Mutation Testing is awesome! And it is used to evaluate the quality of existing software tests by modifying the program's source code, based on well-defined mutation operators. Each 'mutated' version is called a mutant and a test which detects the mutation (fail) will kill the mutant. Mutants without failing tests are alive!
The Swift Compiler and Standard LibrarySantosh Rajan
The document discusses the Swift compiler, standard library, and key language features. It provides an overview of the Swift compiler's location and how to compile and run Swift programs from the command line. It also summarizes the main types, protocols, operators and global functions that are included in Swift's standard library.
This is the second set of slightly updated slides from a Perl programming course that I held some years ago.
I want to share it with everyone looking for intransitive Perl-knowledge.
A table of content for all presentations can be found at i-can.eu.
The source code for the examples and the presentations in ODP format are on https://github.com/kberov/PerlProgrammingCourse
OCJP Samples Questions: Exceptions and assertionsHari kiran G
The document contains sample questions and explanations for the OCP Java SE 8 exam related to exceptions and assertions. It includes multiple choice questions about exception handling, try-catch blocks, and assertion failures. The explanations provide details about which exceptions would be thrown and the output of code snippets.
Here is a Python function that calculates the distance between two points given their x and y coordinates:
```python
import math
def distance_between_points(x1, y1, x2, y2):
return math.sqrt((x2 - x1)**2 + (y2 - y1)**2)
```
To use it:
```python
distance = distance_between_points(1, 2, 4, 5)
print(distance)
```
This would print 3.605551275463989, which is the distance between the points (1,2) and (4,5).
The key steps are:
1.
There are a lot of operators in Perl 6, so many that it can be called an OOL: operator oriented language. Here I describe most of them from the angle of contexts, which Perl 6 has also much more than Perl 5.
This document provides an agenda and overview for a Python programming training on exception handling, modules, packages, object-oriented programming concepts, and working with databases in Python. The training will cover exception handling syntax, raising exceptions, and try/except blocks. It will also discuss modules, packages, and how to create reusable code. Key object-oriented programming concepts like classes, objects, inheritance, polymorphism, and encapsulation are defined. The document gives examples of connecting to a database and executing SQL statements using the MySQLdb module in Python.
The Guava project contains several of Google’s core libraries that we rely on in our Java-based projects: collections, caching, primitives support, concurrency libraries, common annotations, string processing, I/O, and so forth. There will be the slides presenting most useful and interesting features of Guava (v.12) that makes stuff simpler, better and code cleaner. We will cover most of the com.google.common.base.* classes and basic use of functions in collection and Google collections and few other features that are part of Guava and I find them very useful. Some of you will think that there is an overlap with Apache commons – and it’s true, but Guava is built with expectation that there is a Function and a Predicate class as well as various builders which makes it really cool and simple for many use cases.
The Swift Compiler and Standard LibrarySantosh Rajan
The document discusses the Swift compiler, standard library, and key language features. It provides an overview of the Swift compiler's location and how to compile and run Swift programs from the command line. It also summarizes the main types, protocols, operators and global functions that are included in Swift's standard library.
This is the second set of slightly updated slides from a Perl programming course that I held some years ago.
I want to share it with everyone looking for intransitive Perl-knowledge.
A table of content for all presentations can be found at i-can.eu.
The source code for the examples and the presentations in ODP format are on https://github.com/kberov/PerlProgrammingCourse
OCJP Samples Questions: Exceptions and assertionsHari kiran G
The document contains sample questions and explanations for the OCP Java SE 8 exam related to exceptions and assertions. It includes multiple choice questions about exception handling, try-catch blocks, and assertion failures. The explanations provide details about which exceptions would be thrown and the output of code snippets.
Here is a Python function that calculates the distance between two points given their x and y coordinates:
```python
import math
def distance_between_points(x1, y1, x2, y2):
return math.sqrt((x2 - x1)**2 + (y2 - y1)**2)
```
To use it:
```python
distance = distance_between_points(1, 2, 4, 5)
print(distance)
```
This would print 3.605551275463989, which is the distance between the points (1,2) and (4,5).
