This document appears to describe domain modeling and architecture using Scala. It includes code snippets defining traits for resources, ontologies, relational entities, graph vertices and edges. It also shows implementations of a Chromosome entity and methods to enrich domain models, filter for XML models, and retrieve ingoing edges. The code defines a type hierarchy for domain models with relational, graph and XML capabilities.
This document discusses Scala as a domain-specific language (DSL) for building other DSLs. Some key points:
- Scala can be used to create internal DSLs within applications as well as external DSLs for defining domain concepts.
- Examples shown include using Scala for TODO list management, entity-relationship modeling, and processing streaming data.
- Scala's traits, classes, functions and other features allow defining DSLs with a natural, domain-focused syntax and semantics.
The document discusses Groovy concepts including types, operators, objects, structures, closures, control structures, and methods for strings, lists, and maps. It covers topics such as optional syntax, imports, type checking, numbers, strings, GStrings, lists, maps, enums, operators, date/time operations, and closure usage including delegation and implicit parameters. Groovy allows for optional syntax elements, dynamic typing, closures, and methods to operate on common data types like strings, lists, and maps.
The Ring programming language version 1.7 book - Part 40 of 196Mahmoud Samir Fayed
This document summarizes Ring documentation for built-in classes including Tree, Math, DateTime, File, System, Debug, and DataType. It provides examples of using methods from each class, such as setting and printing tree nodes, calculating trigonometric functions with Math, getting date/time with DateTime, reading and writing files with File, and executing system commands with System. Descriptions of each class's methods are included to explain their functions.
The Ring programming language version 1.8 book - Part 50 of 202Mahmoud Samir Fayed
The Page class contains methods for generating HTML elements and adding content to web pages. It includes methods for common elements like headings, paragraphs, links, forms, tables, and more. Each method accepts a parameter that allows setting attributes of the element through a list. This allows generating HTML elements with customized attributes in a simple way.
The Ring programming language version 1.10 book - Part 39 of 212Mahmoud Samir Fayed
The document discusses object-oriented programming in Ring. It explains that classes can be defined to create objects, and objects can access attributes and methods using braces or dot notation. Constructors can be used to initialize objects. Inheritance, packages, sorting and finding objects are also covered.
This document provides a quick reference guide for EJBQL 3.0, including:
1) How to write queries using parameters, perform updates and deletes, use subqueries, ordering, and aggregates.
2) Details on query structure, available where clause methods, and using SQL queries.
3) How to map query results to custom result classes and aliases.
The Ring programming language version 1.5.4 book - Part 44 of 185Mahmoud Samir Fayed
This document contains code for classes that provide functionality for database operations and model-view-controller (MVC) patterns in Ring.
The Database class handles database connections and queries. The ModelBase class extends Database and provides methods for CRUD operations on a database table based on the class name. The ControllerBase class sets up an associated view and model based on its class name and provides routing functionality. Together these classes provide a framework for building MVC-based applications with Ring that interact with a database.
The Ring programming language version 1.4.1 book - Part 13 of 31Mahmoud Samir Fayed
This document provides documentation on Ring's web library API for generating HTML pages and elements. It describes classes and methods for creating pages, adding content and attributes, handling forms, and more. The Page class allows adding various HTML elements to the page content through methods like text(), html(), h1(), etc. The Application class contains methods for encoding, cookies, and page structure. WebLib enables generating complete HTML pages in Ring code.
This document discusses Scala as a domain-specific language (DSL) for building other DSLs. Some key points:
- Scala can be used to create internal DSLs within applications as well as external DSLs for defining domain concepts.
- Examples shown include using Scala for TODO list management, entity-relationship modeling, and processing streaming data.
- Scala's traits, classes, functions and other features allow defining DSLs with a natural, domain-focused syntax and semantics.
The document discusses Groovy concepts including types, operators, objects, structures, closures, control structures, and methods for strings, lists, and maps. It covers topics such as optional syntax, imports, type checking, numbers, strings, GStrings, lists, maps, enums, operators, date/time operations, and closure usage including delegation and implicit parameters. Groovy allows for optional syntax elements, dynamic typing, closures, and methods to operate on common data types like strings, lists, and maps.
The Ring programming language version 1.7 book - Part 40 of 196Mahmoud Samir Fayed
This document summarizes Ring documentation for built-in classes including Tree, Math, DateTime, File, System, Debug, and DataType. It provides examples of using methods from each class, such as setting and printing tree nodes, calculating trigonometric functions with Math, getting date/time with DateTime, reading and writing files with File, and executing system commands with System. Descriptions of each class's methods are included to explain their functions.
