I have been helping students with their homework for the past 9 years. I solve assignments related to C Programming.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with C Programming Assignments.
An introduction to pointers and references in C++ (with elements of C++11 and C++14). The presentation introduces the readers to the concepts of pointers and references through the pragmatic need of writing a swap function between integers. Generic programming notions (e.g., type constructors) are adopted when useful for the explanation.
Paradigmas de Linguagens de Programacao - Aula #4Ismar Silveira
The document discusses different parameter passing techniques in programming languages, including pass by value, pass by reference, and pass by result/value-result. It provides examples in languages like C, C++, Java, C#, Pascal, Ada to illustrate how each technique works and the differences between them. It also covers topics like parameter modes (in, out, in-out), parameter arrays, and variable arguments.
This document discusses pointers, virtual functions, and polymorphism in C++. It begins by defining pointers and how they can refer to and manipulate objects and memory addresses. It then explains virtual functions, which allow dynamic binding at runtime, and polymorphism. There are two types of polymorphism: compile-time polymorphism which includes function overloading, and runtime polymorphism using virtual functions. Virtual functions allow derived classes to override base class functions. The document also covers pure virtual functions, virtual constructors and destructors, and provides examples of how pointers and virtual functions enable polymorphism.
This document discusses F# and FParsec. It provides examples of parsing expressions in FParsec using lazy evaluation and references, as opposed to NParsec which uses bindings. FParsec allows defining recursive parsers in a natural way in F#.
Introduction to ad-3.4, an automatic differentiation library in Haskellnebuta
Haskellの自動微分ライブラリ Ad-3.4 の紹介(の試み) If you don't see 21 slides in this presentation, try this one (re-uploaded): http://www.slideshare.net/nebuta/130329-ad-by-ekmett
Paradigmas de Linguagens de Programacao - Aula #5Ismar Silveira
The document discusses type systems in programming languages. It defines a type system as a method for proving the absence of certain program behaviors by classifying phrases based on the values they compute. Type systems can help detect errors, improve security, enable abstraction and verification, and aid in evolution and documentation. The document then discusses different characteristics of type systems such as being static or dynamic, strong or weak, manifest or implicit. It provides examples to illustrate these concepts in different programming languages like C, C#, Pascal, Lua, JavaScript, and Fortran.
This document provides instructions for implementing a basic four-function calculator using stacks and queues. It describes converting an infix expression to postfix notation, evaluating the postfix expression, and handling parentheses. Code is provided to get started, and the tasks are to complete functions to convert infix to postfix, evaluate postfix expressions, and update infix to postfix to handle parentheses. Test cases should be run to demonstrate the functionality.
I am Bernard. I am a C Assignment Expert at programminghomeworkhelp.com. I hold a Ph.D. in Programming from, University of Leeds, UK. I have been helping students with their homework for the past 9 years. I solve assignments related to C Programming.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with C Programming Assignments.
An introduction to pointers and references in C++ (with elements of C++11 and C++14). The presentation introduces the readers to the concepts of pointers and references through the pragmatic need of writing a swap function between integers. Generic programming notions (e.g., type constructors) are adopted when useful for the explanation.
Paradigmas de Linguagens de Programacao - Aula #4Ismar Silveira
The document discusses different parameter passing techniques in programming languages, including pass by value, pass by reference, and pass by result/value-result. It provides examples in languages like C, C++, Java, C#, Pascal, Ada to illustrate how each technique works and the differences between them. It also covers topics like parameter modes (in, out, in-out), parameter arrays, and variable arguments.
This document discusses pointers, virtual functions, and polymorphism in C++. It begins by defining pointers and how they can refer to and manipulate objects and memory addresses. It then explains virtual functions, which allow dynamic binding at runtime, and polymorphism. There are two types of polymorphism: compile-time polymorphism which includes function overloading, and runtime polymorphism using virtual functions. Virtual functions allow derived classes to override base class functions. The document also covers pure virtual functions, virtual constructors and destructors, and provides examples of how pointers and virtual functions enable polymorphism.
Pointer variables store memory addresses and can be used to indirectly access other variables. Pointers allow values to be passed by reference into functions rather than by value. Arrays can be accessed using pointers by treating the array name as a pointer to its first element. Dynamic memory allocation with new/delete operators allows pointers to reference variables in heap memory.
Virtual functions allow objects of derived classes to be referenced by pointers or references to the base class. This allows polymorphic behavior where calling code does not need to know the exact derived class, but the correct overridden function for that derived class will be called at runtime. Some key points:
- Virtual functions provide runtime polymorphism in C++. The correct function to call is determined by the actual object type, not the reference/pointer type.
- Pure virtual functions are declared in a base class but provide no definition - derived classes must override these to be instantiable.
- Constructors cannot be virtual but destructors can, and it is important to make base class destructors virtual to ensure proper cleanup
The document provides an overview of the Rust programming language. It describes how Rust grew out of a personal project at Mozilla in 2009. Rust aims to be a safe, concurrent, and practical language supporting multiple paradigms. It uses concepts like ownership and borrowing to prevent data races at compile time. Rust also features traits, generics, pattern matching, and lifetimes to manage memory in a flexible yet deterministic manner.
Pointers are among C’s most powerful, yet most difficult concepts to master. Some tasks like dynamic memory allocation done only by using pointers. So it is essential to learn pointers.
