Basic introduction to pure functions using Javascript as the language. Introduction to some concepts as side effects, referential transparency and shared state.
This document discusses callback functions in JavaScript. A callback function is a function passed into another function as an argument, which is then invoked inside the outer function to complete some kind of routine or action. Callback functions allow asynchronous code execution in JavaScript by performing tasks without blocking subsequent code from running. Common examples of callbacks include functions used in event handling and asynchronous operations like AJAX requests.
Asynchronous JavaScript Programming with Callbacks & PromisesHùng Nguyễn Huy
This presentation is about JavaScript Promise. Topics covered in this session are:
1. Asynchronous processing in JavaScript
2. Callbacks and Callback hell
3. Promises arrive in JavaScript!
4. Constructing a Promise
5. Promise states
6. Promises chaining and transformation
7. Error handling
8. Promise.all() and Promise.race()
This document provides an introduction to Flux, describing it as an architecture pattern for one-way data binding that is framework agnostic. It explains the key components of Flux including Stores, Actions, Dispatcher, Smart Components, and Dumb Components. Stores contain the application state, Actions are used to invoke state changes by passing arguments to the Dispatcher, and there is only one Dispatcher. Smart Components are aware of the Store and listen for changes, while Dumb Components only display data passed in via props. Examples of when to use Flux include for single page apps and complex UIs, while simpler components or static sites may not need it. Redux is recommended as a common Flux implementation.
Erlang is a programming language designed for writing concurrent programs that run forever. It has a great concurrency model, is network transparent, fault tolerant, and allows replacing running code. Erlang uses processes, immutable variables, recursion, pattern matching, and functional programming. It has built-in support for concurrency through lightweight processes that communicate via message passing. The language philosophy is to "let it crash" and handle errors through recovery in other processes rather than defensive programming.
The document discusses transaction propagation and isolation levels in Spring. It describes the different propagation behaviors like REQUIRED, REQUIRES_NEW, and NESTED that control how transactions are created or joined. It also covers isolation levels like READ_UNCOMMITTED, READ_COMMITTED, REPEATABLE_READ, and SERIALIZABLE that control the visibility of uncommitted data between transactions and prevent different types of anomalies like dirty reads, non-repeatable reads, and phantom reads.
The document provides an introduction to asynchronous JavaScript. It discusses callbacks and their disadvantages like callback hell. Promises are introduced as a better way to handle asynchronous code by making it easier to write and chain asynchronous operations. Async/await is described as syntactic sugar that allows asynchronous code to be written more readably in a synchronous style using await and try/catch. Key aspects like the event loop, microtask queue, and Promise methods like all and race are explained. Overall the document aims to help understand what makes asynchronous code different and newer methods like promises and async/await that improve handling asynchronous operations in JavaScript.
Functional programming concepts like purity, immutability, and side effects can seem intimidating at first. However, they aim to make code more predictable by avoiding state mutations and ensuring the same output is always produced from the same inputs. Key concepts discussed include pure functions that are free of side effects; immutable objects whose state cannot change; partial application of fixing arguments; and currying of transforming functions to chains of functions that each take a single argument to enable easier composition of simple functions into more complex ones. Resources recommended for learning more include functional programming books and libraries like Ramda, RxJS, and Immutable.js.
This document discusses callback functions in JavaScript. A callback function is a function passed into another function as an argument, which is then invoked inside the outer function to complete some kind of routine or action. Callback functions allow asynchronous code execution in JavaScript by performing tasks without blocking subsequent code from running. Common examples of callbacks include functions used in event handling and asynchronous operations like AJAX requests.