The key steps are:
1.
There are a lot of operators in Perl 6, so many that it can be called an OOL: operator oriented language. Here I describe most of them from the angle of contexts, which Perl 6 has also much more than Perl 5.
This document provides an agenda and overview for a Python programming training on exception handling, modules, packages, object-oriented programming concepts, and working with databases in Python. The training will cover exception handling syntax, raising exceptions, and try/except blocks. It will also discuss modules, packages, and how to create reusable code. Key object-oriented programming concepts like classes, objects, inheritance, polymorphism, and encapsulation are defined. The document gives examples of connecting to a database and executing SQL statements using the MySQLdb module in Python.
The Guava project contains several of Google’s core libraries that we rely on in our Java-based projects: collections, caching, primitives support, concurrency libraries, common annotations, string processing, I/O, and so forth. There will be the slides presenting most useful and interesting features of Guava (v.12) that makes stuff simpler, better and code cleaner. We will cover most of the com.google.common.base.* classes and basic use of functions in collection and Google collections and few other features that are part of Guava and I find them very useful. Some of you will think that there is an overlap with Apache commons – and it’s true, but Guava is built with expectation that there is a Function and a Predicate class as well as various builders which makes it really cool and simple for many use cases.
This document provides an overview of the Python programming language. It includes several code examples and summaries of key Python concepts like strings, lists, tuples, dictionaries, files, regular expressions, and object-oriented programming. It also lists some common Python functions and modules for tasks like HTTP requests and database access. The document aims to introduce Python's main features and provide basic code samples to help new Python learners.
Protocols with Associated Types, and How They Got That WayAlexis Gallagher
This talk at the 2015 Function Swift Conference summarized challenges with Swift's Protocols With Associated Types, the reasons for their behavior, their roots in features from other languages, how to workaround issues, and whether to expect them to change.
This document provides an overview of Guava, a common libraries project from Google that includes utilities for collections, caching, predicates and functions, I/O, and more. It highlights features like Optional for avoiding null checks, immutable collections, filtering collections, transforming collections, caching, and string/object utilities. The document also discusses when and where Guava can be used, such as for temporary collections, avoiding null checks, and leveraging a popular library maintained by others.
This document summarizes new features in Swift 2 including guard/defer statements for flow control, protocol extensions for default implementations, and error handling improvements like throwing and catching errors. It also mentions Swift becoming open source with its source code released under a permissive license and contributions accepted from the community, including ports for Linux. Nest is provided as an example open source Swift web framework project on GitHub.
Slides for presentation on Google Guava I gave at the Near Infinity (www.nearinfinity.com) 2013 spring conference.
The associated sample code is on GitHub at https://github.com/sleberknight/google-guava-samples
This document provides an overview and examples of using Google Guava, an open-source Java library that includes common libraries useful for writing Java code. It highlights some key classes and methods in Guava, including annotations, strings, collections, I/O, and more. Code samples demonstrate using Guava features like predicates, sets, files, and InetAddress utilities.
The core libraries you always wanted - Google GuavaMite Mitreski
Google Guava is a set of core Java libraries that includes collections, caching, predicates and functions, primitives support, and other utilities. It aims to fill in gaps in the Java class library and improve on Java SE classes. Some key features include optional types, immutable collections, caching utilities, character matching, and functional interfaces like predicates and functions. Guava provides utilities to avoid null checks, filter collections, transform values, and load resources. It also includes hashing, bloom filters, and other utilities. Using Guava can make code cleaner and safer by leveraging well-tested utilities rather than reimplementing functionality.
This document provides an overview of Go and compares it to Java. It begins with "Hello World" examples in both Go and Java. It then covers familiar features like variables, conditions, functions, errors, and loops. It discusses differences between the two languages such as visibility, type inference, and interfaces. It also provides performance comparisons showing Go to be significantly faster than Java. The document aims to help Java developers get started with Go.
This document provides an overview of Go and compares it to Java. It begins with "Hello World" examples in Go and Java. It then covers familiar features like variables, conditions, functions, errors, and loops. It discusses differences between the languages like visibility, type inference, and interfaces. The document suggests Go has better performance than Java and allows cross-compilation. It also introduces gRPC and WebAssembly as technologies that work with Go.
