Php 5.4: New Language Features You Will Find UsefulDavid Engel
PHP 5.4 includes several new features including improved UTF8 support, session status functions, binary syntax, number formatting improvements, and support for traits. It also includes enhancements to classes like allowing constructor-less instantiation and calling static methods via strings. Arrays have a new short syntax and functions can now be dereferenced.
A Haskell module is a collection of related functions, types and typeclasses. Modules allow organizing code into namespaces and provide a way to selectively import functionality from other modules. Some key points about modules include:
- Modules manage types and functions into namespaces
- The main module can load other modules
- Modules are imported at the top of a file using import statements
- Functions and types can be selectively imported from a module
- Modules in the same parent folder can be in the same namespace
These are the outline slides that I used for the Pune Clojure Course.
The slides may not be much useful standalone, but I have uploaded them for reference.
This document provides 7 habits for writing more functional Swift code. It discusses avoiding mutability and for-loops in favor of map, filter and reduce functions. It also covers being lazy, currying functions, writing domain-specific languages, and thinking about code in terms of data and functions rather than objects.
XPath is a syntax for selecting parts of an XML document, similar to how an operating system describes paths to files. It allows selecting elements using functions like contains and position, attributes using starts-with, and axes like ancestor and descendant. Smart XPath processing has advantages like easy maintenance, debugging, less documentation time, and saving time and energy over complex absolute paths.
This document discusses streaming and input/output (I/O) actions in Haskell. It explains that I/O actions fetch values from the outside world and can only be handled in an impure environment using the <- operator. Various I/O functions are presented, including reading and writing files lazily using readFile and putStr, as well as getting user input from the command line with getLine.
This Python code loads and preprocesses a CSV dataset using Pandas and Scikit-Learn. It splits the data into training and test sets, scales the features, fits an SVC model with RBF kernel, and performs 10-fold cross-validation and grid search to tune the hyperparameters. Key steps include importing libraries, reading the CSV file, splitting the data, fitting an SVC classifier, applying cross-validation to obtain accuracy scores, and using grid search with 10-fold CV to find the best model parameters.
This document provides an introduction to Python data structures including lists, tuples, sets, and dictionaries. It describes how to define, access, and modify each type of data structure. It also covers file handling, string functions, exceptions, and other Python concepts. The key points are:
- Lists are the most versatile data type and can contain elements of different types. They can be accessed by index, sliced, modified via assignments to slices.
- Tuples are immutable sequences that are useful for grouping related data. They allow packing and unpacking of elements.
- Sets store unique elements and support mathematical operations like union and intersection.
- Dictionaries store mappings of unique keys to values. They allow
An array is a container that holds a fixed number of elements of the same type. An array's length is established at creation and cannot be changed. Each element has an index number starting from 0. The document demonstrates how to declare, initialize, access, and copy array elements in Java. It also discusses multidimensional arrays.
Dictionary in Python is an unordered collection of data values, used to store data values like a map, which unlike other Data Types that hold only single value as an element, Dictionary holds key:value pair. Key value is provided in the dictionary to make it more optimized. Each key-value pair in a Dictionary is separated by a colon :, whereas each key is separated by a ‘comma’.
A Dictionary in Python works similar to the Dictionary in a real world. Keys of a Dictionary must be unique and of immutable data type such as Strings, Integers and tuples, but the key-values can be repeated and be of any type.
The Ring programming language version 1.7 book - Part 35 of 196Mahmoud Samir Fayed
The document contains documentation for the Ring programming language. It describes a Ring class that stores information about objects, including their name, symbol, and position. For each object, it lists these attributes. It also contains descriptions of using self and this to reference attributes and methods from within classes.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
The document discusses various parts of the Python programming language including keywords, variables, operators, data types, and more. It provides examples and explanations of concepts like:
- Keywords are reserved words with specific uses like False, None, True, and, or, etc.
- Variables store values in reserved memory locations and can be of different data types like integers, floats, strings.