Asynchronous JavaScript Programming with Callbacks & PromisesHùng Nguyễn Huy
This presentation is about JavaScript Promise. Topics covered in this session are:
1. Asynchronous processing in JavaScript
2. Callbacks and Callback hell
3. Promises arrive in JavaScript!
4. Constructing a Promise
5. Promise states
6. Promises chaining and transformation
7. Error handling
8. Promise.all() and Promise.race()
This document provides an introduction to Flux, describing it as an architecture pattern for one-way data binding that is framework agnostic. It explains the key components of Flux including Stores, Actions, Dispatcher, Smart Components, and Dumb Components. Stores contain the application state, Actions are used to invoke state changes by passing arguments to the Dispatcher, and there is only one Dispatcher. Smart Components are aware of the Store and listen for changes, while Dumb Components only display data passed in via props. Examples of when to use Flux include for single page apps and complex UIs, while simpler components or static sites may not need it. Redux is recommended as a common Flux implementation.
Erlang is a programming language designed for writing concurrent programs that run forever. It has a great concurrency model, is network transparent, fault tolerant, and allows replacing running code. Erlang uses processes, immutable variables, recursion, pattern matching, and functional programming. It has built-in support for concurrency through lightweight processes that communicate via message passing. The language philosophy is to "let it crash" and handle errors through recovery in other processes rather than defensive programming.
The document discusses transaction propagation and isolation levels in Spring. It describes the different propagation behaviors like REQUIRED, REQUIRES_NEW, and NESTED that control how transactions are created or joined. It also covers isolation levels like READ_UNCOMMITTED, READ_COMMITTED, REPEATABLE_READ, and SERIALIZABLE that control the visibility of uncommitted data between transactions and prevent different types of anomalies like dirty reads, non-repeatable reads, and phantom reads.
The document provides an introduction to asynchronous JavaScript. It discusses callbacks and their disadvantages like callback hell. Promises are introduced as a better way to handle asynchronous code by making it easier to write and chain asynchronous operations. Async/await is described as syntactic sugar that allows asynchronous code to be written more readably in a synchronous style using await and try/catch. Key aspects like the event loop, microtask queue, and Promise methods like all and race are explained. Overall the document aims to help understand what makes asynchronous code different and newer methods like promises and async/await that improve handling asynchronous operations in JavaScript.
Functional programming concepts like purity, immutability, and side effects can seem intimidating at first. However, they aim to make code more predictable by avoiding state mutations and ensuring the same output is always produced from the same inputs. Key concepts discussed include pure functions that are free of side effects; immutable objects whose state cannot change; partial application of fixing arguments; and currying of transforming functions to chains of functions that each take a single argument to enable easier composition of simple functions into more complex ones. Resources recommended for learning more include functional programming books and libraries like Ramda, RxJS, and Immutable.js.
The Perks and Perils of the Singleton Design PatternBADR
Singleton design pattern is on the most famous and used design patterns. It's also a source of endless debates between software engineers! In this session, we discuss the perks and perils of the singleton design patters.
This document recaps topics covered in Week 1 of a coding initiative, including functions, modules, boolean expressions, relational operators, and conditional statements in Python. It provides examples and explanations of each topic, such as how functions have a header, body and can take parameters; how to import and use modules; how boolean expressions work with logical operators; and how to write conditional statements using if/elif/else.
This document discusses behavioral modeling in Verilog using procedures. It covers:
1. Procedures are sections of code intended for a specific task and execute sequentially like hardware blocks.
2. Modules can contain multiple procedures that execute concurrently. Everything in behavioral modeling uses procedural blocks.
3. Procedural blocks can use "initial" blocks that execute once at time zero or "always" blocks that execute forever during simulation. Initial blocks are for test benches while always blocks model hardware.
The document discusses different programming paradigms including imperative, object-oriented, functional, protocol-oriented, and functional reactive programming. It provides examples of code using each paradigm and how to recognize them. It notes that the paradigms often mix together and provides some additional resources on concepts like monads, signals, and bridging between paradigms in Swift.
The document provides an agenda and overview of RxSwift, a library for reactive and asynchronous programming. It discusses key RxSwift concepts like Observables, operators, and subjects. It also covers how to install and use RxSwift, including examples of creating Observables, transforming and filtering data with operators, and using Schedulers. The document emphasizes how RxSwift simplifies asynchronous tasks in UI programming by allowing code to react to new data in a sequential, isolated manner.