This document provides an overview of the Perl programming language. It introduces key Perl concepts like data types, scalars, arrays, hashes, flow control, input/output, and operators. Perl allows variables to be of any type and handles automatic type conversion. It supports common data structures like arrays and associative arrays (hashes). Subroutines provide modularity and scoping rules determine variable visibility. Perl scripts can process command line arguments, files, and network connections.
This document provides an introduction and overview of the Google Guava libraries. It describes what Guava is, why developers would use it, how it compares to Apache Commons libraries, its design principles and release cycles. It provides descriptions of some key Guava packages and classes for common Java utilities, including Preconditions, Optional, Objects, Strings, Charsets, CaseFormat, CharMatcher, Joiner and Splitter. The document aims to explain the purpose and usage of important Guava functionality.
Functional programming is all the rage. It can undoubtedly produce cleaner and more expressive code, but why switch to Scala or wait for Java 8? In fact, there are many ways to dramatically improve your Java code quality by using a more functional style today. This presentation discusses how techniques such as functional programming, using fluent APIs, and other clean coding practices can make your code more concise, more readable, and much easier to maintain. But more importantly, you will learn about libraries such as LambdaJ and Google Guava that make this possible today with your existing Java code base.
Slides from Advaned Python lectures I gave recently in Haifa Linux club
Advanced python, Part 1:
- Decorators
- Descriptors
- Metaclasses
- Multiple inheritance
The document provides an overview of functional programming in Java. It discusses functional programming concepts like higher-order functions and avoiding side effects. It gives examples of functional-style code in Java for filtering lists and transforming objects. It also discusses how functional programming can be used to implement customizable business logic by passing functions as parameters and looking up functions through a dependency injection container.
Introduction to Swift programming language.Icalia Labs
Take a look to Swift, if you've been developing for iOS in Objective-C many things may look familiar, maybe just "upgraded". If you're a first timer diving into iOS development we strongly recommend you to understand first the basics of Cocoa.
Swift is a multi-paradigm programming language developed by Apple for iOS, macOS, watchOS, and tvOS. It was inspired by Objective-C, Rust, Haskell, Ruby, Python, C#, CLU, and other languages. The document discusses Swift's history, principles, syntax including variables, constants, data types, functions, closures, and control structures. It provides code examples and explanations of Swift's main features.
Full-day tutorial for the dutch php conference 2011 giving a very quick tour around all the various areas of the ZCE syllabus and some tips on the exam styles
Java 8: the good, the bad and the ugly (Oracle Code Brussels 2017)Brian Vermeer
This document summarizes key features of Java 8 including lambdas, functional interfaces, streams, and optional. It discusses lambda expressions and how they allow implementing functional interfaces more concisely. Streams are introduced as a way to process collections lazily and in parallel. Exceptions in lambdas and streams are covered. Optional is presented as a wrapper for null values. Best practices are provided around these new Java 8 features.
Java 8: the good, the bad and the ugly (JBCNConf 2017)Brian Vermeer
This document provides an overview and summary of key features in Java 8, including:
- Lambda expressions which allow implementation of functional interfaces in a more concise way
- Default methods which allow extension of interfaces without breaking existing implementations
- Streams API which supports functional-style operations on streams of elements
- Date and time API improvements with new java.time package
- Optional as a container class for nullable values
This document contains notes from a series of tips and quirks related to Ruby programming. It covers topics like local variables in different Ruby versions, differences between strings and symbols, using modules and classes, responding to super, object counting, finalizers, and calling procs. The document provides code examples to demonstrate various Ruby language features and behaviors.
The document provides an overview of the Groovy programming language. It discusses key Groovy features such as closures, operator overloading, array slicing, collections, dynamic methods, properties and mixins. It also covers regular expressions, file input/output, database operations and how Groovy provides a unified approach to these tasks. The agenda outlines topics including introductions, features, closures and more.