Pointers are a type of variable, just like int, double, etc., except instead of storing a value, they store a memory address of another variable.
This document provides an overview of C++ development environments, basic C++ syntax like classes and pointers, and key concepts like memory management and object oriented programming. It discusses compiling C++ code with g++, using makefiles, preprocessor directives, classes, procedural programming, pointers, memory allocation, problems like dangling pointers and memory leaks, and canonical class forms.
The document discusses pointers in C/C++. Some key points:
1) A pointer is a variable that stores the address of another variable. Pointers allow accessing and modifying the data being pointed to.
2) The & operator returns the address of a variable. Dereferencing a pointer using * accesses the data being pointed to.
3) Pointer arithmetic allows treating pointers like arrays - incrementing/decrementing a pointer adjusts its address by the size of the pointed-to type.
This document discusses pointers and memory in C++. It begins with an introduction to memory and pointers, explaining that pointers are memory addresses. It then covers arrays, noting that arrays are stored continuously in memory and an array name represents the starting memory address. The document also discusses pointer operations like dereferencing with * and incrementing with ++. Finally, it discusses scope, which is the region of code where a variable is accessible or visible.
Complete Information till 2D arrays. In this slides you can also find information about loops and control decision....
Best slides for beginners who wants to learn about C programming language..
Memory management is one of the most fundamental and important aspect for any computer programming language. In the dynamic memory allocation, the memory is allocated to a variable or program at the run time.
I am Blake H. I am a Software Construction Assignment Expert at programminghomeworkhelp.com. I hold a PhD. in Programming, Curtin University, Australia. I have been helping students with their homework for the past 10 years. I solve assignments related to Software Construction.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Software Construction Assignments.
The document discusses input and output statements in C++. It explains that the iostream library includes cout and cin for standard output and input. cout uses the insertion operator << to output data to the screen, while cin uses the extraction operator >> to input data from the keyboard. The document provides examples of using cout and cin to output text, numbers, and calculate values from user input.
This document discusses loops in R and when to use them versus vectorization. It provides examples of for, while, and repeat loops in R. The key points are:
- Loops allow repeating operations but can be inefficient; vectorization is preferred when possible.
- For loops execute a fixed number of times based on an index or counter. Nested for loops allow manipulating multi-dimensional arrays.
- While and repeat loops execute until a condition is met, but repeat ensures at least one iteration.
- Break and next statements allow interrupting loop iterations early.
Pointers are used to access array elements, pass arguments to functions by reference so the function can modify the original argument, pass arrays and strings to functions, obtain memory from the system, and create data structures like linked lists. Pointers store the address of another variable in memory. This allows the pointer variable to indirectly access the contents of the other variable through dereferencing the pointer. Functions can accept arguments passed by reference using pointers, allowing the function to modify the original argument.
A pointer is a variable that stores the memory address of another variable. A double pointer stores the address of a pointer variable. In the example code, a double pointer p2 stores the address of a single pointer p1, which stores the address of an integer variable v. The code then prints the value of v using the single and double pointers to demonstrate this. Pointers allow arithmetic operations like incrementing and decrementing to move the pointer to the next memory location without changing the actual variable value. A function pointer is a pointer that points to executable code in memory, allowing a function to be indirectly called through the pointer variable.
The document provides information on control structures in C++ including relational operators, loops, and decisions. It discusses relational operators like ==, <, > that compare values and return true or false. It describes the three types of loops in C++ - for, while, and do-while loops. The for loop executes a fixed number of times based on initialization, test, and increment expressions. The while loop repeats while a test condition is true. The do-while loop executes the body at least once and then repeats while the test condition is true. The document also covers the if statement for simple conditions and if-else for alternative paths, and provides code examples to demonstrate each control structure.
Pointer variables store memory addresses. They must be declared with a data type and the asterisk (*) symbol. Pointer variables can point to variables of basic data types like int, float, and char. Arithmetic operations on pointers change the memory address being pointed to. Pointers are useful for handling arrays, returning multiple values from functions, and dynamic memory allocation.
The document discusses pointers in C++, including how to access addresses and contents using pointers, how to access array elements using indexes and pointers, and how pointers can be used to pass arguments to functions by reference or by pointer. It also provides examples of pointer usage and briefly describes bubble sort as a sorting algorithm.
Pointers in C allow programs to store and manipulate memory addresses. The document explains that pointers store the address of another variable in memory and use dereferencing operators like * to access the value at that address. It demonstrates how to declare and assign pointers, pass pointers to functions, and use pointer arithmetic to traverse arrays. Key concepts covered include address-of & and dereference * operators, double pointers, and how modifying a pointer or value it points to changes the referenced memory location.
The document discusses pointers in C programming. It defines pointers as variables that store memory addresses and can be used to indirectly access the value of another variable. It explains pointer declaration syntax and how to assign values and memory addresses to pointers. It provides examples of pointer arithmetic and how pointers can be used to modify variable values.
This document discusses continuous integration (CI) and using Jenkins for CI. It mentions using Vim, Git, LaTeX, and generating PDFs. It discusses setting up a private system build in CI that uses Ruby and sbt (Scala build tool). Jenkins is used to run builds from version control and ensure the system is properly integrated and built.
Pointer variables store memory addresses and can be used to indirectly access other variables. Pointers allow values to be passed by reference into functions rather than by value. Arrays can be accessed using pointers by treating the array name as a pointer to its first element. Dynamic memory allocation with new/delete operators allows pointers to reference variables in heap memory.