- Python supports common operators for arithmetic, comparison, logical, bitwise and other operations.
- Core data types include numbers, strings, lists, tuples, and dictionaries.
- Other concepts covered are indentation, comments, input/output functions, type conversions.
The document discusses different JavaScript data types including:
- HTMLString - A string used to represent DOM elements
- Number - Numeric values including parsing, NaN, Infinity
- Object - All values in JavaScript are objects that can have properties accessed via dot or bracket notation
- Array - Mutable lists that can be accessed and modified with index notation
- PlainObject - Distinct from other object types, a plain object is a collection of key-value pairs identified by jQuery's isPlainObject method
This document summarizes a C# lesson that covers LINQ, generics, attributes, reflection, and the System.Collections.Generic namespace. It begins with an agenda that lists the topics to be covered. It then provides examples and explanations of LINQ queries, generic classes and constraints, commonly used collection classes like List and Dictionary, how to define and apply attributes to classes and properties, how to obtain type information at runtime using reflection, and concludes with a demo of an exporter application.
WHAT IS DICTIONARY IN PYTHON?
HOW TO CREATE A DICTIONARY
INITIALIZE THE DICTIONARY
ACCESSING KEYS AND VALUES FROM A DICTIONARY
LOOPS TO DISPLAY KEYS AND VALUES IN A DICTIONARY
METHODS IN A DICTIONARY
TO WATCH VIDEO OR PDF:
https://computerassignmentsforu.blogspot.com/p/dictinpyxii.html
Developing Applications with MySQL and Java for beginnersSaeid Zebardast
A presentation about Developing Applications with MySQL and Java for beginners. It includes the following topics:
- Requirements
- MySQL Data Definitions
- Java Classes
- MySQL Connector (JDBC)
- Define Methods
- Compile and Run
Python programming: Anonymous functions, String operationsMegha V
The document discusses anonymous or lambda functions in Python. Some key points:
- Lambda functions are anonymous functions defined using the lambda keyword. They can take any number of arguments but return only one expression.
- Lambda functions have limited functionality compared to regular functions as they cannot contain multiple expressions or statements.
- Lambda functions are commonly used along with built-in functions like map(), filter() and reduce() to perform operations on lists.
Scala supports first-class functions that can be passed as arguments to other functions or stored in variables. Functions can be defined as method members or as anonymous function literals. Function literals allow defining unnamed functions inline. Functions in Scala support closures, where functions can close over variables in the enclosing scope. This allows functions to access variables that are not passed in as arguments. The document discusses various ways to define functions in Scala including local functions, function literals, partially applied functions, and repeated parameters.
The document discusses different ways of using arrays and classes in C++. It describes how arrays can be declared as data members within a class. An example class called Student is given that contains integer and character array data members to store student details like roll number, name, and marks in different subjects. The document also discusses declaring arrays of objects by creating an array of Student objects. Nested classes are described as classes declared within other classes, and examples of private and public nested classes are provided. Different types of functions that can be declared within a class are also summarized, including inline, constant, and nested functions.
JavaScript Fundamentals with Angular and LodashBret Little
The purpose of this presentation is also largely to explain some of the fun parts of JavaScript (dynamic function invocation with reflection, dynamic arguments, etc). I don't necessarily encourage putting complex logic throughout your templates with lodash, though there may be times it is appropriate.
Lets talk about lodash and how it can easily be married to Angular. Using a six line filter, I will expose the power of lodash directly within angular templates. This will be an introduction to lodash, angular templates, and we'll talk about scope and reflection within JavaScript.
Machine Learning Game Changer for IT - Maartens LourensOpenCredo
In this talk Senior Consultant Maartens Lourens introduces machine learning in a pragmatic way. He aims to make it easy to understand the basic Machine Learning process involved by leveraging only the essential tools and libraries required.
Other than some generic containers like list, Python in its definition can also handle containers with specified data types. Array can be handled in python by module named “array“. They can be useful when we have to manipulate only a specific data type values.