This document provides an overview of the Python programming language. It includes several code examples and summaries of key Python concepts like strings, lists, tuples, dictionaries, files, regular expressions, and object-oriented programming. It also lists some common Python functions and modules for tasks like HTTP requests and database access. The document aims to introduce Python's main features and provide basic code samples to help new Python learners.
Protocols with Associated Types, and How They Got That WayAlexis Gallagher
This talk at the 2015 Function Swift Conference summarized challenges with Swift's Protocols With Associated Types, the reasons for their behavior, their roots in features from other languages, how to workaround issues, and whether to expect them to change.
This document provides an overview of Guava, a common libraries project from Google that includes utilities for collections, caching, predicates and functions, I/O, and more. It highlights features like Optional for avoiding null checks, immutable collections, filtering collections, transforming collections, caching, and string/object utilities. The document also discusses when and where Guava can be used, such as for temporary collections, avoiding null checks, and leveraging a popular library maintained by others.
This document summarizes new features in Swift 2 including guard/defer statements for flow control, protocol extensions for default implementations, and error handling improvements like throwing and catching errors. It also mentions Swift becoming open source with its source code released under a permissive license and contributions accepted from the community, including ports for Linux. Nest is provided as an example open source Swift web framework project on GitHub.
Slides for presentation on Google Guava I gave at the Near Infinity (www.nearinfinity.com) 2013 spring conference.
The associated sample code is on GitHub at https://github.com/sleberknight/google-guava-samples
This document provides an overview and examples of using Google Guava, an open-source Java library that includes common libraries useful for writing Java code. It highlights some key classes and methods in Guava, including annotations, strings, collections, I/O, and more. Code samples demonstrate using Guava features like predicates, sets, files, and InetAddress utilities.
The core libraries you always wanted - Google GuavaMite Mitreski
Google Guava is a set of core Java libraries that includes collections, caching, predicates and functions, primitives support, and other utilities. It aims to fill in gaps in the Java class library and improve on Java SE classes. Some key features include optional types, immutable collections, caching utilities, character matching, and functional interfaces like predicates and functions. Guava provides utilities to avoid null checks, filter collections, transform values, and load resources. It also includes hashing, bloom filters, and other utilities. Using Guava can make code cleaner and safer by leveraging well-tested utilities rather than reimplementing functionality.
This document provides an overview of Go and compares it to Java. It begins with "Hello World" examples in both Go and Java. It then covers familiar features like variables, conditions, functions, errors, and loops. It discusses differences between the two languages such as visibility, type inference, and interfaces. It also provides performance comparisons showing Go to be significantly faster than Java. The document aims to help Java developers get started with Go.
This document provides an overview of Go and compares it to Java. It begins with "Hello World" examples in Go and Java. It then covers familiar features like variables, conditions, functions, errors, and loops. It discusses differences between the languages like visibility, type inference, and interfaces. The document suggests Go has better performance than Java and allows cross-compilation. It also introduces gRPC and WebAssembly as technologies that work with Go.
This document provides an overview of the Perl programming language. It introduces key Perl concepts like data types, scalars, arrays, hashes, flow control, input/output, and operators. Perl allows variables to be of any type and handles automatic type conversion. It supports common data structures like arrays and associative arrays (hashes). Subroutines provide modularity and scoping rules determine variable visibility. Perl scripts can process command line arguments, files, and network connections.
This document provides an introduction and overview of the Google Guava libraries. It describes what Guava is, why developers would use it, how it compares to Apache Commons libraries, its design principles and release cycles. It provides descriptions of some key Guava packages and classes for common Java utilities, including Preconditions, Optional, Objects, Strings, Charsets, CaseFormat, CharMatcher, Joiner and Splitter. The document aims to explain the purpose and usage of important Guava functionality.
Functional programming is all the rage. It can undoubtedly produce cleaner and more expressive code, but why switch to Scala or wait for Java 8? In fact, there are many ways to dramatically improve your Java code quality by using a more functional style today. This presentation discusses how techniques such as functional programming, using fluent APIs, and other clean coding practices can make your code more concise, more readable, and much easier to maintain. But more importantly, you will learn about libraries such as LambdaJ and Google Guava that make this possible today with your existing Java code base.