Virtual functions allow objects of derived classes to be referenced by pointers or references to the base class. This allows polymorphic behavior where calling code does not need to know the exact derived class, but the correct overridden function for that derived class will be called at runtime. Some key points:
- Virtual functions provide runtime polymorphism in C++. The correct function to call is determined by the actual object type, not the reference/pointer type.
- Pure virtual functions are declared in a base class but provide no definition - derived classes must override these to be instantiable.
- Constructors cannot be virtual but destructors can, and it is important to make base class destructors virtual to ensure proper cleanup
The document provides an overview of the Rust programming language. It describes how Rust grew out of a personal project at Mozilla in 2009. Rust aims to be a safe, concurrent, and practical language supporting multiple paradigms. It uses concepts like ownership and borrowing to prevent data races at compile time. Rust also features traits, generics, pattern matching, and lifetimes to manage memory in a flexible yet deterministic manner.
Pointers are among C’s most powerful, yet most difficult concepts to master. Some tasks like dynamic memory allocation done only by using pointers. So it is essential to learn pointers.
Pointers are a type of variable, just like int, double, etc., except instead of storing a value, they store a memory address of another variable.
This document provides an overview of C++ development environments, basic C++ syntax like classes and pointers, and key concepts like memory management and object oriented programming. It discusses compiling C++ code with g++, using makefiles, preprocessor directives, classes, procedural programming, pointers, memory allocation, problems like dangling pointers and memory leaks, and canonical class forms.
The document discusses pointers in C/C++. Some key points:
1) A pointer is a variable that stores the address of another variable. Pointers allow accessing and modifying the data being pointed to.
2) The & operator returns the address of a variable. Dereferencing a pointer using * accesses the data being pointed to.
3) Pointer arithmetic allows treating pointers like arrays - incrementing/decrementing a pointer adjusts its address by the size of the pointed-to type.
This document discusses pointers and memory in C++. It begins with an introduction to memory and pointers, explaining that pointers are memory addresses. It then covers arrays, noting that arrays are stored continuously in memory and an array name represents the starting memory address. The document also discusses pointer operations like dereferencing with * and incrementing with ++. Finally, it discusses scope, which is the region of code where a variable is accessible or visible.
Complete Information till 2D arrays. In this slides you can also find information about loops and control decision....
Best slides for beginners who wants to learn about C programming language..
Memory management is one of the most fundamental and important aspect for any computer programming language. In the dynamic memory allocation, the memory is allocated to a variable or program at the run time.
I am Blake H. I am a Software Construction Assignment Expert at programminghomeworkhelp.com. I hold a PhD. in Programming, Curtin University, Australia. I have been helping students with their homework for the past 10 years. I solve assignments related to Software Construction.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Software Construction Assignments.
The document discusses input and output statements in C++. It explains that the iostream library includes cout and cin for standard output and input. cout uses the insertion operator << to output data to the screen, while cin uses the extraction operator >> to input data from the keyboard. The document provides examples of using cout and cin to output text, numbers, and calculate values from user input.
This document discusses loops in R and when to use them versus vectorization. It provides examples of for, while, and repeat loops in R. The key points are:
- Loops allow repeating operations but can be inefficient; vectorization is preferred when possible.
- For loops execute a fixed number of times based on an index or counter. Nested for loops allow manipulating multi-dimensional arrays.
- While and repeat loops execute until a condition is met, but repeat ensures at least one iteration.
- Break and next statements allow interrupting loop iterations early.
Pointers are used to access array elements, pass arguments to functions by reference so the function can modify the original argument, pass arrays and strings to functions, obtain memory from the system, and create data structures like linked lists. Pointers store the address of another variable in memory. This allows the pointer variable to indirectly access the contents of the other variable through dereferencing the pointer. Functions can accept arguments passed by reference using pointers, allowing the function to modify the original argument.
A pointer is a variable that stores the memory address of another variable. A double pointer stores the address of a pointer variable. In the example code, a double pointer p2 stores the address of a single pointer p1, which stores the address of an integer variable v. The code then prints the value of v using the single and double pointers to demonstrate this. Pointers allow arithmetic operations like incrementing and decrementing to move the pointer to the next memory location without changing the actual variable value. A function pointer is a pointer that points to executable code in memory, allowing a function to be indirectly called through the pointer variable.
The document provides information on control structures in C++ including relational operators, loops, and decisions. It discusses relational operators like ==, <, > that compare values and return true or false. It describes the three types of loops in C++ - for, while, and do-while loops. The for loop executes a fixed number of times based on initialization, test, and increment expressions. The while loop repeats while a test condition is true. The do-while loop executes the body at least once and then repeats while the test condition is true. The document also covers the if statement for simple conditions and if-else for alternative paths, and provides code examples to demonstrate each control structure.
Pointer variables store memory addresses. They must be declared with a data type and the asterisk (*) symbol. Pointer variables can point to variables of basic data types like int, float, and char. Arithmetic operations on pointers change the memory address being pointed to. Pointers are useful for handling arrays, returning multiple values from functions, and dynamic memory allocation.
The document discusses pointers in C++, including how to access addresses and contents using pointers, how to access array elements using indexes and pointers, and how pointers can be used to pass arguments to functions by reference or by pointer. It also provides examples of pointer usage and briefly describes bubble sort as a sorting algorithm.