Performance testing determines how responsive and stable a system is under different workloads. It tests for speed, scalability, stability, and ensures a positive user experience. Types of performance testing include load testing to evaluate behavior under expected loads, and stress testing to find upper capacity limits. Key metrics measured are response time, throughput, and resource utilization. Performance testing involves planning test goals, methodology, implementation, validation of results, and interpreting results. Common tools used for performance testing are JMeter, LoadRunner, and Webload.
- JMeter is an open source load testing tool that can test web applications and other services. It uses virtual users to simulate real user load on a system.
- JMeter tests are prepared by recording HTTP requests using a proxy server. Tests are organized into thread groups and loops to simulate different user behaviors and loads.
- Tests can be made generic by using variables and default values so the same tests can be run against different environments. Assertions are added to validate responses.
- Tests are run in non-GUI mode for load testing and can be distributed across multiple machines for high user loads. Test results are analyzed using aggregated graphs and result trees.
This Python code loads and preprocesses a CSV dataset using Pandas and Scikit-Learn. It splits the data into training and test sets, scales the features, fits an SVC model with RBF kernel, and performs 10-fold cross-validation and grid search to tune the hyperparameters. Key steps include importing libraries, reading the CSV file, splitting the data, fitting an SVC classifier, applying cross-validation to obtain accuracy scores, and using grid search with 10-fold CV to find the best model parameters.
This document provides an introduction to Python data structures including lists, tuples, sets, and dictionaries. It describes how to define, access, and modify each type of data structure. It also covers file handling, string functions, exceptions, and other Python concepts. The key points are:
- Lists are the most versatile data type and can contain elements of different types. They can be accessed by index, sliced, modified via assignments to slices.
- Tuples are immutable sequences that are useful for grouping related data. They allow packing and unpacking of elements.
- Sets store unique elements and support mathematical operations like union and intersection.
- Dictionaries store mappings of unique keys to values. They allow
An array is a container that holds a fixed number of elements of the same type. An array's length is established at creation and cannot be changed. Each element has an index number starting from 0. The document demonstrates how to declare, initialize, access, and copy array elements in Java. It also discusses multidimensional arrays.
Dictionary in Python is an unordered collection of data values, used to store data values like a map, which unlike other Data Types that hold only single value as an element, Dictionary holds key:value pair. Key value is provided in the dictionary to make it more optimized. Each key-value pair in a Dictionary is separated by a colon :, whereas each key is separated by a ‘comma’.
A Dictionary in Python works similar to the Dictionary in a real world. Keys of a Dictionary must be unique and of immutable data type such as Strings, Integers and tuples, but the key-values can be repeated and be of any type.
The Ring programming language version 1.7 book - Part 35 of 196Mahmoud Samir Fayed
The document contains documentation for the Ring programming language. It describes a Ring class that stores information about objects, including their name, symbol, and position. For each object, it lists these attributes. It also contains descriptions of using self and this to reference attributes and methods from within classes.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
The document discusses various parts of the Python programming language including keywords, variables, operators, data types, and more. It provides examples and explanations of concepts like:
- Keywords are reserved words with specific uses like False, None, True, and, or, etc.
- Variables store values in reserved memory locations and can be of different data types like integers, floats, strings.
- Python supports common operators for arithmetic, comparison, logical, bitwise and other operations.
- Core data types include numbers, strings, lists, tuples, and dictionaries.
- Other concepts covered are indentation, comments, input/output functions, type conversions.
The document discusses different JavaScript data types including:
- HTMLString - A string used to represent DOM elements
- Number - Numeric values including parsing, NaN, Infinity
- Object - All values in JavaScript are objects that can have properties accessed via dot or bracket notation
- Array - Mutable lists that can be accessed and modified with index notation
- PlainObject - Distinct from other object types, a plain object is a collection of key-value pairs identified by jQuery's isPlainObject method
This document summarizes a C# lesson that covers LINQ, generics, attributes, reflection, and the System.Collections.Generic namespace. It begins with an agenda that lists the topics to be covered. It then provides examples and explanations of LINQ queries, generic classes and constraints, commonly used collection classes like List and Dictionary, how to define and apply attributes to classes and properties, how to obtain type information at runtime using reflection, and concludes with a demo of an exporter application.