Slides from Advaned Python lectures I gave recently in Haifa Linux club
Advanced python, Part 1:
- Decorators
- Descriptors
- Metaclasses
- Multiple inheritance
The document provides an overview of functional programming in Java. It discusses functional programming concepts like higher-order functions and avoiding side effects. It gives examples of functional-style code in Java for filtering lists and transforming objects. It also discusses how functional programming can be used to implement customizable business logic by passing functions as parameters and looking up functions through a dependency injection container.
Introduction to Swift programming language.Icalia Labs
Take a look to Swift, if you've been developing for iOS in Objective-C many things may look familiar, maybe just "upgraded". If you're a first timer diving into iOS development we strongly recommend you to understand first the basics of Cocoa.
Swift is a multi-paradigm programming language developed by Apple for iOS, macOS, watchOS, and tvOS. It was inspired by Objective-C, Rust, Haskell, Ruby, Python, C#, CLU, and other languages. The document discusses Swift's history, principles, syntax including variables, constants, data types, functions, closures, and control structures. It provides code examples and explanations of Swift's main features.
Full-day tutorial for the dutch php conference 2011 giving a very quick tour around all the various areas of the ZCE syllabus and some tips on the exam styles
Java 8: the good, the bad and the ugly (Oracle Code Brussels 2017)Brian Vermeer
This document summarizes key features of Java 8 including lambdas, functional interfaces, streams, and optional. It discusses lambda expressions and how they allow implementing functional interfaces more concisely. Streams are introduced as a way to process collections lazily and in parallel. Exceptions in lambdas and streams are covered. Optional is presented as a wrapper for null values. Best practices are provided around these new Java 8 features.
Java 8: the good, the bad and the ugly (JBCNConf 2017)Brian Vermeer
This document provides an overview and summary of key features in Java 8, including:
- Lambda expressions which allow implementation of functional interfaces in a more concise way
- Default methods which allow extension of interfaces without breaking existing implementations
- Streams API which supports functional-style operations on streams of elements
- Date and time API improvements with new java.time package
- Optional as a container class for nullable values
This document contains notes from a series of tips and quirks related to Ruby programming. It covers topics like local variables in different Ruby versions, differences between strings and symbols, using modules and classes, responding to super, object counting, finalizers, and calling procs. The document provides code examples to demonstrate various Ruby language features and behaviors.
The document provides an overview of the Groovy programming language. It discusses key Groovy features such as closures, operator overloading, array slicing, collections, dynamic methods, properties and mixins. It also covers regular expressions, file input/output, database operations and how Groovy provides a unified approach to these tasks. The agenda outlines topics including introductions, features, closures and more.
The document provides an introduction and overview of the Groovy programming language. It discusses key Groovy features such as closures, operator overloading, array slicing, collections, graphics, and web programming capabilities. The agenda outlines topics covered which include introductions to Groovy, closures, collections, and how to get started with Groovy installations and configurations. Examples of Groovy code are also provided to illustrate various language features.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and optionally returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then tells the processor to execute the program. Functions allow code to be reused by defining operations that take in arguments and return values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
The document discusses key concepts in Java programming including:
1. Java is an object-oriented programming language that is platform independent and allows developers to create applications, applets, and web applications.
2. The Java code is first compiled to bytecode, which can then be executed on any Java Virtual Machine (JVM) regardless of the underlying hardware or operating system.
3. Core Java concepts covered include classes, objects, encapsulation, inheritance, polymorphism, and abstraction. Operators, flow control statements, arrays, strings and object-oriented programming principles are also summarized.
Lazy Java by Mario Fusco
Like all imperative languages Java is, with some minor but notable exceptions, an eagerly evaluated programming language. Nevertheless the introduction of lambdas in Java 8 also allowed the adoption of some lazy patterns and data structures that are more typically employed in functional languages. Streams represent the most evident example of how also native Java API has taken advantage of laziness, but there is a number of other interesting scenarios where laziness can be an effective solution to quite common problems. In fact laziness is the only possible technique to process potentially infinite amount of data, or more in general to delay the expensive evaluation of an expression only when and if it is necessary. But laziness is even more than that: for instance the reader monad delays not only a computation but also the need of external dependencies thus lowering the abuse of dependency injection, while a trampoline uses laziness to delay and then linearize recursive calls preventing the overflow of the stack. The purpose of this talk is illustrating why and how implementing laziness in Java with practical examples delivered with both slides and live coding sessions.