Pointers in C allow programs to store and manipulate memory addresses. The document explains that pointers store the address of another variable in memory and use dereferencing operators like * to access the value at that address. It demonstrates how to declare and assign pointers, pass pointers to functions, and use pointer arithmetic to traverse arrays. Key concepts covered include address-of & and dereference * operators, double pointers, and how modifying a pointer or value it points to changes the referenced memory location.
The document discusses pointers in C programming. It defines pointers as variables that store memory addresses and can be used to indirectly access the value of another variable. It explains pointer declaration syntax and how to assign values and memory addresses to pointers. It provides examples of pointer arithmetic and how pointers can be used to modify variable values.
This document discusses continuous integration (CI) and using Jenkins for CI. It mentions using Vim, Git, LaTeX, and generating PDFs. It discusses setting up a private system build in CI that uses Ruby and sbt (Scala build tool). Jenkins is used to run builds from version control and ensure the system is properly integrated and built.
This document appears to be a collection of tweets and comments discussing various programming languages and tools including Scala, F#, SQL, Git, C#, Ruby, OCaml, Haskell, CommonJS, Amazon EC2, Coq, ZendEngine, AsakusaSatellite, and XYZ. Many Twitter handles are mentioned in the replies discussing topics like garbage collection, meta-object Lisps, and functional programming languages.
This document discusses monads and continuations in functional programming. It provides examples of using monads like Option and List to handle failure in sequences of operations. It also discusses delimited continuations as a low-level control flow primitive that can implement exceptions, concurrency, and suspensions. The document proposes using monads to pass implicit state through programs by wrapping computations in a state transformer (ST) monad.
This document provides an overview of essential data wrangling tasks in R, including importing, exploring, indexing/subsetting, reshaping, merging, aggregating, and repeating/looping data. It discusses functions for reading different file types like CSV, Excel, and plain text. It also covers exploring data structure and summary statistics, subsetting vectors, data frames and matrices, reshaping between wide and long format, performing different types of joins to merge data, and using loops and sequences to repeat operations.
The document is a report on the topic of computer programming and utilization prepared by group C. It discusses functions, including the definition of a function, function examples, benefits of functions, function prototypes, function arguments, and recursion. It provides examples of math library functions, global and local variables, and external variables. It also includes examples of recursive functions to calculate factorials and the Fibonacci series recursively.
This document provides an introduction to MATLAB through examples of basic operations and functions. It demonstrates how to perform numeric calculations with scalars and vectors, plot graphs, work with matrices, and solve linear systems of equations. The key concepts covered include loading and saving variables, arithmetic operations, matrix operations, plotting functions, and the MATLAB command history.
Integral Calculus Anti Derivatives reviewerJoshuaAgcopra
This document provides an overview of integration concepts and formulas covered in Calculus 2 (Math 112) at the University of Science and Technology of Southern Philippines. It includes the following:
- Course outcomes focus on carrying out integration using fundamental formulas and techniques for single and multiple integrals.
- Topic outline covers anti-differentiation, simple power formulas, and simple trigonometric functions.
- Worked examples demonstrate evaluating indefinite integrals using power, trigonometric, and other basic integration rules.
- Important notes emphasize that the general solution for an indefinite integral includes an unknown constant C and the differential dx.
This document provides an overview of the F# programming language. It discusses key features of F# including functional programming paradigms like higher-order functions, pure functions and immutability. It also covers multi-paradigm support, performance similar to C#, and tools for F# in Visual Studio. Examples are provided for common constructs like functions, recursion, pattern matching, and computation expressions.
MATLAB is a programming tool that simplifies programming compared to languages like C and C#. The document introduces basic MATLAB functions like help, inputting matrices and vectors, matrix operations, loops, conditional statements, and graphs. It also covers symbolic math, Laplace transforms, Fourier transforms, and other domains and transforms. The overall document serves as an introduction to essential MATLAB programming concepts and capabilities.
This document provides a 3-sentence summary of the given document:
The document is a tutorial introduction to high-performance Haskell that covers topics like lazy evaluation, reasoning about space usage, benchmarking, profiling, and making Haskell code run faster. It explains concepts like laziness, thunks, and strictness and shows how to define tail-recursive functions, use foldl' for a strict left fold, and force evaluation of data constructor arguments to avoid space leaks. The goal is to help programmers optimize Haskell code and make efficient use of multiple processor cores.
Introduction to Functional Programming with Scalapramode_ce
The document provides an introduction to functional programming with Scala. It outlines the following topics that will be covered: learning Scala syntax and writing simple programs; important functional programming concepts like closures, higher-order functions, purity, lazy evaluation, currying, tail calls, immutability, and type inference; and understanding the functional programming paradigm through Scala. It also provides some background information on Scala and examples of Scala code demonstrating various concepts.
Laziness, trampolines, monoids and other functional amenities: this is not yo...Mario Fusco
The document discusses functional programming concepts like higher-order functions, function composition, currying, and lazy evaluation. It provides examples of implementing strategies like converting between units using functions and creating streams of prime numbers lazily to avoid stack overflows. Tail call optimization is mentioned as a way to avoid stack overflows with recursive functions.
The Functional Programming Triad of Folding, Scanning and Iteration - a first...Philip Schwarz
The document discusses implementing various functional programming concepts like folding, scanning, and iteration to solve problems involving converting between digit sequences and integers. It provides examples in Scala and Haskell of using fold left to implement a digits-to-integer function and the iterate function to implement an integer-to-digits function. It also discusses using techniques like pipes in Scala and the $ operator in Haskell to improve readability by ordering function applications in the sequence they will be executed.