The Ring programming language version 1.8 book - Part 50 of 202Mahmoud Samir Fayed
The Page class contains methods for generating HTML elements and adding content to web pages. It includes methods for common elements like headings, paragraphs, links, forms, tables, and more. Each method accepts a parameter that allows setting attributes of the element through a list. This allows generating HTML elements with customized attributes in a simple way.
The Ring programming language version 1.10 book - Part 39 of 212Mahmoud Samir Fayed
The document discusses object-oriented programming in Ring. It explains that classes can be defined to create objects, and objects can access attributes and methods using braces or dot notation. Constructors can be used to initialize objects. Inheritance, packages, sorting and finding objects are also covered.
This document provides a quick reference guide for EJBQL 3.0, including:
1) How to write queries using parameters, perform updates and deletes, use subqueries, ordering, and aggregates.
2) Details on query structure, available where clause methods, and using SQL queries.
3) How to map query results to custom result classes and aliases.
The Ring programming language version 1.5.4 book - Part 44 of 185Mahmoud Samir Fayed
This document contains code for classes that provide functionality for database operations and model-view-controller (MVC) patterns in Ring.
The Database class handles database connections and queries. The ModelBase class extends Database and provides methods for CRUD operations on a database table based on the class name. The ControllerBase class sets up an associated view and model based on its class name and provides routing functionality. Together these classes provide a framework for building MVC-based applications with Ring that interact with a database.
The Ring programming language version 1.4.1 book - Part 13 of 31Mahmoud Samir Fayed
This document provides documentation on Ring's web library API for generating HTML pages and elements. It describes classes and methods for creating pages, adding content and attributes, handling forms, and more. The Page class allows adding various HTML elements to the page content through methods like text(), html(), h1(), etc. The Application class contains methods for encoding, cookies, and page structure. WebLib enables generating complete HTML pages in Ring code.
Apache Spark - Key Value RDD - Transformations | Big Data Hadoop Spark Tutori...CloudxLab
The document provides information about key-value RDD transformations and actions in Spark. It defines transformations like keys(), values(), groupByKey(), combineByKey(), sortByKey(), subtractByKey(), join(), leftOuterJoin(), rightOuterJoin(), and cogroup(). It also defines actions like countByKey() and lookup() that can be performed on pair RDDs. Examples are given showing how to use these transformations and actions to manipulate key-value RDDs.
Slides from my talk at the Junction (Jan 24, 2013)
Single-core performance has hit a ceiling, and building web-scale multi-core applications using imperative programming models is nightmarishly difficult. Parallel programming creates a new set of challenges, best practices and design patterns. Scala is designed to enable building scalable systems, elegantly blending functional and object oriented paradigms into an expressive and concise language, while retaining interoperability with Java. Scala is the fastest growing JVM programming language, being rapidly adopted by leading companies such as Twitter, LinkedIn and FourSquare.
This presentation provides a comprehensive overview of the language, which managed to increase type safety while feeling more dynamic, being more concise and improving readability at the same time. We will see how Scala simplifies real life problems by empowering the developer with powerful functional programming primitives, without giving up on the object oriented paradigm. The overview includes tools for multi-core programming in Scala, the type system, collection framework and domain-specific languages. We’ll explore the power of compile-time meta-programming, which is made possible by the newly released Scala 2.10, and get a glimpse into what to expect from 2.11 in 2014.
We will also see how Scala helps overcome the inherent limitations of Java, such as type erasure, array covariance and boxing overhead.
Multiple examples emphasize how Scala pushes the JVM harder than any other mainstream language through the infinite number of boilerplate busters, increased type safety and productivity boosters from a Java developer’s perspective.
The Ring programming language version 1.9 book - Part 53 of 210Mahmoud Samir Fayed
This document provides code examples and documentation for Ring's web application framework. It includes code for user authentication using a database, classes for database access and web controllers, and descriptions of the main classes and methods in the WebLib API for generating HTML pages and handling requests. The document covers key concepts like generating pages dynamically based on request parameters, working with databases using Model classes, and common tasks like cookies, file uploads, and URL encoding.
Lecture on Rubinius for Compiler Construction at University of TwenteDirkjan Bussink
This document summarizes Rubinius, an implementation of the Ruby programming language that includes a bytecode virtual machine written in C++ and Ruby. Some key points:
- Rubinius compiles Ruby code to bytecode that runs on its built-in virtual machine. This provides performance improvements over interpreting Ruby code.