From Imperative to Functional Programming (for Absolute Beginners)Alex Bunardzic
This document discusses the history and differences between imperative and functional programming paradigms. It explains that functional programming uses immutable data and pure functions without side effects, making programs more reliable and easier to test. Some benefits of the functional approach include improved performance, easier debugging, and the ability to safely deploy updates by simply replacing code. The document provides examples and guidelines for transitioning from imperative to functional programming.
The document discusses best practices for writing clean JavaScript code, including avoiding global variables, properly encapsulating variables, and batching DOM operations for performance. It emphasizes using strict comparisons, templating frameworks to help avoid common pitfalls, and following principles like KISS and SRP. Overall it stresses the importance of coding discipline, iterative development, and expressing code in an unambiguous way to facilitate collaboration.
Robert C. Martin is a software engineer since 1970 who has edited and written several books. He co-authored the Agile Manifesto. The book Clean Code discusses principles of clean code such as functions doing one thing, avoiding duplications, and refactoring code in small steps. Tests are important to keep code flexible and readable by being fast, independent, repeatable, self-validating, and timely. Writing clean code is a craft that requires writing dirty code first and then cleaning it.
This document discusses functional programming concepts in JavaScript including:
- Pure functions that always return the same output for a given input without side effects. This makes functions more reliable and testable.
- Composition, which combines simple functions to build more complex ones by passing the result of each function to the next. This makes code more readable.
- Immutability, where data cannot be changed once created. New data is created instead of mutating existing data, improving performance.
- The document provides examples and explanations of these functional programming concepts and principles in JavaScript to illustrate how to start writing code in a more functional style.
Functions are reusable blocks of code that can be called to perform tasks. There are two ways to define a function: with a statement or expression. Functions may accept parameters and return values. Variables declared inside a function have local scope, while parameters and the this keyword can refer to different objects depending on the context. Functions allow code to be reused and are fundamental to JavaScript programming.
This is a simple presentation with a set of exercises to introduce some React key concepts. The concepts your are going to learn are:
Props, State, React Component, React Instance, React Element
You are also going to practise unit testing with React using:Mocha, Chai, Sinon, Enzyme, Jsdom, React Test Utilities
The document discusses functional programming concepts like pure functions, higher order functions, and referential transparency. Pure functions are those whose return value depends only on their input values, without any observable side effects. Higher order functions are functions that take other functions as arguments or return functions. Referential transparency means a function call can be replaced by its return value without changing the program's behavior. The document argues that functional programming benefits include easier debugging, simpler and cleaner code, and increased reusability. While not all programs can be purely functional, its principles can still be applied.
Maybe developer testing is more trouble than it's worth. Teams have found writing tests to be a hinderance. Then they reduce testing in order to deliver "faster". They feel that tests actually make changing the code and fixing bugs harder. They might be right.
see also: https://www.linkedin.com/pulse/testing-cable-chain-mark-windholtz/
Working Effectively with Legacy Code: Lessons in PracticeAmar Shah
Code rots. Even the best designs can fall into chaos, weighed down by changing requirements, hard-coded dependencies, and overzealous cut-and-paste. Eventually, the mess has to be cleaned up, but there's just one problem: There are no tests. No one knows exactly what the code is supposed to do. You will think you're fixing it, but instead you'll break it--and you won't even know.
A few months ago, I inherited just such a mess. In this talk, I'll explore Michael Feathers' classic Working Effectively with Legacy Code, a comprehensive and accessible guide to refactoring the even the ugliest, most neglected code bases. Using real examples, I'll explain how Feathers' techniques are working for me.
Deterministic behaviour and performance in trading systemsPeter Lawrey
Peter Lawrey gave a presentation on deterministic behavior and performance in trading. Some key points:
- Using lambda functions and state machines can help make systems more deterministic and easy to reason about.