WHAT IS DICTIONARY IN PYTHON?
HOW TO CREATE A DICTIONARY
INITIALIZE THE DICTIONARY
ACCESSING KEYS AND VALUES FROM A DICTIONARY
LOOPS TO DISPLAY KEYS AND VALUES IN A DICTIONARY
METHODS IN A DICTIONARY
TO WATCH VIDEO OR PDF:
https://computerassignmentsforu.blogspot.com/p/dictinpyxii.html
Developing Applications with MySQL and Java for beginnersSaeid Zebardast
A presentation about Developing Applications with MySQL and Java for beginners. It includes the following topics:
- Requirements
- MySQL Data Definitions
- Java Classes
- MySQL Connector (JDBC)
- Define Methods
- Compile and Run
Python programming: Anonymous functions, String operationsMegha V
The document discusses anonymous or lambda functions in Python. Some key points:
- Lambda functions are anonymous functions defined using the lambda keyword. They can take any number of arguments but return only one expression.
- Lambda functions have limited functionality compared to regular functions as they cannot contain multiple expressions or statements.
- Lambda functions are commonly used along with built-in functions like map(), filter() and reduce() to perform operations on lists.
Scala supports first-class functions that can be passed as arguments to other functions or stored in variables. Functions can be defined as method members or as anonymous function literals. Function literals allow defining unnamed functions inline. Functions in Scala support closures, where functions can close over variables in the enclosing scope. This allows functions to access variables that are not passed in as arguments. The document discusses various ways to define functions in Scala including local functions, function literals, partially applied functions, and repeated parameters.
The document discusses different ways of using arrays and classes in C++. It describes how arrays can be declared as data members within a class. An example class called Student is given that contains integer and character array data members to store student details like roll number, name, and marks in different subjects. The document also discusses declaring arrays of objects by creating an array of Student objects. Nested classes are described as classes declared within other classes, and examples of private and public nested classes are provided. Different types of functions that can be declared within a class are also summarized, including inline, constant, and nested functions.
JavaScript Fundamentals with Angular and LodashBret Little
The purpose of this presentation is also largely to explain some of the fun parts of JavaScript (dynamic function invocation with reflection, dynamic arguments, etc). I don't necessarily encourage putting complex logic throughout your templates with lodash, though there may be times it is appropriate.
Lets talk about lodash and how it can easily be married to Angular. Using a six line filter, I will expose the power of lodash directly within angular templates. This will be an introduction to lodash, angular templates, and we'll talk about scope and reflection within JavaScript.
Machine Learning Game Changer for IT - Maartens LourensOpenCredo
In this talk Senior Consultant Maartens Lourens introduces machine learning in a pragmatic way. He aims to make it easy to understand the basic Machine Learning process involved by leveraging only the essential tools and libraries required.
Other than some generic containers like list, Python in its definition can also handle containers with specified data types. Array can be handled in python by module named “array“. They can be useful when we have to manipulate only a specific data type values.
Performance testing determines how responsive and stable a system is under different workloads. It tests for speed, scalability, stability, and ensures a positive user experience. Types of performance testing include load testing to evaluate behavior under expected loads, and stress testing to find upper capacity limits. Key metrics measured are response time, throughput, and resource utilization. Performance testing involves planning test goals, methodology, implementation, validation of results, and interpreting results. Common tools used for performance testing are JMeter, LoadRunner, and Webload.
- JMeter is an open source load testing tool that can test web applications and other services. It uses virtual users to simulate real user load on a system.
- JMeter tests are prepared by recording HTTP requests using a proxy server. Tests are organized into thread groups and loops to simulate different user behaviors and loads.