- The virtual machine is implemented in both C++ and Ruby to provide flexibility. It can inline methods, perform just-in-time compilation, and garbage collect memory.
- Rubinius aims to be a complete Ruby implementation while also improving performance through techniques like inline caching, profiling, and garbage collection optimizations.
Functional Object-Oriented Imperative Scala / 関数型オブジェクト指向命令型 Scala by Sébasti...scalaconfjp
The document discusses Scala's ability to combine functional and object-oriented programming paradigms. It provides an example of an Emitter class that uses mutable internal state carried between method invocations to improve performance, while maintaining an immutable/functional API that encapsulates the mutable state so it is not observable from outside the class. This approach allows algorithms with mutable data structures internally for readability while preserving the benefits of immutable/functional programming in the public interface.
The Ring programming language version 1.7 book - Part 41 of 196Mahmoud Samir Fayed
This document discusses using nested structures and object composition in Ring to enable declarative programming. It shows how to:
1. Create objects inside lists and add objects to lists.
2. Return objects and lists by reference from methods to avoid copies.
3. Execute a "BraceEnd()" method after accessing an object with braces {} to run cleanup code.
4. Build a declarative programming environment on top of Ring's object orientation features using nested structures, returning references, and BraceEnd() methods.
The Ring programming language version 1.3 book - Part 34 of 88Mahmoud Samir Fayed
This document contains code from the datalib.ring library that defines classes for database connectivity and model-view-controller implementation in Ring.
The Database class handles database connections and queries. The ModelBase class extends Database and adds methods for CRUD operations on a model object. It determines the table name from the class name.
The ControllerBase class is the base class for controllers. It dynamically creates the view and model objects based on the controller class name. It also contains routing logic and pagination methods. These classes provide a framework for building MVC applications with Ring and connecting to a database.
The Ring programming language version 1.10 book - Part 40 of 212Mahmoud Samir Fayed
The document provides examples and explanations of object-oriented programming concepts in Ring including:
1. Defining setter and getter methods to control access to class attributes.
2. Using the self keyword to refer to the current object instance from within methods.
3. Overloading operators like + and - to allow their use with custom class objects.
3. Demonstrating inheritance by defining a child class that inherits from a parent class.
The Ring programming language version 1.5.1 book - Part 43 of 180Mahmoud Samir Fayed
This document provides documentation on functions for performing common database operations like insert, update, delete, search in a Ring application. It includes classes like ModelBase and ControllerBase that handle connecting to the database and executing SQL queries. Methods are provided to load a model from the database, get/set values from the model, and perform CRUD operations on a database table. The ControllerBase class provides request routing and common functions for displaying data in views.
The document discusses several native JavaScript objects including String, Math, Array, and Date objects. It focuses on the String object, describing how to create string variables and primitive types. It then explains several string methods like length, charAt(), charCodeAt(), indexOf(), lastIndexOf(), substr(), toLowerCase(), and toUpperCase() providing examples of how to use each method to manipulate and analyze string values.
Groovy is a great language with extremely powerful capabilities about compile time meta-programming. Do you know that provides more than 40 AST transformations out-of-the box just to make your life as a developer easier?
In this talk you will learn the most important transformations provided by Groovy. I'll use a lot of code examples to explain all the concepts.
Functional programming avoids changing-state and mutable data. Referential transparency means expressions can be replaced without affecting observable behavior. Pure functions only depend on argument values and have no other effects. Case classes provide functionality like equals, hashCode and pattern matching out of the box. Futures allow running blocking operations asynchronously and chaining results with map, flatMap and for comprehensions. Implicits allow type conversions and providing parameters implicitly. Sealed classes allow exhaustive pattern matching of a type hierarchy.
This document provides an overview of Scala and compares it to Java. It discusses Scala's object-oriented and functional capabilities, how it compiles to JVM bytecode, and benefits like less boilerplate code and support for functional programming. Examples are given of implementing a simple Property class in both Java and Scala to illustrate concepts like case classes, immutable fields, and less lines of code in Scala. The document also touches on Java interoperability, learning Scala gradually, XML processing capabilities, testing frameworks, and tool/library support.
The Ring programming language version 1.2 book - Part 20 of 84Mahmoud Samir Fayed
This document provides documentation on object-oriented programming concepts in Ring including:
- Defining classes with attributes and methods
- Accessing object attributes using dot notation and braces
- Composition of objects as attributes of other objects
- Defining setter and getter methods
- Private and public attributes and methods
- Operator overloading for classes
- Inheritance between classes
- Dynamic attributes defined at runtime
- Packages to organize classes
- Printing and finding objects in lists
- Sorting lists of objects
It includes examples of implementing each concept and the output of running the example code.