- Recording all inputs and outputs allows systems to be replayed and upgraded deterministically. This supports testing.
- Little's Law relates throughput, latency, and number of workers. For trading systems, reducing latency increases throughput.
- Avoiding "coordinated omission" is important for accurate latency testing.
- In Java 8, escape analysis and inlining can avoid object creation with lambdas, improving performance.
- Systems using Chronicle Queue can achieve low 25 microsecond latency while ensuring data is
Building React Applications with Redux
with Yuri Takhteyev
OVERVIEW
Since React is just a “view framework”, it leaves you with lots of options for how to architect the deeper parts of your stack. The best way to handle those deeper layers is by using Redux – a state container that allows you to write much of your application in the form of pure functions. Using Redux helps you write applications that are much easier to test and understand and to achieve more thorough separation between your views and your business logic. Redux also unlocks the possibility of using amazing tools.
OBJECTIVE
Introduce the audience to Redux, a state container that can be used together with React to achieve sanity deeper down in your stack.
TARGET AUDIENCE
Developers familiar with core React and looking for a better way to architect their applications.
ASSUMED AUDIENCE KNOWLEDGE
Core React knowledge is assumed. Familiarity with basic Flux concepts would help, but I’ll review those quickly.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
Why pure functions make your code easier to maintain.
How unidirectional data flows help you sleep better at night.
How Redux helps you manage state better via reducers.
How to use Redux together with React.
How to test Redux applications.
This document summarizes Martin Odersky's talk on implicits in Scala. The key points are:
1. Implicits allow certain values or functions to be passed implicitly rather than explicitly as parameters. This can avoid tedious repetition when many parameters rarely change.
2. Implicits are commonly used to establish context, inject dependencies, implement type classes, and prove theorems by modeling types as theorems and programs as proofs.
3. Future changes to implicits in Scala 3 include allowing multiple implicit parameter lists, implicit by-name parameters, and implicit function types which avoid wrapping implicits in monads.
Talk given by Michael Damkot, Principal Network Engineer at Salesforce, at Interop in May 2016
A variety of efforts are underway to bring more programmability and automation to network management. These efforts are important because traditional methods can’t match the speed or scale required by modern applications and services, both in the data center and the cloud.
One mechanism to drive the evolution to a truly programmatic network is declarative network configuration, in which the expected state of the network is maintained in a configuration repository. Software is then used to instantiate the desired state on network devices.
Such software helps engineers and administrators provision network services more quickly, build more reliable networks, and shift their time and resources away from tedious configuration tasks to tackle more interesting challenges.
This talk aims to help you re-think how the network is managed. I’ll offer tips from my experience with declarative network configuration and its effectiveness in the real world, and describe tools I’ve leveraged in the pursuit of a truly automated and framework, including Ansible and Puppet.
How Functional Programming Made Me a Better DeveloperCameron Presley
With the rise in popularity recently, functional programming has become ""The Next Big Thing"". As of today, there are tons of frameworks and tools that can be used for front-end, back-end, desktop, and mobile development. With that being said, the majority of us are still using object-oriented languages for our day jobs and don't need to learn functional programming, right?
In this talk, I'll walk you through my experiences learning functional programming over the last year, how my style of programming has changed, and how I now think about programming with regards to both functional and object-oriented paradigms.
Better Page Object Handling with Loadable Component Pattern - SQA Days 20, Be...Sargis Sargsyan
One of the painful problems in Selenium automated testing is determining whether a HTML page has been loaded. This is especially the case when web application uses a JS heavy framework such as the popular AngularJS.
How to handle Selenium Page Object pattern better with Loadable Component.
The Loadable Component helps test case developers make sure that the page or a component of the page is loaded successfully. I will share my experience about the concept of the Loadable Component and Page Object patterns.
Generating unit tests based on user logsRick Wicker
Developing without automated testing is hard and risky. Making legacy code testable is hard. Try to improve your logging, add a data layer and see if you can drive testing from user behavior.