- Tests can be made generic by using variables and default values so the same tests can be run against different environments. Assertions are added to validate responses.
- Tests are run in non-GUI mode for load testing and can be distributed across multiple machines for high user loads. Test results are analyzed using aggregated graphs and result trees.
This presentation explains about Beanshell scripting in Apache JMeter. This presentation walkthroughs with examples and sample code to understand the concept better.
Rational Performance Tester is a tool that identifies system performance bottlenecks. It simplifies test creation, load generation, and data collection to help ensure applications can accommodate required user loads. Scripting involves recording user actions and inserting transaction points. Tests are then executed according to schedules that can run scripts across multiple remote machines in parallel to simulate different user loads.
TDM: Masking, Subsetting and generating Synthetic Data CA Technologies
This document outlines an agenda and objectives for a hands-on lab demonstrating CA Technologies' Test Data Manager solution. The lab will guide participants through activities to experience provisioning secure test environments using data subsetting, masking, and synthetic data generation techniques. Specifically, the lab consists of three parts: a subsetting lab to reduce production data size, a masking lab to anonymize sensitive data fields, and a data generation lab to enhance test data quality.
This document provides an overview of Apache JMeter, an open source load testing tool. It discusses JMeter's features such as supporting various protocols like HTTP, databases via JDBC, and messaging. The document also covers how to install and use JMeter, including creating simple test plans, and its distributed testing architecture. Hands-on labs are included to build basic JMeter tests.
Performance testing with JMeter provides an introduction to key concepts and how to implement performance tests using JMeter. Some important steps include designing test plans, preparing the environment, determining metrics and goals, notifying stakeholders, and using JMeter elements like thread groups, samplers, listeners, assertions and configuration elements to simulate load and measure performance. JMeter is an open source tool that can run in GUI or non-GUI mode for load testing web applications and determining maximum operating capacity and bottlenecks under heavy loads.
Most developers will be familiar with lex, flex, yacc, bison, ANTLR, and other tools to generate parsers for use inside their own code. Erlang, the concurrent functional programming language, has its own pair, leex and yecc, for accomplishing most complicated text-processing tasks. This talk is about how the seemingly simple prospect of parsing text turned into a new parser toolkit for Erlang, and why functional programming makes parsing fun and awesome.
The document provides an agenda for a two-day Perl training course. Day 1 will cover Perl fundamentals like scalars, arrays, hashes, subroutines, modules, and advanced data structures. Day 2 will focus on bioinformatics with Bioperl, including finding modules and methods, sequence processing, and visualization. The document outlines topics like variables, lists, functions, operators, and using the perldoc system for documentation.
A teaser talk for Scala newbies, introducing five basic elements that (in my opinion) make the transition from Java to Scala a no-brainer.
Given at the 7th JJTV (Israeli Java/JVM user group) tool night, July 2nd, 2013.
Lisp Macros in 20 Minutes (Featuring Clojure)Phil Calçado
"We just started holding 20 minutes presentations during lunch time in the ThoughtWorks Sydney office. For the first session I gave a not-that-short talk on Lisp macros using Clojure. The slides are below.
It turns out that 20 minutes is too little time to actually acquire content but I think at least we now have some people interested in how metaprogramming can be more than monkey patching."
http://fragmental.tw/2009/01/20/presentation-slides-macros-in-20-minutes/
1) The document discusses XPath, an XML query language used to select nodes from an XML document. It provides examples of how XPath can be used to query nodes based on attributes, children, and other properties.
2) The document then discusses how XPath injection could allow an attacker to bypass authentication, bypass business logic, or extract arbitrary data from an XML database if user input is not sanitized in XPath queries.
3) Useful XPath functions like count, name, substring are demonstrated that could help an attacker crawl through and extract information from an XML structure. True/false-based blind XPath injection techniques are also presented.