The Ring programming language version 1.9 book - Part 41 of 210Mahmoud Samir Fayed
This document provides summaries of Ring programming functions related to classes and objects. It describes functions for getting class names and checking class definitions, getting classes within packages, and checking class and attribute definitions. It also summarizes functions for working with objects, including getting/setting attributes and methods, checking if an object or attribute exists, and adding attributes and methods to objects. Examples are provided to demonstrate the usage of each function.
The Ring programming language version 1.6 book - Part 35 of 189Mahmoud Samir Fayed
This document provides a summary of Ring object-oriented programming functions including:
- Functions to get class, object, and attribute information like classname(), objectid(), isobject(), attributes()
- Functions to add/remove attributes and methods like addattribute(), addmethod()
- Functions to get/set attribute values like getattribute(), setattribute()
- Other functions like mergemethods() to share methods between classes, and packagename() to get the imported package name
The document explains each function and provides examples of their usage.
The Ring programming language version 1.10 book - Part 47 of 212Mahmoud Samir Fayed
This document summarizes the methods available in various Ring classes for data types, conversions, databases, security, and internet functions. It provides examples of using each class and the output. The DataType class allows checking value types and properties. The Conversion class converts between data types. Database classes like ODBC, MySQL, SQLite and PostgreSQL provide methods for connecting to databases and executing queries. The Security class implements hashing and encryption algorithms. The Internet class allows downloading files and sending emails.
Kotlin Basics - Apalon Kotlin Sprint Part 2Kirill Rozov
This document provides an overview of Kotlin basics including:
- Basic data types like Int, String, Boolean
- Collections like List, Set, Map
- Variables, functions, control flow
- Classes, properties, constructors
- Inheritance, interfaces
- Additional features like lambdas, extensions, coroutines
It aims to introduce fundamental Kotlin concepts and syntax in a concise manner.
When you write unit tests for your projects, there’s a fair chance that you do so by following the classical « Given-When-Then » paradigm, in which you set some input data, execute the code you’re testing, and finally assert that its outcome is indeed the one you expected.
While this approach is perfectly sound, it does suffer one downside: your program will only be tested on the static input data defined in your tests, and there is no real guarantee that this data does cover all edge cases. This can be especially problematic for SDK developers, who, by definition, have a very hard time anticipating all the different situations in which their code will be used.
To improve on this issue, another approach exists, and it is called property-based testing. The idea behind it is very simple: you write your tests by defining properties that must always be true for your program. For example, « an array reversed twice is always equal to itself ». The testing framework will then generate random input values and test wether the property holds or not. And, as you can imagine, this approach is extremely good at narrowing down on overlooked edge cases.
In Swift, we are lucky enough to already have a full-fledged implementation called SwiftCheck, that enables property-based testing (https://github.com/typelift/SwiftCheck). The goal of this talk is thus to explain how property-based testing can be a powerful addition to a testing suite, and give actual and actionable examples of how it can be added to a project using SwiftCheck.
Apache Spark - Key Value RDD - Transformations | Big Data Hadoop Spark Tutori...CloudxLab
The document provides information about key-value RDD transformations and actions in Spark. It defines transformations like keys(), values(), groupByKey(), combineByKey(), sortByKey(), subtractByKey(), join(), leftOuterJoin(), rightOuterJoin(), and cogroup(). It also defines actions like countByKey() and lookup() that can be performed on pair RDDs. Examples are given showing how to use these transformations and actions to manipulate key-value RDDs.
Slides from my talk at the Junction (Jan 24, 2013)
Single-core performance has hit a ceiling, and building web-scale multi-core applications using imperative programming models is nightmarishly difficult. Parallel programming creates a new set of challenges, best practices and design patterns. Scala is designed to enable building scalable systems, elegantly blending functional and object oriented paradigms into an expressive and concise language, while retaining interoperability with Java. Scala is the fastest growing JVM programming language, being rapidly adopted by leading companies such as Twitter, LinkedIn and FourSquare.
This presentation provides a comprehensive overview of the language, which managed to increase type safety while feeling more dynamic, being more concise and improving readability at the same time. We will see how Scala simplifies real life problems by empowering the developer with powerful functional programming primitives, without giving up on the object oriented paradigm. The overview includes tools for multi-core programming in Scala, the type system, collection framework and domain-specific languages. We’ll explore the power of compile-time meta-programming, which is made possible by the newly released Scala 2.10, and get a glimpse into what to expect from 2.11 in 2014.