The Perks and Perils of the Singleton Design PatternBADR
Singleton design pattern is on the most famous and used design patterns. It's also a source of endless debates between software engineers! In this session, we discuss the perks and perils of the singleton design patters.
This document recaps topics covered in Week 1 of a coding initiative, including functions, modules, boolean expressions, relational operators, and conditional statements in Python. It provides examples and explanations of each topic, such as how functions have a header, body and can take parameters; how to import and use modules; how boolean expressions work with logical operators; and how to write conditional statements using if/elif/else.
This document discusses behavioral modeling in Verilog using procedures. It covers:
1. Procedures are sections of code intended for a specific task and execute sequentially like hardware blocks.
2. Modules can contain multiple procedures that execute concurrently. Everything in behavioral modeling uses procedural blocks.
3. Procedural blocks can use "initial" blocks that execute once at time zero or "always" blocks that execute forever during simulation. Initial blocks are for test benches while always blocks model hardware.
The document discusses different programming paradigms including imperative, object-oriented, functional, protocol-oriented, and functional reactive programming. It provides examples of code using each paradigm and how to recognize them. It notes that the paradigms often mix together and provides some additional resources on concepts like monads, signals, and bridging between paradigms in Swift.
The document provides an agenda and overview of RxSwift, a library for reactive and asynchronous programming. It discusses key RxSwift concepts like Observables, operators, and subjects. It also covers how to install and use RxSwift, including examples of creating Observables, transforming and filtering data with operators, and using Schedulers. The document emphasizes how RxSwift simplifies asynchronous tasks in UI programming by allowing code to react to new data in a sequential, isolated manner.
From Imperative to Functional Programming (for Absolute Beginners)Alex Bunardzic
This document discusses the history and differences between imperative and functional programming paradigms. It explains that functional programming uses immutable data and pure functions without side effects, making programs more reliable and easier to test. Some benefits of the functional approach include improved performance, easier debugging, and the ability to safely deploy updates by simply replacing code. The document provides examples and guidelines for transitioning from imperative to functional programming.
The document discusses best practices for writing clean JavaScript code, including avoiding global variables, properly encapsulating variables, and batching DOM operations for performance. It emphasizes using strict comparisons, templating frameworks to help avoid common pitfalls, and following principles like KISS and SRP. Overall it stresses the importance of coding discipline, iterative development, and expressing code in an unambiguous way to facilitate collaboration.
Robert C. Martin is a software engineer since 1970 who has edited and written several books. He co-authored the Agile Manifesto. The book Clean Code discusses principles of clean code such as functions doing one thing, avoiding duplications, and refactoring code in small steps. Tests are important to keep code flexible and readable by being fast, independent, repeatable, self-validating, and timely. Writing clean code is a craft that requires writing dirty code first and then cleaning it.
This document discusses functional programming concepts in JavaScript including:
- Pure functions that always return the same output for a given input without side effects. This makes functions more reliable and testable.
- Composition, which combines simple functions to build more complex ones by passing the result of each function to the next. This makes code more readable.
- Immutability, where data cannot be changed once created. New data is created instead of mutating existing data, improving performance.
- The document provides examples and explanations of these functional programming concepts and principles in JavaScript to illustrate how to start writing code in a more functional style.
Functions are reusable blocks of code that can be called to perform tasks. There are two ways to define a function: with a statement or expression. Functions may accept parameters and return values. Variables declared inside a function have local scope, while parameters and the this keyword can refer to different objects depending on the context. Functions allow code to be reused and are fundamental to JavaScript programming.
This is a simple presentation with a set of exercises to introduce some React key concepts. The concepts your are going to learn are:
Props, State, React Component, React Instance, React Element
You are also going to practise unit testing with React using:Mocha, Chai, Sinon, Enzyme, Jsdom, React Test Utilities
The document discusses functional programming concepts like pure functions, higher order functions, and referential transparency. Pure functions are those whose return value depends only on their input values, without any observable side effects. Higher order functions are functions that take other functions as arguments or return functions. Referential transparency means a function call can be replaced by its return value without changing the program's behavior. The document argues that functional programming benefits include easier debugging, simpler and cleaner code, and increased reusability. While not all programs can be purely functional, its principles can still be applied.
