Far from being mutually exclusive ways to write software, OOP and functional programming are two useful mental toolsets for designing software. Graham explores how the two are related to find out more about each.
The document discusses different types of queues including simple queue, circular queue, priority queue, and deque. A simple queue follows FIFO principle but has limitations as items can only be inserted once. A circular queue overcomes this by allowing the rear and front pointers to wrap around. A priority queue inserts or deletes items based on priority. Deque allows insertions and deletions on both ends.
The document discusses different data structures for implementing dictionaries, including arrays, linked lists, hash tables, binary trees, and B-trees. It focuses on hashing as a technique for implementing dictionaries. Hashing maps keys to table slots using a hash function to achieve fast average-case search, insertion, and deletion times of O(1). Collisions are resolved using chaining, where each slot contains a linked list. The load factor affects performance, with lower load factors resulting in faster operations.
Download for flawless quality (slides viewed online look a bit grainy and out of focus).
Equivalence of nested flatMaps and chained flatMaps for Kleisli arrow composition.
Queue is a linear data structure where elements are inserted at the rear end and deleted from the front end, following FIFO (First In First Out) principle. A queue can be implemented using arrays or linked lists. The document discusses implementation of queues using static arrays and dynamic memory allocation. It also covers insertion and deletion algorithms and provides examples of queue operations using both array-based and linked list-based implementations. Circular queues are introduced as an enhancement over standard queues to avoid overflow in static array implementation.
I am Samuel H. I am a Mechanical Engineering Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. Matlab, University of Alberta, Canada. I have been helping students with their homework for the past 12 years. I solve assignments related to Mechanical Engineering.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Mechanical Engineering Assignments.
The document discusses different types of queues including simple queue, circular queue, priority queue, and deque. A simple queue follows FIFO principle but has limitations as items can only be inserted once. A circular queue overcomes this by allowing the rear and front pointers to wrap around. A priority queue inserts or deletes items based on priority. Deque allows insertions and deletions on both ends.
The document discusses different data structures for implementing dictionaries, including arrays, linked lists, hash tables, binary trees, and B-trees. It focuses on hashing as a technique for implementing dictionaries. Hashing maps keys to table slots using a hash function to achieve fast average-case search, insertion, and deletion times of O(1). Collisions are resolved using chaining, where each slot contains a linked list. The load factor affects performance, with lower load factors resulting in faster operations.
Download for flawless quality (slides viewed online look a bit grainy and out of focus).
Equivalence of nested flatMaps and chained flatMaps for Kleisli arrow composition.
Queue is a linear data structure where elements are inserted at the rear end and deleted from the front end, following FIFO (First In First Out) principle. A queue can be implemented using arrays or linked lists. The document discusses implementation of queues using static arrays and dynamic memory allocation. It also covers insertion and deletion algorithms and provides examples of queue operations using both array-based and linked list-based implementations. Circular queues are introduced as an enhancement over standard queues to avoid overflow in static array implementation.
I am Samuel H. I am a Mechanical Engineering Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. Matlab, University of Alberta, Canada. I have been helping students with their homework for the past 12 years. I solve assignments related to Mechanical Engineering.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Mechanical Engineering Assignments.
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and ScalaPhilip Schwarz
(download for perfect quality) - See how recursive functions and structural induction relate to recursive datatypes.
Follow along as the fold abstraction is introduced and explained.
Watch as folding is used to simplify the definition of recursive functions over recursive datatypes
Part 1 - through the work of Richard Bird and Graham Hutton.
Errata:
slide 7, 11 fib(0) is 0,rather than 1
slide 23: was supposed to be followed by 2-3 slides recapitulating definitions of factorial and fibonacci with and without foldr, plus translation to scala
slide 36: concat not invoked in concat example
slides 48 and 49: unwanted 'm' in definition of sum
throughout: a couple of typographical errors
throughout: several aesthetic imperfections (wrong font, wrong font colour)
Computer Graphics in Java and Scala - Part 1Philip Schwarz
Computer Graphics in Java and Scala - Part 1.