The document discusses lazy evaluation and how it can improve performance by avoiding unnecessary computations. Some key points:
- Lazy evaluation delays evaluating expressions until their values are needed. This allows for optimizations like avoiding evaluating function arguments that are not used.
- Languages like Java are strict, meaning functions always immediately evaluate their arguments. But some constructs like boolean operators and ternary expressions are lazily evaluated for efficiency.
- Lazy evaluation enables infinite streams, as in Java 8, since intermediate operations are not computed until a terminal operation triggers the full pipeline.
- Some algorithms like generating primes cannot reasonably be implemented without laziness. It allows separating problem description from evaluation.
- Implementing laziness in Java requires
Mario Fusco - Lazy Java - Codemotion Milan 2018Codemotion
Like all imperative languages Java is eagerly evaluated, but the introduction of lambdas allowed the adoption of some lazy patterns and data structures that are typically functional. Streams are the most evident example of a native Java API using laziness, but there are other cases where laziness is an effective solution to common problems. In fact it makes possible to process infinite amount of data, but it is even more than that. This talk shows why and how implementing laziness in Java with practical examples delivered with both slides and live coding sessions.
Functions allow programmers to organize and structure their code by splitting it into reusable blocks. There are two types of functions: built-in functions that are predefined in Python, and user-defined functions that programmers create. Functions make code easier to debug, test and maintain by dividing programs into separate, reusable parts. Functions can take arguments as input and return values. Function definitions do not alter the normal flow of a program's execution, but calling a function causes the program flow to jump to the function code and then return to pick up where it left off.
The document discusses various techniques for refactoring Ruby code including improving readability, maintainability, and extensibility while preserving existing behavior. It provides examples of simplifying conditional logic, reducing duplication, improving brevity, and leveraging built-in Ruby methods and syntax.
Functions, Exception, Modules and Files
Functions: Difference between a Function and a Method, Defining a Function, Calling a Function, Returning Results from a Function, Returning Multiple Values from a Function, Functions are First Class Objects, Pass by Object Reference, Formal and Actual Arguments, Positional Arguments, Keyword Arguments, Default Arguments, Variable Length Arguments, Local and Global Variables, The Global Keyword, Passing a Group of Elements to a Function, Recursive Functions, Anonymous Functions or Lambdas (Using Lambdas with filter() Function, Using Lambdas with map() Function, Using Lambdas with reduce() Function), Function Decorators, Generators, Structured Programming, Creating our Own Modules in Python, The Special Variable __name__
Exceptions: Errors in a Python Program (Compile-Time Errors, Runtime Errors, Logical Errors),Exceptions, Exception Handling, Types of Exceptions, The Except Block, The assert Statement, UserDefined Exceptions, Logging the Exceptions
20%
Files: Files, Types of Files in Python, Opening a File, Closing a File, Working with Text Files Containing Strings, Knowing Whether a File Exists or Not, Working with Binary Files, The with Statement, Pickle in Python, The seek() and tell() Methods, Random Accessing of Binary Files, Random Accessing of Binary Files using mmap, Zipping and Unzipping Files, Working with Directories, Running Other Programs from Python Program
Desarrollando aplicaciones web en minutosEdgar Suarez
This document provides an overview of the Ruby programming language, including:
- Its creation by Yukihiro Matsumoto in 1993 and key influences like Perl, Smalltalk, and Lisp.
- Its main features like dynamic typing, duck typing, readable syntax, metaprogramming capabilities, blocks, exceptions, and object orientation.
- How Ruby on Rails was created by David Heinemeier Hansson in 2004 to build web applications using Ruby.
- Common tasks when using Ruby like installing Ruby and Rails, generating models and migrations, associations, validations, and using the MVC framework.