Maybe developer testing is more trouble than it's worth. Teams have found writing tests to be a hinderance. Then they reduce testing in order to deliver "faster". They feel that tests actually make changing the code and fixing bugs harder. They might be right.
see also: https://www.linkedin.com/pulse/testing-cable-chain-mark-windholtz/
Working Effectively with Legacy Code: Lessons in PracticeAmar Shah
Code rots. Even the best designs can fall into chaos, weighed down by changing requirements, hard-coded dependencies, and overzealous cut-and-paste. Eventually, the mess has to be cleaned up, but there's just one problem: There are no tests. No one knows exactly what the code is supposed to do. You will think you're fixing it, but instead you'll break it--and you won't even know.
A few months ago, I inherited just such a mess. In this talk, I'll explore Michael Feathers' classic Working Effectively with Legacy Code, a comprehensive and accessible guide to refactoring the even the ugliest, most neglected code bases. Using real examples, I'll explain how Feathers' techniques are working for me.
Deterministic behaviour and performance in trading systemsPeter Lawrey
Peter Lawrey gave a presentation on deterministic behavior and performance in trading. Some key points:
- Using lambda functions and state machines can help make systems more deterministic and easy to reason about.
- Recording all inputs and outputs allows systems to be replayed and upgraded deterministically. This supports testing.
- Little's Law relates throughput, latency, and number of workers. For trading systems, reducing latency increases throughput.
- Avoiding "coordinated omission" is important for accurate latency testing.
- In Java 8, escape analysis and inlining can avoid object creation with lambdas, improving performance.
- Systems using Chronicle Queue can achieve low 25 microsecond latency while ensuring data is
Building React Applications with Redux
with Yuri Takhteyev
OVERVIEW
Since React is just a “view framework”, it leaves you with lots of options for how to architect the deeper parts of your stack. The best way to handle those deeper layers is by using Redux – a state container that allows you to write much of your application in the form of pure functions. Using Redux helps you write applications that are much easier to test and understand and to achieve more thorough separation between your views and your business logic. Redux also unlocks the possibility of using amazing tools.
OBJECTIVE
Introduce the audience to Redux, a state container that can be used together with React to achieve sanity deeper down in your stack.
TARGET AUDIENCE
Developers familiar with core React and looking for a better way to architect their applications.
ASSUMED AUDIENCE KNOWLEDGE
Core React knowledge is assumed. Familiarity with basic Flux concepts would help, but I’ll review those quickly.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
Why pure functions make your code easier to maintain.
How unidirectional data flows help you sleep better at night.
How Redux helps you manage state better via reducers.
How to use Redux together with React.
How to test Redux applications.
This document summarizes Martin Odersky's talk on implicits in Scala. The key points are:
1. Implicits allow certain values or functions to be passed implicitly rather than explicitly as parameters. This can avoid tedious repetition when many parameters rarely change.
2. Implicits are commonly used to establish context, inject dependencies, implement type classes, and prove theorems by modeling types as theorems and programs as proofs.
3. Future changes to implicits in Scala 3 include allowing multiple implicit parameter lists, implicit by-name parameters, and implicit function types which avoid wrapping implicits in monads.
Talk given by Michael Damkot, Principal Network Engineer at Salesforce, at Interop in May 2016
A variety of efforts are underway to bring more programmability and automation to network management. These efforts are important because traditional methods can’t match the speed or scale required by modern applications and services, both in the data center and the cloud.
One mechanism to drive the evolution to a truly programmatic network is declarative network configuration, in which the expected state of the network is maintained in a configuration repository. Software is then used to instantiate the desired state on network devices.