Continuous (Logical) and Discrete (Device) Coordinates,
with a simple yet pleasing example involving concentric triangles.
Scala code: https://github.com/philipschwarz/computer-graphics-50-triangles-scala
Errata:
1. Scala classes TrianglesPanel and Triangles need not be classes, they could just be objects.
Here is a 3 sentence summary of the document:
The document discusses category theory and how it relates to monads in programming. It explains what categories, functors, natural transformations and monads are from a category theory perspective. It then shows how common monads like Maybe, Either, Writer, Reader, State and List can be simulated in C++ using tuples to represent their structures and demonstrate their usage through examples.
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - with ...Philip Schwarz
(download for perfect quality) - See how recursive functions and structural induction relate to recursive datatypes.
Follow along as the fold abstraction is introduced and explained.
Watch as folding is used to simplify the definition of recursive functions over recursive datatypes
Part 1 - through the work of Richard Bird and Graham Hutton.
This version corrects the following issues:
slide 7, 11 fib(0) is 0,rather than 1
slide 23: was supposed to be followed by 2-3 slides recapitulating definitions of factorial and fibonacci with and without foldr, plus translation to scala
slide 36: concat not invoked in concat example
slides 48 and 49: unwanted 'm' in definition of sum
throughout: a couple of typographical errors
throughout: several aesthetic imperfections (wrong font, wrong font colour)
This document discusses various plotting tools in Matlab, including:
- The plot and stem functions for plotting data values against their index or specified x-values.
- Tools for labeling axes, titles, legends, and setting axis properties.
- The subplot function for dividing the figure window into multiple plots.
- Functions for turning the grid on/off and holding plots.
- Examples of simple 2D and 3D function plots.
An Introduction to Functional Programming using HaskellMichel Rijnders
The document provides an introduction to functional programming using Haskell. It discusses Haskell's main features such as being purely functional, lazy, strongly typed, and supporting higher-order functions. It also covers Haskell's history, types, functions, pattern matching, and common data structures like lists. Programming techniques like recursion, algebraic data types, and type classes are explained. Examples of list processing functions and higher-order functions are provided.
This document discusses indefinite integrals and anti-derivatives. It explains that the indefinite integral of a function is the set of all anti-derivatives of that function. It provides rules for finding the anti-derivative of a function given its derivative, such as adding 1 to the power and dividing by the new power. Examples are given of using these rules to find the function given its derivative.
This document provides an overview of plotting functions in MATLAB. It discusses how to generate basic and 3D plots, customize plots using options like color, style and labels, and control the plot appearance using functions such as axis, title, legend. Examples are given to illustrate plotting a simple function, holding multiple plots, using subplots, and generating surface plots. The document also covers plotting in 3D using functions like surf, plot3 and manipulating axes properties.
The document discusses accumulation functions and the second fundamental theorem of calculus. It defines an accumulation function A(x) based on a derivative function f(t) and asks the reader to find the derivative of several accumulation functions based on being composite functions. It also provides a table to sketch the graph of an example accumulation function and its derivative.
This document provides a cheat sheet for common Matlab commands and functions. It summarizes basics like saving/loading variables, constructing matrices, defining variables, arithmetic operations, solving equations, plotting, and transposes/dot products. Key commands include save, load, rand, zeros, ones, eye, diag, sin, plot, eig, and dot for constructing matrices, numerical operations, solving equations, plotting, and linear algebra.
This document discusses adaptive filtering, which uses an iterative method to automatically adjust filter coefficients over time to deal with non-stationary signals. It describes the general adaptive filtering block diagram and algorithm. It then discusses specific applications of adaptive filtering, including adaptive frequency estimation/system identification, adaptive noise cancelling, and adaptive line enhancement. It provides an example of using adaptive filtering for system identification and shows the results of the first three iterations.