MATLAB DOCUMENTATION ON SOME OF THE MODULES
A.Generate videos in which a skeleton of a person doing the following Gestures.
1.Tilting his head to right and left
2.Tilting his hand to right and left
3.Walking
in matlab.
B. Write a MATLAB program that converts a decimal number to Roman number and vice versa.
C.Using EZ plot & anonymous functions plot the following:
· Y=Sqrt(X)
· Y= X^2
· Y=e^(-XY)
D.Take your picture and
· Show R, G, B channels along with RGB Image in same figure using sub figure.
· Convert into HSV( Hue, saturation and value) and show the H,S,V channels along with HSV image
E.Record your name pronounced by yourself. Try to display the signal(name) in a plot vs Time, using matlab.
F.Write a script to open a new figure and plot five circles, all centered at the origin and with increasing radii. Set the line width for each circle to something thick (at least 2 points), and use the colors from a 5-color jet colormap (jet).
G. NEWTON RAPHSON AND SECANT METHOD
H.Write any one of the program to do following things using file concept.
1.Create or Open a file
2. Read data from the file and write data to another file
3. Append some text to already existed file
4. Close the file
I.Write a function to perform following set operations
1.Union of A and B
2. Intersection of A and B
3. Complement of A and B
(Assume A= {1, 2, 3, 4, 5, 6}, B= {2, 4, 6})
This document provides an introduction to monads through a presentation given by Mikhail Girkin. Some key points:
1. Monads are commonly used in functional programming to represent computations or chaining of operations. They consist of a type, a unit operation, and a bind (flatMap) operation.
2. Many languages like C# and Java already use monads through things like flatMap, they just don't refer to them as monads. Collections like Seq are monads.
3. Option and Try are examples of monads used to handle potential failures gracefully. For-comprehensions provide a cleaner way to write code involving monads compared to nested flatMaps.
4. Other
(1) The document provides instructions for installing the CounterClockwise plugin for Eclipse to get an IDE for Clojure development. (2) It describes how to create and load Clojure files and launch a REPL for evaluation. (3) The document includes exercises on Clojure basics like functions, macros, and functional programming techniques as well as examples for implementing macros.
The document provides an introduction to integral calculus. It discusses how integral calculus is motivated by the problem of defining and calculating the area under a function's graph. The key points are:
1) Integration is the inverse process of differentiation, where we find the original function given its derivative. This results in families of functions that differ by an arbitrary constant.
2) Indefinite integrals represent families of functions, while definite integrals have practical uses in science, engineering, economics and other fields.
3) Standard formulae for integrals are provided that correspond to common derivative formulae, which can be used to evaluate more complex integrals.
Integral Calculus. - Differential Calculus - Integration as an Inverse Process of Differentiation - Methods of Integration - Integration using trigonometric identities - Integrals of Some Particular Functions - rational function - partial fraction - Integration by partial fractions - standard integrals - First and second fundamental theorem of integral calculus
Scala is a multi-paradigm programming language that supports functional, object-oriented and imperative programming paradigms. The document discusses Scala's support for types, expressions, objects, functions, and provides examples of using Scala for expressions, functions, control structures, patterns, spaces and actors.
The document describes the syllabus for a course on design analysis and algorithms. It covers topics like asymptotic notations, time and space complexities, sorting algorithms, greedy methods, dynamic programming, backtracking, and NP-complete problems. It also provides examples of algorithms like computing greatest common divisor, Sieve of Eratosthenes for primes, and discusses pseudocode conventions. Recursive algorithms and examples like Towers of Hanoi and permutation generation are explained. Finally, it outlines the steps for designing algorithms like understanding the problem, choosing appropriate data structures and computational devices.
The Functional Programming Triad of Folding, Scanning and Iteration - a first...Philip Schwarz
This slide deck can work both as an aide mémoire (memory jogger), or as a first (not completely trivial) example of using left folds, left scans and iteration, to implement mathematical induction.
Errata: on almost half of the slides there is some minor typo or imperfection or in some cases a minor error and in one case, an omission. See a later version for corrections and some improvements.
(for best quality images, either download or view here: https://philipschwarz.dev/fpilluminated/?page_id=455)
Scala code for latest version: https://github.com/philipschwarz/fp-fold-scan-iterate-triad-a-first-example-scala
Flying Futures at the same sky can make the sun rise at midnightWiem Zine Elabidine
Template made by Slidesgo
Implementing responsive and high-performance applications is the most obvious challenge that we face in our programming life. It’s interesting to deeply study concurrency and parallelism on the JVM. In this talk you will learn how to describe parallel tasks and the idea behind Futures and the execution context. I will cover the tricky part of concurrency when the concurrent tasks share and use the same resources and how flying Futures in the same sky can make the sun rise at midnight! At the end I will talk about some possible solutions that you can use to reduce your worries about the pitfalls of concurrency.