Creating Domain Specific Languages in PythonSiddhi
This document discusses domain specific languages (DSLs) and provides examples of creating DSLs in Python. It explains that DSLs allow users to work in specialized mini-languages tailored to specific problem domains. As examples, it discusses SQL as a DSL for databases and regular expressions as a DSL for patterns. It then demonstrates how to create an external DSL for defining forms using PyParsing and an internal DSL for the same using Python features like metaclasses. The document concludes that DSLs make code easier to read, write and maintain for non-programmers.
Solr provides concise summaries of key points from the document:
1. Solr discusses its search architecture including the use of Thrift for service encapsulation and reduced network traffic. Only IDs are returned from searches to reduce index size and enable easy scaling of primary key lookups.
2. Load balancing is discussed, including an algorithm that hashes the query and number of servers to provide server affinity while distributing load evenly.
3. Replication of the index is covered, including challenges with multicast and an implementation using BitTorrent to efficiently replicate files.
2 BytesC++ course_2014_c7_ operator overloading, friends and references kinan keshkeh
The document discusses different ways of overloading operators in C++ classes. It explains how to overload operators as standalone functions or member functions. It provides examples of overloading the +, -, >>, <<, ++, -- and [] operators. It also discusses how to define the >> and << operators as friend functions to allow input and output of class objects through cout and cin.
This document provides a summary of Jacek Laskowski as the main sponsor of a Clojure conference. It lists his background and experience including being a functional apprentice of Clojure, founder and co-leader of a JUG, conference organizer, member of Apache Software Foundation and IBM. It also lists his blog and Twitter accounts.
Many developers will be familiar with lex, flex, yacc, bison, ANTLR, and other related tools to generate parsers for use inside their own code. For recognizing computer-friendly languages, however, context-free grammars and their parser-generators leave a few things to be desired. This is about how the seemingly simple prospect of parsing some text turned into a new parser toolkit for Erlang, and why functional programming makes parsing fun and awesome
This document provides an overview of DataMapper, an object-relational mapper (ORM) library for Ruby applications. It summarizes DataMapper's main features such as associations, migrations, database adapters, naming conventions, validations, custom types and stores. The document also provides examples of how to use DataMapper with different databases, import/export data, and validate models for specific contexts.
This document discusses Clojure macros, including how they differ from functions in that arguments passed to macros are not evaluated. It provides examples of defining simple macros and discusses common issues like symbol capture. The key aspects covered are the macroexpansion process, using syntax quoting to return code, and when macros are generally useful like for syntactic sugar or preventing argument evaluation.
This document provides an overview of functional programming patterns and abstractions in Java 8. It introduces common functional concepts like functors, applicative functors, monads, and type classes. It then describes implementations of these concepts for option, either, stream, future, and completable future in Java. The document explains how functional patterns allow for simpler composition and avoidance of null checks compared to imperative programming with conditionals.
Perl6 regular expression ("regex") syntax has a number of improvements over the Perl5 syntax. The inclusion of grammars as first-class entities in the language makes many uses of regexes clearer, simpler, and more maintainable. This talk looks at a few improvements in the regex syntax and also at how grammars can help make regex use cleaner and simpler.
Functional Programming in Javascript - IL Tech Talks weekyoavrubin
The document discusses a presentation about functional programming in JavaScript. It will cover inner functions and closures, higher order functions, and decomplecting calls patterns. It will discuss how these functional programming concepts can improve performance, provide different perspectives on objects, avoid array mistakes, and allow for recursion. The presentation will provide an overview of functional programming and JavaScript, and then do a deep dive into combining the two paradigms.
Using Groovy is easy and fun. After getting your hands dirty with a few basics it is good to go deeper. In this session we will cover Design Patterns in Groovy, mixing Java and Groovy, Metaprogramming, and using CodeNarc. So get ready to take it to the next level.
Attributes Unwrapped: Lessons under the surface of active record.toster
Ведущий разработчик Ruby on Rails (Rails Core member) Джон Лейтон не так давно работал над совершенствованием реализации работы с атрибутами в Active Record. Он расскажет о своем опыте работы над важной для производительности областью Rails, даст советы и расскажет о техниках, которые могут быть применены к собственным приложениям слушателей.