This document describes algorithms for inserting and deleting elements from a sorted or unsorted array. The insert sorted algorithm inserts an element into the correct position in a sorted array by shifting elements down. The insert unsorted algorithm inserts an element into a specified location by shifting elements downward. The delete algorithm removes an element from a specified location by shifting elements upward and decrementing the count.
This document describes various math, statistical, text, logical, and date functions in Excel. It provides examples of functions such as SUM, PRODUCT, MIN, MAX, AVERAGE, CEILING, FLOOR, ROUND, INT, MOD, POWER, FACT, RAND, RANDBETWEEN, SQRT, UPPER, LOWER, PROPER, LEN, LEFT, RIGHT, TRIM, CONCATENATE, REPT, VALUE, TEXT, CODE, CHAR, AND, OR, NOT, COUNTIF, IFERROR, SUMIF and more. It also discusses date formats which depend on the operating system locale settings.
The document discusses functor composition and the functor laws. It explains that the composition of two functors F and G is itself a functor, where the map operation maps a function f by first applying F's map to lift f into F, and then applying G's map to lift the result into G. This satisfies the functor laws, where the mapping of a composition of functions is the composition of their individual mappings.
This document discusses solving sets of linear equations and analyzing DC circuits. It explains that to solve a set of linear equations in matrix form A*x=y, the matrix A and augmented matrix [A y] must have equal rank. It then discusses calculating the condition number of A, which should be close to 1 for an accurate solution. The document provides an example circuit in matrix form Z*I=V and shows using Matlab commands to calculate the rank of Z and [Z V], the condition number of Z, and solve for the current I.
Computer Graphics in Java and Scala - Part 1bPhilip Schwarz
First see the Scala program from Part 1 translated into Java.
Then see the Scala program modified to produce a more intricate drawing.
Java Code: https://github.com/philipschwarz/computer-graphics-50-triangles-java
Scala Code: https://github.com/philipschwarz/computer-graphics-chessboard-with-a-great-many-squares-scala
The document contains code for two Java applets:
1. The first applet draws a series of overlapping ovals with changing positions and sizes.
2. The second applet draws 25 numbered ovals arranged in a 5x5 grid, using nested for loops to handle the positioning and coloring of the ovals.
The document describes MATLAB functions for numerical integration using various rules:
1) Trapezoidal, Simpsons 1/3, Simpsons 3/8, Booles, Weddles, and Rectangular rules are presented with code examples.
2) Each function takes the initial and final inputs, number of intervals, and function as inputs and returns the numerical integration as the output.
3) The functions break the interval into subintervals and calculate the area using the specific rule's formula to approximate the definite integral.
This document provides examples of Kotlin programming concepts including:
- Null safety checks using safe calls (?.) and Elvis operator (?:) to handle null values.
- Smart casts that allow treating a variable as a more specific type after checking its type in an if statement.
- String templates using $ variable interpolation to embed values in strings.
- Range expressions using .., downTo, and step operators to iterate over a range of values.
- Higher order functions like let, apply, use, with that take functions as parameters and help scope variables or simplify code.
- When expressions as a replacement for switch/case with more powerful pattern matching capabilities.
- Functions for mutable and
Gentle Introduction to Functional ProgrammingSaurabh Singh
This slide is basically aimed at professionals and students to introduce them with functional programming.
I haven't used much functional programming terminologies because I personally feel they could be overwhelming to people getting introduced to FP for the first time. For similar reasons I have deliberately avoided using any functional programming language and kept the discussions programming language agnostic as far as possible.
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and ScalaPhilip Schwarz
(download for perfect quality) - See how recursive functions and structural induction relate to recursive datatypes.
Follow along as the fold abstraction is introduced and explained.
Watch as folding is used to simplify the definition of recursive functions over recursive datatypes
Part 1 - through the work of Richard Bird and Graham Hutton.