Similar to yield and return (poor English ver) (20)
This document provides a summary of an individual's background and experiences including programming languages, conferences, and meetups. It includes the following information in 3 sentences:
The document identifies an individual named bleis-tift and lists their experiences with programming languages like F#, C#, Git, and Vim as well as their involvement with Meetup groups focused on test-driven development, source code management, and more. Various conferences and meetups are listed that they have attended related to programming topics such as .NET, Ruby, F#, JavaScript, functional programming, and more. Locations mentioned include Nagoya, Japan where several meetups on topics such as Perl, OCaml, Scala, and development practices were held.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
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3. Agenda
Part1: Computation Expression
Part2:Dierence of yield and return
∼considerations∼
Part3:Dierence of yield and return
∼implementations∼
Part4:Conclusion
I will talk about how to implement computation
expression.
5. Computation expression is...
expression that extends normal F# grammer and
provides some customize points
able to dene an user dene process
.
the grammer of F#
..
.
let someFunc a b =
let x = f a
let y = g b
x + y
.
computation expression
..
.
let someFunc a b = builder {
let! x = f a
let! y = g b
return x + y
}
6. Usages
Remove nests of match expressions for option
Hide parameters for state
Remove nests of function call for async proc
and so on...
But I will skip these topics today.
7. The way of implementation
The computation exprs are implemented by
some translation rules in F#
Needless any interfaces
Most important thing is which translated exprs are
compilable
.
.
grammer of computation expr
translate
normal grammer
Let's look at some translation rules together!
8. Notation
Sans-Serif Code of F#. ex) fun x - x
Serif meta Variables. ex) cexpr
Itaric The part related to the translation. ex)
T(e, C)
9. Translation rule (most outside)
.
. builder-expr { cexpr }
F#compiler translates following:
.
. let b = builder-expr in {| cexpr |}
b is a fresh variable.
10. builder-expr
Just a normal expression
Builder is evaluated only once
Dene methods called at runtime into builder
type
All methods are dened as instance method
11. {| ... |}
Translate expr to core language grammer
ex) {| cexpr |} ... translate cexpr
See below for further detais
12. cexpr
The most outer target of translation
Other computation expr is represented by ce
cexpr is translated by Delay-trans, Quote-trans,
Run-trans if necessary
13. Representation of the translation rules
The translation rules are described by T-notation
.
T-notation
..
.T(e, C)
e:The computation expr that will be translated
C:The context that was translated
Find the translation rule that match e, and translate
it
14. T-notation of {| cexpr |}
.
T-notation
..
. {| cexpr |} ≡ T(cexpr, λv.v)
λv.v is anonymous function
before dot: the parameter
after dot: the function body
v is the translated expression
Function application is done at compile-time
(not run-time)
15. Trans rule for return
.
Trans rule
..
. T(return e, C) = C(b.Return(e))
if cexpr is return 42 then:
.
Example
..
.
T(return 42, λv.v)
−→(λv.v)(b.Return(42))
−→b.Return(42)
Complete!
16. Trans rule for let
.
Trans rules
..
.
T(return e, C) = C(b.Return(e))
T(let p = e in ce, C) = T(ce, λv.C(let p = e in v))
.
Example
..
.
T(let x = 42 in return x, λv1.v1)
−→T(return x, λv2.(λv1.v1)(let x = 42 in v2))
−→(λv2.(λv1.v1)(let x = 42 in v2))(b.Return(x))
−→(λv1.v1)(let x = 42 in b.Return(x))
−→let x = 42 in b.Return(x)
17. Trans rule of if
.
Trans rules
..
.
{| cexpr |} ≡ T(cexpr, λv.v)
T(return e, C) = C(b.Return(e))
T(if e then ce1 else ce2, C) = C(if e then {| ce1 |} else {| ce2 |})
T(if e then ce, C) = C(if e then {| ce |} else b.Zero())
.
Example
..
.
T(if c then return 42, λv1.v1)
−→(λv1.v1)(if c then {| return 42 |} else b.Zero())
−→(λv1.v1)(if c then T(return 42, λv2.v2) else b.Zero())
−→(λv1.v1)(if c then (λv2.v2)(b.Return(42)) else b.Zero())
−→(λv1.v1)(if c then b.Return(42) else b.Zero())
−→if c then b.Return(42) else b.Zero()
19. Trans rule of while.
Trans rules
..
.
{| cexpr |} ≡ T(cexpr, λv.v)
T(return e, C) = C(b.Return(e))
T(if e then ce, C) = C(if e then {| ce |} else b.Zero())
T(ce1; ce2, C) = C(b.Combine({| ce1 |},b.Delay(fun () - {| ce2 |})))
T(while e do ce, C) = T(ce, λv.C(b.While(fun () - e,b.Delay(fun () - v))))
.
Example
..
.
T (while f() do if g() then return 42 done; return 0, λv1.v1)
−→(λv1.v1)(b.Combine({| while f() do if g() then return 42 |},b.Delay(fun () - {| return 0 |})))
−→(λv1.v1)(b.Combine(
T (if g() then return 42, λv2.b.While(fun () - f(),b.Delay(fun () - v2)))
,b.Delay(fun () - b.Return(0))))
−→(λv1.v1)(b.Combine(
(λv2.b.While(fun () - f(),b.Delay(fun () - v2)))(if g() then b.Return(42) else b.Zero())
,b.Delay(fun () - b.Return(0))))
−→(λv1.v1)(b.Combine(
b.While(fun () - f(),b.Delay(fun () - if g() then b.Return(42) else b.Zero()))
,b.Delay(fun () - b.Return(0))))
−→b.Combine(b.While(fun () - f(),b.Delay(fun () - if g() then b.Return(42) else b.Zero()))
,b.Delay(fun () - b.Return(0)))
20. Feature of computation expr
Computation expr is similar to
do notation (Haskell)
for expression (Scala)
query expression (C#)
Dierence is computation expr has more exibility
than core language.