This document discusses refactoring code in Ruby. It provides examples of refactoring techniques like replacing conditionals with polymorphism, introducing named parameters, replacing magic numbers with symbolic constants, extracting surrounding methods, and replacing loops with closure methods. The goal of refactoring is to clean up code without changing its external behavior in order to make it more readable, flexible and maintainable.
Similar to Mutation testing with the mutant gem (20)
Imagine for a while that Rails wouldn't exist. How would we write a MVC app from scratch?
Rack provides a minimal interface for developing web applications in Ruby. In fact it's the solid foundation of all major Ruby powered web frameworks.
During this talk we will dive deep into Rack. We will see the smallest possible Rack Application and learn how it works, by studying Rack internals. We will grow the Application step by step till we implement it in simple MVC style.
The document discusses the return of an old enemy to the PHP community who has reformed and is now well-organized to improve. It then provides an extensive list of PHP libraries, frameworks, and tools categorized by function to help with improving PHP skills and code quality. The list is maintained by the Awesome PHP project and covers areas like dependency management, frameworks, testing, security, and more.
Rails Girls: Programming, Web Applications and Ruby on RailsDonSchado
This document provides an introduction to programming, web applications, and Ruby on Rails. It discusses key concepts like HTTP requests and responses, the MVC pattern, and the Rails framework. It encourages learning programming through communication, passion, research, problem solving and patience. The document concludes by recommending resources for learning to code in Ruby on Rails.
This document discusses the Decorator and Presenter design patterns as solutions to fat controllers and views that contain too much logic. The Decorator pattern allows dynamically adding behavior to individual objects by wrapping them, keeping concerns separated. A Presenter is a specialized Decorator that provides view-specific data. The document recommends using a Presenter/Decorator like Draper to move presentation logic out of controllers and into dedicated objects. This keeps controllers lean and logic out of views.
Computer science is more than just writing code. So we will take a brief look on some theoretical concepts and problems which scientists study for decades (and maybe never will solve).
This document summarizes how a basic Rails application works using the example of a Facebook Lite app. The app has models like Post and User, controllers like WelcomeController, views to render the HTML, and a database to store posts. When a request comes in, the Rails router directs it to the appropriate controller action, which gets data from the model and passes it to a view which inserts it into a layout to send the HTML response back to the client.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
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.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
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.
3. def mutation_testing
<<-eos
is used to evaluate the quality of existing software tests
modifying the program's source code
based on well-defined mutation operators
each 'mutated' version is called a mutant
a test which detects the mutation (fail) will kill the mutant
mutants without failing tests are alive
eos
end
4. def mutation_testing
<<-eos
is used to evaluate the quality of existing software tests
modifying the program's source code
based on well-defined mutation operators
each 'mutated' version is called a mutant
a test which detects the mutation (fail) will kill the mutant
mutants without failing tests are ALIVE
eos
end
11. require 'spec_helper'
describe 'FancyAlgorithm' do
let(:random_list) { %w[2 1 3 5 6 4 9 8 7] }
let(:sorted_list) { %w[1 2 3 4 5 6 7 8 9] }
context ':sort' do
subject { FancyAlgorithm.new(:sort) }
it { expect(subject.perform(random_list)).to eql(sorted_list) }
end
context ':unsort' do
subject { FancyAlgorithm.new(:unsort) }
it { expect(subject.perform(random_list)).to_not eql(sorted_list) }
end
end
12. class FancyAlgorithm
attr_accessor :strategy
def initialize(strategy)
@strategy = strategy.to_s
end
def perform(list)
self.send("#{strategy}_algorithm!", list)
end
private
def sort_algorithm!(list)
return list if list.size <= 1
0.upto(list.size - 1) do |i|
(list.size - 1).downto(i + 1) do |j|
if list[j] < list[j - 1]
list[j], list[j - 1] = list[j - 1], list[j]
end
end
end
list
end
def unsort_algorithm!(list)
return list.shuffle unless list.empty?