Errata:
slide 7, 11 fib(0) is 0,rather than 1
slide 23: was supposed to be followed by 2-3 slides recapitulating definitions of factorial and fibonacci with and without foldr, plus translation to scala
slide 36: concat not invoked in concat example
slides 48 and 49: unwanted 'm' in definition of sum
throughout: a couple of typographical errors
throughout: several aesthetic imperfections (wrong font, wrong font colour)
Computer Graphics in Java and Scala - Part 1Philip Schwarz
Computer Graphics in Java and Scala - Part 1.
Continuous (Logical) and Discrete (Device) Coordinates,
with a simple yet pleasing example involving concentric triangles.
Scala code: https://github.com/philipschwarz/computer-graphics-50-triangles-scala
Errata:
1. Scala classes TrianglesPanel and Triangles need not be classes, they could just be objects.
Here is a 3 sentence summary of the document:
The document discusses category theory and how it relates to monads in programming. It explains what categories, functors, natural transformations and monads are from a category theory perspective. It then shows how common monads like Maybe, Either, Writer, Reader, State and List can be simulated in C++ using tuples to represent their structures and demonstrate their usage through examples.
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - with ...Philip Schwarz
(download for perfect quality) - See how recursive functions and structural induction relate to recursive datatypes.
Follow along as the fold abstraction is introduced and explained.
Watch as folding is used to simplify the definition of recursive functions over recursive datatypes
Part 1 - through the work of Richard Bird and Graham Hutton.
This version corrects the following issues:
slide 7, 11 fib(0) is 0,rather than 1
slide 23: was supposed to be followed by 2-3 slides recapitulating definitions of factorial and fibonacci with and without foldr, plus translation to scala
slide 36: concat not invoked in concat example
slides 48 and 49: unwanted 'm' in definition of sum
throughout: a couple of typographical errors
throughout: several aesthetic imperfections (wrong font, wrong font colour)
This document discusses various plotting tools in Matlab, including:
- The plot and stem functions for plotting data values against their index or specified x-values.
- Tools for labeling axes, titles, legends, and setting axis properties.
- The subplot function for dividing the figure window into multiple plots.
- Functions for turning the grid on/off and holding plots.
- Examples of simple 2D and 3D function plots.
An Introduction to Functional Programming using HaskellMichel Rijnders
The document provides an introduction to functional programming using Haskell. It discusses Haskell's main features such as being purely functional, lazy, strongly typed, and supporting higher-order functions. It also covers Haskell's history, types, functions, pattern matching, and common data structures like lists. Programming techniques like recursion, algebraic data types, and type classes are explained. Examples of list processing functions and higher-order functions are provided.
This document discusses indefinite integrals and anti-derivatives. It explains that the indefinite integral of a function is the set of all anti-derivatives of that function. It provides rules for finding the anti-derivative of a function given its derivative, such as adding 1 to the power and dividing by the new power. Examples are given of using these rules to find the function given its derivative.
This document provides an overview of plotting functions in MATLAB. It discusses how to generate basic and 3D plots, customize plots using options like color, style and labels, and control the plot appearance using functions such as axis, title, legend. Examples are given to illustrate plotting a simple function, holding multiple plots, using subplots, and generating surface plots. The document also covers plotting in 3D using functions like surf, plot3 and manipulating axes properties.
The document discusses accumulation functions and the second fundamental theorem of calculus. It defines an accumulation function A(x) based on a derivative function f(t) and asks the reader to find the derivative of several accumulation functions based on being composite functions. It also provides a table to sketch the graph of an example accumulation function and its derivative.
This document provides a cheat sheet for common Matlab commands and functions. It summarizes basics like saving/loading variables, constructing matrices, defining variables, arithmetic operations, solving equations, plotting, and transposes/dot products. Key commands include save, load, rand, zeros, ones, eye, diag, sin, plot, eig, and dot for constructing matrices, numerical operations, solving equations, plotting, and linear algebra.