We will also see how Scala helps overcome the inherent limitations of Java, such as type erasure, array covariance and boxing overhead.
Multiple examples emphasize how Scala pushes the JVM harder than any other mainstream language through the infinite number of boilerplate busters, increased type safety and productivity boosters from a Java developer’s perspective.
The Ring programming language version 1.9 book - Part 53 of 210Mahmoud Samir Fayed
This document provides code examples and documentation for Ring's web application framework. It includes code for user authentication using a database, classes for database access and web controllers, and descriptions of the main classes and methods in the WebLib API for generating HTML pages and handling requests. The document covers key concepts like generating pages dynamically based on request parameters, working with databases using Model classes, and common tasks like cookies, file uploads, and URL encoding.
Lecture on Rubinius for Compiler Construction at University of TwenteDirkjan Bussink
This document summarizes Rubinius, an implementation of the Ruby programming language that includes a bytecode virtual machine written in C++ and Ruby. Some key points:
- Rubinius compiles Ruby code to bytecode that runs on its built-in virtual machine. This provides performance improvements over interpreting Ruby code.
- The virtual machine is implemented in both C++ and Ruby to provide flexibility. It can inline methods, perform just-in-time compilation, and garbage collect memory.
- Rubinius aims to be a complete Ruby implementation while also improving performance through techniques like inline caching, profiling, and garbage collection optimizations.
Functional Object-Oriented Imperative Scala / 関数型オブジェクト指向命令型 Scala by Sébasti...scalaconfjp
The document discusses Scala's ability to combine functional and object-oriented programming paradigms. It provides an example of an Emitter class that uses mutable internal state carried between method invocations to improve performance, while maintaining an immutable/functional API that encapsulates the mutable state so it is not observable from outside the class. This approach allows algorithms with mutable data structures internally for readability while preserving the benefits of immutable/functional programming in the public interface.
The Ring programming language version 1.7 book - Part 41 of 196Mahmoud Samir Fayed
This document discusses using nested structures and object composition in Ring to enable declarative programming. It shows how to:
1. Create objects inside lists and add objects to lists.
2. Return objects and lists by reference from methods to avoid copies.
3. Execute a "BraceEnd()" method after accessing an object with braces {} to run cleanup code.
4. Build a declarative programming environment on top of Ring's object orientation features using nested structures, returning references, and BraceEnd() methods.
The Ring programming language version 1.3 book - Part 34 of 88Mahmoud Samir Fayed
This document contains code from the datalib.ring library that defines classes for database connectivity and model-view-controller implementation in Ring.
The Database class handles database connections and queries. The ModelBase class extends Database and adds methods for CRUD operations on a model object. It determines the table name from the class name.
The ControllerBase class is the base class for controllers. It dynamically creates the view and model objects based on the controller class name. It also contains routing logic and pagination methods. These classes provide a framework for building MVC applications with Ring and connecting to a database.
The Ring programming language version 1.10 book - Part 40 of 212Mahmoud Samir Fayed
The document provides examples and explanations of object-oriented programming concepts in Ring including:
1. Defining setter and getter methods to control access to class attributes.
2. Using the self keyword to refer to the current object instance from within methods.
3. Overloading operators like + and - to allow their use with custom class objects.
3. Demonstrating inheritance by defining a child class that inherits from a parent class.
The Ring programming language version 1.5.1 book - Part 43 of 180Mahmoud Samir Fayed
This document provides documentation on functions for performing common database operations like insert, update, delete, search in a Ring application. It includes classes like ModelBase and ControllerBase that handle connecting to the database and executing SQL queries. Methods are provided to load a model from the database, get/set values from the model, and perform CRUD operations on a database table. The ControllerBase class provides request routing and common functions for displaying data in views.
The document discusses several native JavaScript objects including String, Math, Array, and Date objects. It focuses on the String object, describing how to create string variables and primitive types. It then explains several string methods like length, charAt(), charCodeAt(), indexOf(), lastIndexOf(), substr(), toLowerCase(), and toUpperCase() providing examples of how to use each method to manipulate and analyze string values.
Groovy is a great language with extremely powerful capabilities about compile time meta-programming. Do you know that provides more than 40 AST transformations out-of-the box just to make your life as a developer easier?
In this talk you will learn the most important transformations provided by Groovy. I'll use a lot of code examples to explain all the concepts.