Говоря о будущем, Джон также расскажет о своих идеях по изменению API работы с атрибутами в лучшую сторону; эти изменения могут появиться в Rails 4.0.
Scala er et Java-relateret, statisk typet programmeringssprog i hastig fremmarch. Sproget kombinerer aspekter fra objekt- og funktionsorienterede sprog og fokuserer på skalerbarhed og effektivitet, både på det kodemæssige og afviklingsmæssige niveau. Syntaksen er elegant og koncis. Samtidig indeholder sproget stærke konstruktioner til understøttelse af parallelle applikationer, der udnytter fremtidens hardwarearkitekturer.
This document provides an overview of Linux shell scripting concepts including:
- Using Vagrant to create and manage virtual machines for testing shell scripts
- The basics of shell script syntax like naming, permissions, comments and variables
- Common shell commands like echo, read, if/then conditional statements, loops and positional parameters
- Redirection of standard input/output and pipes to connect commands
- Basic text processing tools like cut, sort, uniq and awk
- Functions and case statements for reusability and conditional logic
The document discusses the ResultSet interface in Java. It provides details on:
1) ResultSet objects represent query results from a database and implement the ResultSet interface. They can be scrollable or non-scrollable.
2) Non-scrollable result sets only allow sequential forward access to records while scrollable result sets allow random, bidirectional access.
3) The ResultSet interface defines methods like getString(), getInt() and getDouble() to retrieve column values from the current row.
The document provides an overview of quality assurance and testing practices for agile projects. It discusses traditional and agile testing approaches, defines roles like testers and developers in agile teams, and outlines a test strategy including test planning, automation, and metrics. Key aspects of agile testing covered are testing throughout each sprint, the importance of collaboration, and ensuring quality is "baked in" through a whole team approach.
Software QA and testing involves processes to ensure quality, compliance with standards, and identification of defects. It verifies and validates that software meets requirements through techniques like boundary testing and risk analysis. Testing is needed to prevent release of poor quality products, address different devices and browsers, and uncover issues before many users are affected. It is done through various approaches like traditional testing, agile testing in iterations, and different levels from unit to user acceptance. Specialized testing services include performance, security, usability, and test automation testing. Testers require both testing knowledge of principles and techniques as well as technical, domain, and soft skills.
This document provides an introduction to JMeter, an open source performance testing tool. It discusses what JMeter is used for, its key features, components, strengths and weaknesses. It also provides instructions on setting up and running JMeter, including building a test plan with thread groups, samplers, listeners and other elements. The document demonstrates how to perform tasks like parameterization, session handling, and distributed testing with JMeter.
Coded UI is a User Interface (UI) Test Automation Tool that comes with Microsoft Visual Studio which can be used to automate our manual, repetitive and regression tests thereby increase productivity of Testing teams.
This document discusses performance testing for service oriented architectures (SOA) and enterprise middleware. It covers typical server performance patterns like latency and throughput. It recommends establishing a clustered test environment that mirrors production. Open source tools for performance testing SOA are discussed, including Apache JMeter for load testing and soapUI for functional tests. The document also covers monitoring tools for analyzing performance.
The document provides an introduction and overview of performance testing. It discusses what performance testing, tuning, and engineering are and why they are important. It outlines the typical performance test cycle and common types of performance tests. Finally, it discusses some myths about performance testing and gives an overview of common performance testing tools and architectures.
7. Reg Ex
• ( ) - grouping
• [ ] - character classes
• { } - repetition
• * + ? - repetition
• . - wild-card character
• - escape character
• | - alternatives
• ^ $ - start and end of string or line
8. Functions
• __log()
• __threadNum()- The thread number function simply returns the number of the thread currently being
executed
${__log(${__threadNum},,,******Thread_Number is*********:: )}
9. • __machineName()
The machineName function returns the local host name