This document discusses adaptive filtering, which uses an iterative method to automatically adjust filter coefficients over time to deal with non-stationary signals. It describes the general adaptive filtering block diagram and algorithm. It then discusses specific applications of adaptive filtering, including adaptive frequency estimation/system identification, adaptive noise cancelling, and adaptive line enhancement. It provides an example of using adaptive filtering for system identification and shows the results of the first three iterations.
This document describes algorithms for inserting and deleting elements from a sorted or unsorted array. The insert sorted algorithm inserts an element into the correct position in a sorted array by shifting elements down. The insert unsorted algorithm inserts an element into a specified location by shifting elements downward. The delete algorithm removes an element from a specified location by shifting elements upward and decrementing the count.
This document describes various math, statistical, text, logical, and date functions in Excel. It provides examples of functions such as SUM, PRODUCT, MIN, MAX, AVERAGE, CEILING, FLOOR, ROUND, INT, MOD, POWER, FACT, RAND, RANDBETWEEN, SQRT, UPPER, LOWER, PROPER, LEN, LEFT, RIGHT, TRIM, CONCATENATE, REPT, VALUE, TEXT, CODE, CHAR, AND, OR, NOT, COUNTIF, IFERROR, SUMIF and more. It also discusses date formats which depend on the operating system locale settings.
The document discusses functor composition and the functor laws. It explains that the composition of two functors F and G is itself a functor, where the map operation maps a function f by first applying F's map to lift f into F, and then applying G's map to lift the result into G. This satisfies the functor laws, where the mapping of a composition of functions is the composition of their individual mappings.
This document discusses solving sets of linear equations and analyzing DC circuits. It explains that to solve a set of linear equations in matrix form A*x=y, the matrix A and augmented matrix [A y] must have equal rank. It then discusses calculating the condition number of A, which should be close to 1 for an accurate solution. The document provides an example circuit in matrix form Z*I=V and shows using Matlab commands to calculate the rank of Z and [Z V], the condition number of Z, and solve for the current I.
Computer Graphics in Java and Scala - Part 1bPhilip Schwarz
First see the Scala program from Part 1 translated into Java.
Then see the Scala program modified to produce a more intricate drawing.
Java Code: https://github.com/philipschwarz/computer-graphics-50-triangles-java
Scala Code: https://github.com/philipschwarz/computer-graphics-chessboard-with-a-great-many-squares-scala
The document contains code for two Java applets:
1. The first applet draws a series of overlapping ovals with changing positions and sizes.
2. The second applet draws 25 numbered ovals arranged in a 5x5 grid, using nested for loops to handle the positioning and coloring of the ovals.
The document describes MATLAB functions for numerical integration using various rules:
1) Trapezoidal, Simpsons 1/3, Simpsons 3/8, Booles, Weddles, and Rectangular rules are presented with code examples.
2) Each function takes the initial and final inputs, number of intervals, and function as inputs and returns the numerical integration as the output.
3) The functions break the interval into subintervals and calculate the area using the specific rule's formula to approximate the definite integral.
This document provides examples of Kotlin programming concepts including:
- Null safety checks using safe calls (?.) and Elvis operator (?:) to handle null values.
- Smart casts that allow treating a variable as a more specific type after checking its type in an if statement.
- String templates using $ variable interpolation to embed values in strings.
- Range expressions using .., downTo, and step operators to iterate over a range of values.
- Higher order functions like let, apply, use, with that take functions as parameters and help scope variables or simplify code.
- When expressions as a replacement for switch/case with more powerful pattern matching capabilities.
- Functions for mutable and
Gentle Introduction to Functional ProgrammingSaurabh Singh
This slide is basically aimed at professionals and students to introduce them with functional programming.