Functional programming avoids changing-state and mutable data. Referential transparency means expressions can be replaced without affecting observable behavior. Pure functions only depend on argument values and have no other effects. Case classes provide functionality like equals, hashCode and pattern matching out of the box. Futures allow running blocking operations asynchronously and chaining results with map, flatMap and for comprehensions. Implicits allow type conversions and providing parameters implicitly. Sealed classes allow exhaustive pattern matching of a type hierarchy.
This document provides an overview of Scala and compares it to Java. It discusses Scala's object-oriented and functional capabilities, how it compiles to JVM bytecode, and benefits like less boilerplate code and support for functional programming. Examples are given of implementing a simple Property class in both Java and Scala to illustrate concepts like case classes, immutable fields, and less lines of code in Scala. The document also touches on Java interoperability, learning Scala gradually, XML processing capabilities, testing frameworks, and tool/library support.
The Ring programming language version 1.2 book - Part 20 of 84Mahmoud Samir Fayed
This document provides documentation on object-oriented programming concepts in Ring including:
- Defining classes with attributes and methods
- Accessing object attributes using dot notation and braces
- Composition of objects as attributes of other objects
- Defining setter and getter methods
- Private and public attributes and methods
- Operator overloading for classes
- Inheritance between classes
- Dynamic attributes defined at runtime
- Packages to organize classes
- Printing and finding objects in lists
- Sorting lists of objects
It includes examples of implementing each concept and the output of running the example code.
The Ring programming language version 1.9 book - Part 41 of 210Mahmoud Samir Fayed
This document provides summaries of Ring programming functions related to classes and objects. It describes functions for getting class names and checking class definitions, getting classes within packages, and checking class and attribute definitions. It also summarizes functions for working with objects, including getting/setting attributes and methods, checking if an object or attribute exists, and adding attributes and methods to objects. Examples are provided to demonstrate the usage of each function.
The Ring programming language version 1.6 book - Part 35 of 189Mahmoud Samir Fayed
This document provides a summary of Ring object-oriented programming functions including:
- Functions to get class, object, and attribute information like classname(), objectid(), isobject(), attributes()
- Functions to add/remove attributes and methods like addattribute(), addmethod()
- Functions to get/set attribute values like getattribute(), setattribute()
- Other functions like mergemethods() to share methods between classes, and packagename() to get the imported package name
The document explains each function and provides examples of their usage.
The Ring programming language version 1.10 book - Part 47 of 212Mahmoud Samir Fayed
This document summarizes the methods available in various Ring classes for data types, conversions, databases, security, and internet functions. It provides examples of using each class and the output. The DataType class allows checking value types and properties. The Conversion class converts between data types. Database classes like ODBC, MySQL, SQLite and PostgreSQL provide methods for connecting to databases and executing queries. The Security class implements hashing and encryption algorithms. The Internet class allows downloading files and sending emails.
Kotlin Basics - Apalon Kotlin Sprint Part 2Kirill Rozov
This document provides an overview of Kotlin basics including:
- Basic data types like Int, String, Boolean
- Collections like List, Set, Map
- Variables, functions, control flow
- Classes, properties, constructors
- Inheritance, interfaces
- Additional features like lambdas, extensions, coroutines
It aims to introduce fundamental Kotlin concepts and syntax in a concise manner.
When you write unit tests for your projects, there’s a fair chance that you do so by following the classical « Given-When-Then » paradigm, in which you set some input data, execute the code you’re testing, and finally assert that its outcome is indeed the one you expected.
While this approach is perfectly sound, it does suffer one downside: your program will only be tested on the static input data defined in your tests, and there is no real guarantee that this data does cover all edge cases. This can be especially problematic for SDK developers, who, by definition, have a very hard time anticipating all the different situations in which their code will be used.
To improve on this issue, another approach exists, and it is called property-based testing. The idea behind it is very simple: you write your tests by defining properties that must always be true for your program. For example, « an array reversed twice is always equal to itself ». The testing framework will then generate random input values and test wether the property holds or not. And, as you can imagine, this approach is extremely good at narrowing down on overlooked edge cases.
In Swift, we are lucky enough to already have a full-fledged implementation called SwiftCheck, that enables property-based testing (https://github.com/typelift/SwiftCheck). The goal of this talk is thus to explain how property-based testing can be a powerful addition to a testing suite, and give actual and actionable examples of how it can be added to a project using SwiftCheck.