end
end
13. class FancyAlgorithm
attr_accessor :strategy
def initialize(strategy)
@strategy = strategy.to_s
end
def perform(list)
self.send("#{strategy}_algorithm!", list)
end
private
This is obviously
more advanced
than Array#sort.
def sort_algorithm!(list)
return list if list.size <= 1
0.upto(list.size - 1) do |i|
(list.size - 1).downto(i + 1) do |j|
if list[j] < list[j - 1]
list[j], list[j - 1] = list[j - 1], list[j]
end
end
end
list
end
def unsort_algorithm!(list)
return list.shuffle unless list.empty?
end
end
http://bigocheatsheet.com/
http://www.igvita.com/2009/03/26/ruby-algorithms-sorting-trie-heaps/
14. class FancyAlgorithm
attr_accessor :strategy
def initialize(strategy)
@strategy = strategy.to_s
end
def perform(list)
self.send("#{strategy}_algorithm!", list)
end
private
Quiztime:
Which sorting algorithm
is this?
def sort_algorithm!(list)
return list if list.size <= 1
0.upto(list.size - 1) do |i|
(list.size - 1).downto(i + 1) do |j|
if list[j] < list[j - 1]
list[j], list[j - 1] = list[j - 1], list[j]
end
end
end
list
end
def unsort_algorithm!(list)
return list.shuffle unless list.empty?
end
end
http://bigocheatsheet.com/
http://www.igvita.com/2009/03/26/ruby-algorithms-sorting-trie-heaps/
15. class FancyAlgorithm
attr_accessor :strategy
def initialize(strategy)
@strategy = strategy.to_s
end
def perform(list)
self.send("#{strategy}_algorithm!", list)
end
private
Quiztime:
What‘s the average
Big-O complexity of this
sorting algorithm?
def sort_algorithm!(list)
return list if list.size <= 1
0.upto(list.size - 1) do |i|
(list.size - 1).downto(i + 1) do |j|
if list[j] < list[j - 1]
list[j], list[j - 1] = list[j - 1], list[j]
end
end
end
list
end
def unsort_algorithm!(list)
return list.shuffle unless list.empty?
end
end
http://bigocheatsheet.com/
http://www.igvita.com/2009/03/26/ruby-algorithms-sorting-trie-heaps/
16. class FancyAlgorithm
attr_accessor :strategy
def initialize(strategy)
@strategy = strategy.to_s
end
def perform(list)
self.send("#{strategy}_algorithm!", list)
end
private
Quiztime:
What‘s the sorting
algorithm behind Ruby‘s
Array#sort?
def sort_algorithm!(list)
return list if list.size <= 1
0.upto(list.size - 1) do |i|
(list.size - 1).downto(i + 1) do |j|
if list[j] < list[j - 1]
list[j], list[j - 1] = list[j - 1], list[j]
end
end
end
list
end
def unsort_algorithm!(list)
return list.shuffle unless list.empty?
end
end
http://bigocheatsheet.com/
http://www.igvita.com/2009/03/26/ruby-algorithms-sorting-trie-heaps/
17.
18. $ mutant --help
usage: mutant STRATEGY [options] MATCHERS ...
Strategies:
--rspec
--rspec-level LEVEL
--ignore-subject MATCHER
--zombie
-I, --include DIRECTORY
-r, --require NAME
Options:
--version
--code FILTER
--fail-fast
-d, --debug
-h, --help
kills mutations with rspec
set rspec expansion level
ignores subjects that matches MATCHER
Run mutant zombified
Add DIRECTORY to $LOAD_PATH
Require file with NAME
Print mutants version
Adds a code filter
Fail fast
Enable debugging output
Show this message
43. -
Try it by yourself
clone the repo
play around
write specs to kill the mutants
run mutant in other projects
create issues
help improve the documentation
mutate all the things
44. example project (including this slides):
https://github.com/DonSchado/colognerb-on-mutant
in addition:
https://github.com/DonSchado/bob-the-mutant
obviously:
https://github.com/mbj/mutant
for reference:
http://slid.es/markusschirp/mutation-testing/
http://solnic.eu/2013/01/23/mutation-testing-with-mutant.html
rails?
https://github.com/mockdeep/mutant-rails