I haven't used much functional programming terminologies because I personally feel they could be overwhelming to people getting introduced to FP for the first time. For similar reasons I have deliberately avoided using any functional programming language and kept the discussions programming language agnostic as far as possible.
In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data.
1. The document provides code snippets for implementing various sorting algorithms including heap sort, quicksort, merge sort, radix sort, bucket sort, and insertion sort. It also includes code for graph algorithms like Dijkstra's algorithm, Warshall's algorithm, and the knapsack problem using dynamic programming.
The document provides solutions to various problems involving 1D arrays in C and Python. It includes programs to:
1. Reverse the elements of an array
2. Determine if an array contains all even, odd, or mixed elements
3. Count the number of even and odd elements in an array
4. Check if two arrays are equal
5. Find the sum of perfect square elements in an array
6. Find the minimum scalar product of two vectors
7. Find the smallest and largest elements in an array
8. Print all distinct elements in an array
9. Check if two arrays are disjoint
For each problem, it provides the algorithm, C and Python solutions, sample input/output,
The document discusses the benefits of declarative programming using Scala. It provides examples of implementing algorithms and data structures declaratively in Scala. It also discusses the history and future of Scala, as well as how Scala encourages thinking about programs as transformations rather than changes to memory.
Scala - where objects and functions meetMario Fusco
The document provides an overview of a two-day training course on Scala that covers topics like object orientation, functional programming, pattern matching, generics, traits, case classes, tuples, collections, concurrency, options and monads. The course aims to show how Scala combines object-oriented and functional programming approaches and provides examples of commonly used Scala features like classes, traits, pattern matching, generics and collections.
This document discusses tuples and sets in Python. It defines tuples as immutable sequences that can contain heterogeneous data types. Tuples can be indexed and sliced but not modified. Sets are unordered collections of unique and immutable elements. Common set operations include union, intersection, difference, and symmetric difference.
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.
Introduction to Neural Networks and Deep Learning from ScratchAhmed BESBES
If you're willing to understand how neural networks work behind the scene and debug the back-propagation algorithm step by step by yourself, this presentation should be a good starting point.
We'll cover elements on:
- the popularity of neural networks and their applications
- the artificial neuron and the analogy with the biological one
- the perceptron
- the architecture of multi-layer perceptrons
- loss functions
- activation functions
- the gradient descent algorithm
At the end, there will be an implementation FROM SCRATCH of a fully functioning neural net.
code: https://github.com/ahmedbesbes/Neural-Network-from-scratch
This document provides an overview of functional programming with Haskell. It discusses key concepts of functional programming like immutable data structures and pure functions. It introduces Haskell types including basic types, tuples, lists, data types, and type classes. It covers Haskell functions like pattern matching, guards, and higher order functions. It also discusses Haskell concepts like laziness, currying, and polymorphism. Finally, it provides an introduction to monads in Haskell and discusses Haskell tools, frameworks, and performance.
This document discusses functional programming concepts like map, reduce, and filter and provides Swift code examples for applying these concepts. It begins with an introduction to functional programming and key concepts. It then covers Swift basics like function types and passing functions. The bulk of the document explains and demonstrates map, reduce, filter and their uses on arrays and optionals in Swift. It concludes with suggestions for further functional programming topics and resources.
The document provides information about Python programming language:
- Python was created in the late 1980s and became widely popular in the early 2000s.
- It is a high-level, general-purpose, interpreted programming language that can be used for web, desktop, game development, data science, and more.
- Some key features of Python include dynamic typing, automatic memory management, and being multi-paradigm supporting object-oriented, imperative, functional programming styles.
R is a free and open-source programming language for statistical analysis and graphics. It allows users to import, clean, transform, visualize and model data. Key features of R include its large collection of statistical and graphical techniques, ability to easily extend its functionality through user-contributed packages, and open-source nature which allows for free use and development. The document provides instructions on installing R, getting started with the R interface and commands, and an overview of common functions and operations for data analysis, visualization and statistics.