This document discusses Scala features for parallelism, concurrency, and reactive programming. Some key points include:
- Scala supports parallel collections that can perform operations like map, reduce, and filter in parallel.
- Futures represent asynchronous computations whose results are not yet known. They allow non-blocking operations.
- Actors are units of concurrency that communicate asynchronously by message passing. They encapsulate state and behavior.
- Akka is a toolkit for building highly concurrent, distributed, and fault-tolerant event-driven applications using actors. It implements the actor model in Scala.
Some languages, like SML, Haskell, and Scala, have built-in support for pattern matching, which is a generic way of branching based on the structure of data.
While not without its drawbacks, pattern matching can help eliminate a lot of boilerplate, and it's often cited as a reason why functional programming languages are so concise.
In this talk, John A. De Goes talks about the differences between built-in patterns, and so-called first-class patterns (which are "do-it-yourself" patterns implemented using other language features).
Unlike built-in patterns, first-class patterns aren't magical, so you can store them in variables and combine them in lots of interesting ways that aren't always possible with built-in patterns. In addition, almost every programming language can support first-class patterns (albeit with differing levels of effort and type-safety).
During the talk, you'll watch as a mini-pattern matching library is developed, and have the opportunity to follow along and build your own pattern matching library in the language of your choice.
Cypher inside out: Como a linguagem de pesquisas em grafo do Neo4j foi constr...adrianoalmeida7
The document discusses how Cypher, the query language of Neo4j, was built and how to use it. It explains that Cypher was constructed using parser combinators in Scala to parse queries into an AST. It then describes how the different clauses of a Cypher query (start, match, where, return, etc.) are parsed and provides examples. Finally, it discusses how queries are executed by passing through different processing pipes in the ExecutionEngine.
Model-Driven Software Development - Pretty-Printing, Editor Services, Term Re...Eelco Visser
The document discusses three topics: pretty-printing, editor services, and term rewriting. Pretty-printing involves transforming abstract syntax trees to concrete syntax. Editor services define behaviors for syntax highlighting, code folding, outlines, and completions. Term rewriting uses rewrite rules and strategies to transform abstract syntax trees.
This document provides an introduction to the Scala programming language. It discusses that Scala is a hybrid language that is both object-oriented and functional, runs on the JVM, and provides seamless interoperability with Java. It highlights features of Scala such as pattern matching, traits, case classes, immutable data structures, lazy evaluation, and actors for concurrency.
The document provides an overview of Scala concepts for Java programmers, including object-oriented features, pattern matching, functional programming constructs like immutability and higher-order functions, actors and futures for concurrency, and implicits. Key concepts covered include case classes, lazy evaluation, parallel collections, currying, partial functions, and implicit parameters.
(How) can we benefit from adopting scala?Tomasz Wrobel
Scala offers benefits from adopting it such as increased productivity through concise and expressive code, static typing with type inference, support for both object-oriented and functional programming paradigms, and interoperability with Java. Switching from Java to Scala involves some changes like using val for immutable variables and var for mutable, but overall the syntax is quite similar which eases the transition.
This document provides an overview of pattern matching in Scala. It begins by comparing Scala's match expression to switch statements in other languages. Match expressions allow matching against a broader range of types, including alternate patterns using pipes (|). Variables can be bound in matches using the "x @ pattern" syntax. Matches can also be made on type and include guards for fine-grained selection. Case classes enable easy pattern matching on constructor arguments. Sealed hierarchies allow exhaustive matching. Custom extractors can be defined to perform matching via the "unapply" method. Examples show matching IP addresses and summing components using custom octet extraction.
This document provides an overview of coding in style with Scala. It discusses embracing expressions over statements, operator notation, using language features to simplify code, favoring higher-order functions, manipulating data with collections, working with asynchronous code and futures, macro programming to transform ASTs, and new features coming in Scala 2.11 like potential modularization and performance improvements. The document encourages idiomatic Scala techniques like favoring expressions, embracing operators, letting the language do work, aiming higher with higher-order functions, and embracing new language features.
This document discusses Haskell concepts and how they compare to object-oriented programming concepts in languages like C++ and Python. It covers topics like algebraic data types, classes and instances in Haskell, and how concepts like private fields differ between Haskell and other languages. It also includes examples of data types, functions, and classes in Haskell as well as frequently asked questions about Haskell features.
The document provides an overview of the Spock testing framework for Java Virtual Machine (JVM) applications. It describes Spock as a behavior-driven development (BDD) testing tool that can be used for both unit and system tests. Spock tests use a given-when-then structure and various blocks like setup, cleanup, and where to define fixtures, exercise code, and make assertions. It also supports features like parameterized tests, helper methods, and powerful assertions.