Such software helps engineers and administrators provision network services more quickly, build more reliable networks, and shift their time and resources away from tedious configuration tasks to tackle more interesting challenges.
This talk aims to help you re-think how the network is managed. I’ll offer tips from my experience with declarative network configuration and its effectiveness in the real world, and describe tools I’ve leveraged in the pursuit of a truly automated and framework, including Ansible and Puppet.
How Functional Programming Made Me a Better DeveloperCameron Presley
With the rise in popularity recently, functional programming has become ""The Next Big Thing"". As of today, there are tons of frameworks and tools that can be used for front-end, back-end, desktop, and mobile development. With that being said, the majority of us are still using object-oriented languages for our day jobs and don't need to learn functional programming, right?
In this talk, I'll walk you through my experiences learning functional programming over the last year, how my style of programming has changed, and how I now think about programming with regards to both functional and object-oriented paradigms.
Better Page Object Handling with Loadable Component Pattern - SQA Days 20, Be...Sargis Sargsyan
One of the painful problems in Selenium automated testing is determining whether a HTML page has been loaded. This is especially the case when web application uses a JS heavy framework such as the popular AngularJS.
How to handle Selenium Page Object pattern better with Loadable Component.
The Loadable Component helps test case developers make sure that the page or a component of the page is loaded successfully. I will share my experience about the concept of the Loadable Component and Page Object patterns.
Generating unit tests based on user logsRick Wicker
Developing without automated testing is hard and risky. Making legacy code testable is hard. Try to improve your logging, add a data layer and see if you can drive testing from user behavior.
Complex systems fail. Failures are a normal occurrence and how the system responds to component failures determines if the system is resilient or if it results in an incident. This is true not just for Information Systems but also for industrial and mechanical systems. Users can learn from the experience of these systems on what common themes permeate and how to best build our software factories to minimize the effect of component failures and prevent incidents from becoming accidents.
This talk walks through the issues and experiences of complex systems and identifies the common failure points within systems. With a focus on complexity, tight coupling, operator error and transitions, users can learn from the industrial and system accidents that precede them, as they work to build new, modern, efficient, safe software and systems designs. It will draw upon both industrial and software examples of how things can go wrong and the common failure points among them. By the end of this talk, attendees will have an understanding of what decisions increase the chance of failure and which decisions and designs reduce it.
Here are a few steps I would take to analyze the issue:
1. Collect a thread dump of the application to see what threads are currently running and in what state. This will give clues about any threads that may be blocked or spinning.
2. Analyze the thread dump looking for threads that are in a RUNNABLE or BLOCKED state long-term. These could indicate spinning or long waits.
3. Check for threads waiting on locks, semaphores or other synchronization primitives. This could point to a potential deadlock.
4. Trace the code path and logic for threads of interest to understand what they are trying to accomplish and why they may be spinning or blocked.
5. Check
How are systems in finance design for deterministic outcomes, and performance. What are the benefits and what is the performance you can achieve.
Included a demo you can download.
Here are a few steps I would take to troubleshoot this issue:
1. Generate a thread dump of the application to see the state of all threads. This will show any threads that may be blocked or in an unexpected state.
2. Analyze the thread dump to look for threads that are in a "RUNNABLE" state but not making progress. These could be spinning threads wasting CPU.
3. Check for threads blocked on locks, monitors or other synchronization primitives. These indicate possible deadlocks.
4. Trace the code path for the package management service to see where it may be spinning or blocking unexpectedly.
5. Check application and server logs for any errors or exceptions that could cause blocking
This paper discusses challenges in diagnosing errors when deploying Hadoop ecosystems. It provides 15 examples of specific errors that can occur with Hbase/Hadoop deployment on Amazon EC2, along with potential root causes. The paper also classifies errors as operational, configuration, software, or resource-related. It identifies inconsistencies across component logs, high signal-to-noise ratios, and uncertainty in correlating events as difficulties for error diagnosis. The paper contributes examples to a repository for mapping deployment symptoms to fault trees to determine root causes.