This document discusses the key principles of functional programming including:
1) Expression-oriented programming with functions treated as first-class citizens that are composed to build new functions.
2) Programming with immutable values rather than mutable state to avoid side effects.
3) Leveraging higher-order functions and behavior-rich containers to preserve data structures and allow parallelization.
4) Focusing on simplicity, composability, and structure-preserving operations to build programs in a declarative rather than imperative style.
A data structure is needed to represent a country with cities connected by bidirectional roads. The data structure will allow finding the longest road between any two cities in the country based on query inputs of two cities. A graph data structure using adjacency lists can model the country, with cities as nodes and roads as edges between nodes labeled with their costs. Queries can then find the longest cost path between two cities using graph traversal algorithms.
Monads and Monoids: from daily java to Big Data analytics in Scala
Finally, after two decades of evolution, Java 8 made a step towards functional programming. What can Java learn from other mature functional languages? How to leverage obscure mathematical abstractions such as Monad or Monoid in practice? Usually people find it scary and difficult to understand. Oleksiy will explain these concepts in simple words to give a feeling of powerful tool applicable in many domains, from daily Java and Scala routines to Big Data analytics with Storm or Hadoop.
Similar to Object-Oriented Programming in Functional Programming in Swift (20)
The document discusses patterns and techniques for writing cross-platform Objective-C code. It describes using a strategy pattern to abstract platform-specific code behind a common interface. Classes like O2LPerson would delegate platform-specific behavior to subclasses like O2LPersonStrategyMac and O2LPersonStrategyiOS. It also provides examples of checking for features at runtime through techniques like responding to selectors, class existence checks, and dlopen.
Taking a Test Drive: iOS Dev UK guide to TDDGraham Lee
The document discusses test-driven development (TDD) and how it can be used to write iOS apps. Some key points:
- TDD aims to validate code behavior, discover defects early, verify fixes, and detect regressions by writing tests before code.
- Unit tests validate individual classes and components, while integration, system, and acceptance tests validate how pieces work together.
- Practicing TDD results in code that is easier to test (small focused classes/methods with few side effects) and design that is more modular.
- Fake objects and mocks can be used to test components that interact with external systems by isolating their behavior.
- Overall, TDD promotes a test
The document discusses taking a test drive of a new product from Fuzzy Aliens Limited. It includes the author's name and company but does not provide any other relevant details.
- The document discusses cryptographic storage for smartphone data, specifically the aescrypt format and software which allows encrypted storage of secret files on phones and across backups.
- Aescrypt uses a randomly generated initialization vector and password hashes to encrypt the bulk of files with AES-256, and includes metadata and integrity checks without revealing secret information.
- The key derived from hashing the password is used to encrypt an actual encryption key, to provide an additional layer of protection in case the derived key is compromised.
Smartphone security and privacy: you're doing it wrongGraham Lee
Before you can get security or privacy features correct, you must understand how people think and how this will impact any UI you show for your privacy settings. In this presentation, I discuss the user's mental model and see how this impacts on iPhone and Android privacy UI.
A look at how the clang static analyser works and how third-party developers can add their own analysis rules, and at the klee symbolic code executor in LLVM.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help alleviate symptoms of mental illness and boost overall mental well-being.
An introduction to the motivation and theory behind test-driven development, suitable for people with experience in Mac or iOS development using Objective-C.
A presentation of some of the security features and APIs in iPhone OS, allowing discussion of the threat model underlying Apple's chosen mitigation technology.
DDS Security Version 1.2 was adopted in 2024. This revision strengthens support for long runnings systems adding new cryptographic algorithms, certificate revocation, and hardness against DoS attacks.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
What is Augmented Reality Image Trackingpavan998932
Augmented Reality (AR) Image Tracking is a technology that enables AR applications to recognize and track images in the real world, overlaying digital content onto them. This enhances the user's interaction with their environment by providing additional information and interactive elements directly tied to physical images.