QuickCheck is a lightweight tool for randomly testing Haskell programs. It uses type classes like Arbitrary and CoArbitrary to generate random test cases for data types and functions. Properties to check are specified using a domain specific language embedded in Haskell. Case studies show it can find errors in programs like unification and pretty printing. While lightweight, QuickCheck has limitations like difficulty testing non-terminating programs and formal specifications are still needed to fully check programs.
Помните легендарные Java Puzzlers? Да-да, те самые, с Джошом Блохом и Нилом Гафтером? Ну, по которым ещё книжку написали? Так вот, в Groovy всё ещё веселее.
В смысле — задачки ещё более странные, и ответы ещё более поразительные. Этот доклад для вас, Groovy-разработчики, мы покажем вам настоящие, большие и красивые подводные камни! И для вас, Java-разработчики, потому что таких вещей на Java-подобном синтакисе вы точно никогда не видели! И для вас, PHP-разработчики… хотя, нет, не для вас :)
Всем точно будет весело — ваши ведущие Женя и Барух будут зажигать, шутить, спорить, бросаться футболками в публику, и самое главное — заставят вас офигевать от Groovy.
Testing Web Applications with GEB provides concise summaries in 3 sentences or less:
GEB allows testing of web applications by driving browsers like Firefox using the Selenium WebDriver API. It integrates with jQuery-like content selection and supports features like page objects, modules, and JavaScript execution to simplify testing of Ajax applications. GEB uses Groovy for a more expressive and dynamic testing approach compared to other frameworks like Selenium.
JavaScript Code Formatting With Prettier by Christopher ChedeauReact London 2017
JavaScript developers are spending soooo much time formatting their code and even more in back and forth in code review fixing small nits. It turns out that machines are really good at doing this kind of tasks. Christopher will walk us through the technical and people challenges of bringing a JavaScript code formatter to reality.
Not so long ago Microsoft announced a new language trageting on front-end developers. Everybody's reaction was like: Why?!! Is it just Microsoft darting back to Google?!
So, why a new language? JavaScript has its bad parts. Mostly you can avoid them or workaraund. You can emulate class-based OOP style, modules, scoping and even run-time typing. But that is doomed to be clumsy. That's not in the language design. Google has pointed out these flaws, provided a new language and failed. Will the story of TypeScript be any different?
Similar to Scala Domain Modeling and Architecture (20)
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
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
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
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.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on automated letter generation for Bonterra Impact Management using Google Workspace or Microsoft 365.
Interested in deploying letter generation automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
31. object Chromosome extends
Entity
with RelationalEntity!
with GraphVertex
with XmlElement {
self =>
sealed trait ChromosomePart {
val ownerType = self
}
// Ontology Trait
val featuringType = self
val ownedFeature = chromatine :: Nil
// XML Trait
val namespace = "urn:domain:chromosome:1.0"
val prefix = "chr"
// Features
val chromatine =
new Chromatine(
name = "chromatine",
ownerType = Chromosome,
mapping = Map.empty[String, String])
}
32. implicit def enrich[A <: DomainModel](model: A) = new {
def metamodel: Option[Type] = Ontology.typeOf(model)
}
def xmlFilter[A <: DomainModel] =
(model: A) ⇒ model.metamodel match {
case Some(_: XmlElement) ⇒ body(XmlModel[A](model))
case _ ⇒ fail[XmlModel[A]]!
("No XmlElement meta-model definition could be found")
}
def ingoingEdges[A <: DomainModel] =
(model: A) ⇒ model.metamodel match {
case Some(vertex: GraphVertex) ⇒ !
Ontology.edges.filter(_.target == vertex)
case _ ⇒ List.empty[GraphEdge]
}
33. implicit def enrich[A <: DomainModel](model: A) = new {
def metamodel: Option[Type] = Ontology.typeOf(model)
}
def xmlFilter[A <: DomainModel] =
(model: A) ⇒ model.metamodel match {
case Some(_: XmlElement) ⇒ body(XmlModel[A](model))
case _ ⇒ fail[XmlModel[A]]!
("No XmlElement meta-model definition could be found")
}
def ingoingEdges[A <: DomainModel] =
(model: A) ⇒ model.metamodel match {
case Some(vertex: GraphVertex) ⇒ !
Ontology.edges.filter(_.target == vertex)
case _ ⇒ List.empty[GraphEdge]
}