Computation expr is more powerful and friendly!
22. Trans rules of yield and return
.
Trans rules
..
.
T(yield e, C) = C(b.Yield(e))
T(return e, C) = C(b.Return(e))
Dierent point is only method...
Today's main theme:
Why exist the same rules?
23. Use properly...?
use yield for yield-like and use return for
return-like...?
use yield for collection-like, otherwise uses
return...?
What's the xxx-like!
I want to decide clearly.
24. Thinking about dierence between yield
and return
Reer the dictionary:
yield produce/provide
return give back
return should not be continue the following
process.
Monad's return? I don't know:)
25. Dierence between yield and return
.
yield
..
.
list {
yield 1
printfn done
}
.return
..
.
list {
return 1
printfn done
}
Whether or not to print done
26. The case of C
return
IET
yield return
yield break
query expression
select
I want to realize something like yield return and
yield break.
27. seq expression
return is not supported
Dicult for yield break like C#
Let's reimplements seq expression by computation
expression!
30. Plan 1
The focus on return breaks remained process
Need to return value when called return
Throw exception that wraps returning value in
Return method and catch the exception in Run
method
31. Impl by exception
.
Builder
..
.
type ReturnExn'T(xs: 'T seq) =
inherit System.Exception()
member this.Value = xs
type SeqBuilder'T() =
member this.Yield(x: 'T) = Seq.singleton x
member this.Return(x: 'T) =
raise (ReturnExn(Seq.singleton x))
member this.Combine(xs: 'T seq, cont: unit - 'T seq) =
Seq.append xs (cont ())
member this.Delay(f: unit - 'T seq) = f
member this.Run(f: unit - 'T seq) =
try f () with
| :? ReturnExn'T as e - e.Value
let seq2'T = SeqBuilder'T() // type function
32. Impl by exception
.
Usage
..
.
seq2 { yield 1; yield 2 };;
val it : seqint = seq [1; 2]
seq2 { return 1; return 2 };;
val it : seqint = seq [1]
Yes!
33. Impl by exception
Scala uses exception for the part of implements
return and break
Looks like easy
But!
34. Problem
.
Bad Example
..
.
seq2 { yield 1; return 2; return 3 };;
val it : seqint = seq [2]
In C#:
.
C#
..
.
IEnumerableint F() {
yield return 1;
yield break 2;
yield break 3; }
It returns the sequencce contains 1 and 2.
35. Rene version
.
Catch ReturnExn in Combine
..
.
type SeqBuilder'T() =
member this.Yield(x: 'T) = Seq.singleton x
member this.Return(x: 'T) =
raise (ReturnExn(Seq.singleton x))
member this.Combine(xs: 'T seq, cont: unit - 'T seq) =
try
Seq.append xs (cont ())
with
| :? ReturnExn'T as e -
raise (ReturnExn(Seq.append xs e.Value))
member this.Delay(f: unit - 'T seq) = f
member this.Run(f: unit - 'T seq) =
try f () with
| :? ReturnExn'T as e - e.Value
let seq2'T = SeqBuilder'T()
36. Impl by exception
If provide try-with, need to catch ReturnExn
in try-with and reraise it
Eventually, can't implement clearly
Disinclined for use to exception for control ow
Could be realized at least
37. Plan 2
Continue or not continue
Insert the judgement of whether to call the rest
process
38. impl by state eld
.
Builder
..
.
type SeqBuilder() =
let mutable isExit = false
member this.Yield(x) = Seq.singleton x
member this.Return(x) =
isExit - true
Seq.singleton x
member this.Combine(xs, cont) =
if isExit then xs else Seq.append xs (cont ())
member this.Delay(f) = f
member this.Run(f) =
let res = f ()
isExit - false
res
let seq2 = SeqBuilder()
39. impl by state eld
.
Usage
..
.
seq2 { yield 1; yield 2 };;
val it : seqint = seq [1; 2]
seq2 { return 1; return 2 };;
val it : seqint = seq [1]
seq2 { yield 1; return 2; return 3 };;
val it : seqint = seq [1; 2]
Yes!
41. Problem
builder instance has state
use the same builder instance at the same time...
.
.
Thread A
seq2 {
yield 1
; // Combine
yield 2 // oops!
} // Run
val it : seqint = seq [1]
seq2.isExit
false
true
false
Thread B
seq2 {
return 10
} // Run
42. Rene version
.
Builder
..
.
type SeqBuilder() =
(* ... *)
let seq2 () = SeqBuilder()
.
Usage
..
.
seq2 () { yield 1; yield 2 };;
val it : seqint = seq [1; 2]
seq2 () { return 1; return 2 };;
val it : seqint = seq [1]
seq2 () { yield 1; return 2; return 3 };;
val it : seqint = seq [1; 2]
43. Impl by state eld
Create the builder instance at every time
Can't forbid that the user share the instance
It's troublesome
Does not stand for practical use...
44. Plan 3
Problem: state sharing
Solution: use the argument
Carry the state by the argument, and unwrap the
state in Run method
The rest process is not called if the state is
Break in Combine method
45. Impl by state arg
.
Builder
..