This document summarizes key abstractions that were important to the success of Comdb2, a highly available clustered relational database system developed at Bloomberg. The four main abstractions discussed are:
1. The relational model and use of SQL provided important abstraction that simplified application development and improved performance and reliability compared to a noSQL approach.
2. A goal of "perfect availability" where the database is always available and applications do not need error handling for failures.
3. Ensuring serializability so the database acts as if it has no concurrency to simplify application development.
4. Presenting the distributed database as a "single system image" so applications do not need to account
Here we discuss Qardio's experience in Core Data, decisions and conclusions that were made. We also spend some extra time comparing different Core Data stacks. Here is the talk itself: https://youtu.be/BF9DD8XXxaI
Better Page Object Handling with Loadable Component PatternSQALab
This document discusses the Loadable Component pattern for improving page object handling in Selenium tests. It begins with an introduction to page object patterns and common failures. It then covers topics like wait strategies in Selenium, the LoadableComponent and SlowLoadableComponent patterns, and implementing these patterns on an existing project. Examples are provided in Java of how to update base page classes and page object classes to use these patterns. Common failures like brittle tests are also discussed.
The document summarizes findings from a survey on continuous delivery practices. The survey found that while 81% of organizations practiced some form of continuous delivery for their code, only around 50% did so for their databases. Key challenges included a lack of database version control, manual scripting processes prone to errors, and a lack of trust and communication between developers and database administrators. Adopting database version control, automated deployments informed by version control data, and making DBAs responsible for continuous delivery processes could help address these challenges and barriers to fully implementing continuous delivery for databases.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
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Artificial intelligence (AI) | Definitio
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
2. Agenda
•What’s a function?
•What’s a pure function?
•What’s a side effect?
•Referential transparency.
•Keep it simple.
•Examples.
•The trouble with shared state.
2
3. What’s a function?
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A function is something that takes an input, and
produces some output.
function sum(a, b) {
return a+b;
}
For example, this is a function that takes two numbers
and returns the sum.
4. What’s a pure function?
4
A pure function is a function which:
• Given the same input, will always return the same
output.
• Produces no side effects.
• Relies on no external state.
5. What’s a side effect?
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Side effects may include, but are not limited to:
• Changing the file system.
• Inserting a record into a database.
• Making an http call.
• Mutations.
• Printing to the screen / logging.
• Obtaining user input.
• Accessing system state.
6. Referential transparency.
6
A function in algebra: f(x) = 2x
> const double = x => x * 2;
Since `double` is a pure function we can replace
`double(5)` with 10 without changing the meaning.
So, `console.log(double(5));` is the same as
`console.log(10);`
7. Keep it simple.
7
Pure functions take some input and return some output
based on that input. They are the simplest reusable
building blocks of code in a program:
• KISS (Keep It Simple, Stupid)
Pure functions are stupid simple in the best possible
way.
10. In summary.
• Extremely independent.
• Easy to move around.
• Refactor.
• Easy to reorganize in your code.
• Gives more flexibility.
• Adaptable to future changes.
• Easy to test.
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12. The trouble with shared state
• Reliant on sequences which vary depending on indeterministic factors.
• The output is impossible to predict.
• Impossible to properly test.
• Impossible to fully understand.
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13. “
| Confidential
There is no non-determinism without mutable states. There
is no race condition or deadlock without mutable states.
Mutable states are the root of the problem.
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— Martin Odersky
15. Recipe for bugs.
• A single threaded JS engine does not imply that there is no
concurrency.
• API I/O, event listeners, web workers, iframes, and timeouts.
Combine that with shared state, and you’ve got a recipe for bugs.
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16. “
| Confidential
Shared mutable state and parallel processing doesn't go
together at all. If you do not use proper synchronization you
will create extremely difficult to find bugs and your
programs are basically broken even if they appear to work
just fine in most cases.
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