Odoo ERP software
Odoo ERP software, a leading open-source software for Enterprise Resource Planning (ERP) and business management, has recently launched its latest version, Odoo 17 Community Edition. This update introduces a range of new features and enhancements designed to streamline business operations and support growth.
The Odoo Community serves as a cost-free edition within the Odoo suite of ERP systems. Tailored to accommodate the standard needs of business operations, it provides a robust platform suitable for organisations of different sizes and business sectors. Within the Odoo Community Edition, users can access a variety of essential features and services essential for managing day-to-day tasks efficiently.
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Measures in SQL (SIGMOD 2024, Santiago, Chile)Julian Hyde
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
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GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
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10. Digression: 2 > 1
⇔
Count: ℕ
At: ℕ→T?
<T>
struct List<T> {
let count: () -> Int
let at: (Int) -> T?
}
protocol List {
associatedtype T
func count() -> Int
func at(index: Int) -> T?
}
⇔
11. struct List<T> {
let count: () -> Int
let at: (Int) -> T?
}
protocol List {
associatedtype T
func count() -> Int
func at(index: Int) -> T?
}
⇔
count f(𝑥)
at g(𝑥)
13. enum ListSelectors {
case count
case at
}
enum ListIMPs<T> {
case count (() -> Int)
case at ((Int) -> T?)
}
typealias List<T> = (ListSelectors) -> ListIMPs<T>
14. If 2>1, then ∞>2
typealias Selector = String
typealias Object = (Selector) -> IMP
enum IMP {
case accessor(()->(Object?)
case mutator((Object)->Void)
…
}
func swift_msgSend(this: Object, _cmd: Selector) -> IMP
{
return this(_cmd)
}
15. TL;DR
• Objects are functions
• …that close over their ivars (constructors are HOFs)
• …that map method selectors to method implementations
• …they’re just ways to pick functions at runtime
Sample code with more discussion: https://github.com/iamleeg/OOPInFPInSwift
Editor's Notes
The Smalltalk version of OOP is derived from adding dynamic binding—that is, late choice of function—to LISP. OOP is not much more than higher-order functions, closures and appropriate use of types, let’s take a look.
Let’s go on a journey. We’re going to start with a function definition, then we’re going to combine functions to describe types with multiple operations, then we’re going to introduce dynamic dispatch to choose functions at runtime. What we’ll end up with is an object that, for now, I’ll call an object.
A set is equivalent to the predicate that tests whether an object is a member of the set. This is a specific case of my assertion: you can define something (usefully, if not exactly) using only its externally-observable behaviour; the operations it supports and its behaviour under those operations.
If I have a table where I can look up an object and find out whether it is or is not a duck, philosophers would call this an extensional definition of the set of ducks. If I have a predicate that I can pass an object and get true if it is a duck and false otherwise, they would call this an intensional definition of the set of ducks. Importantly, both of these are definitions of the same set, they are equivalent.
Someone who knows Swift will probably say that this protocol and struct are not interchangeable because of the difference between associated types and generic types. I don’t care: from a “thinking about this type” perspective, they are each product types of a count function and a type-dependent at function.
In either case, the protocol or the structure, we have a table of names that we can use to look up functions. In other words, we can select methods based on their name, by looking up the name in the table.
…and we have seen before, with sets, that where we have a table we can replace it with a function. So in this case we could have some function that takes the name of a method (the selector), and returns the method implementation. What would that look like?
A method implementation (IMP) is the sum type of all the possible method signatures (two, in this case). This is in principle true in Objective-C, which is why it has the NSMethodSignature type to know how to find the parameters and return value of a method. Smalltalk and Ruby have a single calling convention (and a single type) so can ignore the type of an IMP.
This message send function is more general than that in Smalltalk, ObjC, JS, Ruby etc because it gives objects agency: the object itself decides how to choose what method to give you.