.
type FlowControl = Break | Continue
type SeqBuilder() =
member this.Yield(x) = Seq.singleton x, Continue
member this.Return(x) = Seq.singleton x, Break
member this.Combine((xs, st), cont) =
match st with
| Break - xs, Break
| Continue -
let ys, st = cont ()
Seq.append xs ys, st
member this.Delay(f) = f
member this.Run(f) = f () | fst
let seq2 = SeqBuilder()
46. Impl by state arg
.
Usage
..
.
seq2 { yield 1; yield 2 };;
val it : seqint = seq [1; 2]
seq2 { return 1; return 2 };;
val it : seqint = seq [1]
seq2 { yield 1; return 2; return 3 };;
val it : seqint = seq [1; 2]
Yes!
47. Impl by state arg
Symmetry of the return and yield became clear
The implementation is very complex
Looks like good.
48. Comparison
.
Impl by exception
..
.
member this.Yield(x: 'T) = Seq.singleton x
member this.Return(x: 'T) =
raise (ReturnExn(Seq.singleton x))
.
Impl by state eld
..
.
member this.Yield(x) = Seq.singleton x
member this.Return(x) =
isExit - true
Seq.singleton x
.
Impl by state arg
..
.
member this.Yield(x) = Seq.singleton x, Continue
member this.Return(x) = Seq.singleton x, Break
49. Plan 4
Impl of exception: use the exception to break
the rest process
It is same to discard continuation
yield: call continuation
return: discard continuation
50. Impl by continuation
.Builder
..
.
type SeqBuilder() =
member this.Yield(x) = fun k - k (Seq.singleton x)
member this.Return(x) = fun _ - Seq.singleton x
member this.Combine(f, cont) =
fun k - f (fun xs - cont () k | Seq.append xs)
member this.Delay(f) = f
member this.Run(f) = f () id
let seq2 = SeqBuilder()
.Usage
..
.
seq2 { yield 1; yield 2 };;
val it : seqint = seq [1; 2]
seq2 { return 1; return 2 };;
val it : seqint = seq [1]
seq2 { yield 1; return 2; return 3 };;
val it : seqint = seq [1; 2]
51. Impl by continuation
Symmetry of return and yield is clear
Shortest but complex (and not dene the Bind
method)
The state arg version too
52. Speed Comparison
Write yield at 100,000 times and execute.
builder time
unsupported return 20.5ms
by exception 20.5ms
by state eld 20.7ms
by state arg 21.2ms
by continuation 22.6ms
seq expr 1.18ms
The dierence is less.
But builer is slower than seq expr in the rst place.
54. Summary
The computation expression is powerful
yield and return have the same translation
rule but the meaning is dierent
The seq expression is not supported return →
reimplementation
Implementations:
by exception
by state eld (deprecated)
by state arg
by continuation
55. Impl status of some libraries
Design about return ex) seq/list/option
Target libraries:
FSharpx
ExtCore
FSharpPlus
Basis.Core
As of July 21, 2014
56. Impl status of some libraries
.
Benchmark code
..
.
let xs = [30; 10; 15; 21; -1; 50]
builder {
let i = ref 0
while !i xs.Length do
if xs.[!i] = -1 then
return false
incr i
return true
}
Can compile it
It returns false-like value
57. Impl status of some libraries
.
Expanded benchmark code
..
.
let b = builder
b.Run(
b.Delay(fun () -
let i = ref 0
b.Combine(
b.While(
(fun () - !i xs.Length),
b.Delay(fun () -
b.Combine(
(if xs.[!i] = -1 then b.Return(false)
else b.Zero()),
b.Delay(fun () - incr i; b.Zero())))),
b.Delay(fun () - b.Return(true)))))
61. ExtCore
The impl of Zero is bad.
.
Implementation of Zero
..
.
member inline __.Zero () : unit option =
Some () // TODO : Should this be None?
comment...
65. Rethink about dierence yield and return
Very few libraries implement computation expr
correctly
There is a problem to be solved before yield and
return
Should we give a semantic dierence really?
Should give if you want to take advantage of
computation expr
Should not give if you provide only Bind and
Return (like FSharpPlus)
66. Rethink about computation expression
Should Yield and Return receive continuation?
Compile-time translation is ecient
Can implement yield and return by now rules
I want to take this exibility
67. Suggestion of a Policy
The considered separately depending on the library
design
Case 1: provide monad/monad plus
Case 2: provide more general computing
Case 3: use computaion expr other than monad
68. Provide monad/monad plus
Provide monad
Required: Bind/Return
Optional: ReturnFrom (for convinience)
Optional: Run
Provide another builder that unwrap the value
Provide monad plus
Required: Bind/Return/Zero/Combine
Zero is mzero, Combine is mplus
Required: Delay (depends on trans rule of
Combine)
member this.Delay(f) = f ()
69. Provide more general computing
Separate the modules by feature
Builder module for providing Bind/Return
Builder module for providing Bind/Return/Comine
Combine is not mplus. Combine + Delay is
mplus.
Inevitably, required Delay/Run
member this.Delay(f) = f
member this.Run(f) = f ()
Optional: Zero
Support if-expr without else-clause
70. Use computaion expr other than monad
I have no comments:)
If provide Combine, think about yield and return
Use CustomOperation if necessary
71. Tasks
Report the bug to FSharpx and ExtCore
Create a library that is divided the module by
feature
Verify builder
Edication