Functional programming can be an excellent approach to designing decoupled, reusable systems with a rich domain model. In fact, the lessons from applying DDD in a functional language translate well to object-oriented programming.
(Video and code at https://fsharpforfunandprofit.com/pipeline/)
Passing data through a pipeline of transformations is an alternative approach to classic OOP. The LINQ methods in .NET are designed around this, but the pipeline approach can be used for so much more than manipulating collections.
In this talk, I'll look at pipeline-oriented programming and how it relates to functional programming, the open-closed principle, unit testing, the onion architecture, and more. I'll finish up by showing how you can build a complete web app using only this approach.
(Video of these slides here http://fsharpforfunandprofit.com/rop)
(My response to "this is just Either" here: http://fsharpforfunandprofit.com/rop/#monads)
Many examples in functional programming assume that you are always on the "happy path". But to create a robust real world application you must deal with validation, logging, network and service errors, and other annoyances.
So, how do you handle all this in a clean functional way? This talk will provide a brief introduction to this topic, using a fun and easy-to-understand railway analogy.
(video and more at http://fsharpforfunandprofit.com/fppatterns)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID. The functional programming community has design patterns and principles as well. This talk will provide an overview of some of these patterns (such as currying, monads), and present some demonstrations of FP design in practice. We'll also look at some of the ways you can use these patterns as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
This document provides an overview of diabetes mellitus (DM), including the three main types (Type 1, Type 2, and gestational diabetes), signs and symptoms, complications, pathophysiology, oral manifestations, dental management considerations, emergency management, diagnosis, and treatment. DM is caused by either the pancreas not producing enough insulin or cells not responding properly to insulin, resulting in high blood sugar levels. The document compares and contrasts the characteristics of Type 1 and Type 2 DM.
Power Point Presentation on Artificial Intelligence Anushka Ghosh
Its a Power Point Presentation on Artificial Intelligence.I hope you will find this helpful. Thank you.
You can also find out my another PPT on Artificial Intelligence.The link is given below--
https://www.slideshare.net/AnushkaGhosh5/ppt-presentation-on-artificial-intelligence
Anushka Ghosh
The document summarizes key aspects of the Safe Spaces Act, which aims to address gender-based sexual harassment. It defines harassment in public spaces, online, and work/educational settings. Acts considered harassment include catcalling, unwanted comments on appearance, stalking, and distributing intimate photos without consent. Those found guilty face penalties like imprisonment or fines. The law also requires employers and educational institutions to disseminate the law, prevent harassment, and address complaints through committees.
This document defines hypertension and describes its types, etiology, risk factors, pathophysiology, clinical features, diagnostic evaluations, and management. Hypertension is defined as a systolic blood pressure of 140 mmHg or higher and/or a diastolic blood pressure of 90 mmHg or higher. It is managed primarily through lifestyle modifications like diet and exercise changes as well as pharmacological therapies including diuretics, beta blockers, ACE inhibitors, and calcium channel blockers. Nursing care involves monitoring the patient's condition, educating on lifestyle changes, and ensuring proper treatment adherence.
The document discusses the nursing process, which includes assessment, nursing diagnosis, planning, implementation, and evaluation. It describes each component in detail. Assessment involves collecting client data through various methods. Nursing diagnosis identifies client problems based on the assessment. Planning establishes goals and interventions. Implementation carries out the planned interventions. Evaluation assesses client progress and intervention effectiveness. The nursing process is a systematic approach to providing individualized care.
Domain Driven Design with the F# type System -- NDC London 2013Scott Wlaschin
(Video of these slides here http://fsharpforfunandprofit.com/ddd)
Statically typed functional programming languages like F# encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers.
Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time.
In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
Code, links to video, etc., at http://fsharpforfunandprofit.com/ddd
For more on DDD and F# see:
http://fsharpforfunandprofit.com/ddd/
http://tomasp.net/blog/type-first-development.aspx/
http://gorodinski.com/blog/2013/02/17/domain-driven-design-with-fsharp-and-eventstore/
The Functional Programmer's Toolkit (NDC London 2019)Scott Wlaschin
(slides and video at https://fsharpforfunandprofit.com/fptoolkit)
The functional programming community has a number of patterns with strange names such as monads, monoids, functors, and catamorphisms.
In this beginner-friendly talk, we'll demystify these techniques and see how they all fit together into a small but versatile "tool kit".
We'll then see how the tools in this tool kit can be applied to a wide variety of programming problems, such as handling missing data, working with lists, and implementing the functional equivalent of dependency injection.
Composition is a fundamental principle of functional programming, but how is it different from an object-oriented approach, and how do you use it in practice?
In this talk for beginners, we'll start by going over the basic concepts of functional programming, and then look at some different ways that composition can be used to build large things from small things.
After that, we'll see how composition is used in practice, beginning with a simple FizzBuzz example, and ending with a complete (object-free!) web application.
Domain Driven Design with the F# type System -- F#unctional Londoners 2014Scott Wlaschin
(Video of these slides here http://fsharpforfunandprofit.com/ddd)
Statically typed functional programming languages like F# encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers.
Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time.
In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
Code, links to video, etc., at http://fsharpforfunandprofit.com/ddd
NEW AND IMPROVED - added sections on:
* why OO, not FP is scary
* designing with states and transitions
Functional Programming Patterns (NDC London 2014)Scott Wlaschin
(video of these slides available here http://fsharpforfunandprofit.com/fppatterns/)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID.
The functional programming community has design patterns and principles as well.
This talk will provide an overview of some of these, and present some demonstrations of FP design in practice.
(video of these slides available here http://fsharpforfunandprofit.com/fppatterns/)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID.
The functional programming community has design patterns and principles as well.
This talk will provide an overview of some of these, and present some demonstrations of FP design in practice.
(Video available at http://fsharpforfunandprofit.com/monadster/)
You've got a pile of assorted functions lying around. Each one is useful and reliable, but they just don't fit together properly. How can you assemble them into a complete system that can stand on its own two feet and terrorize the local villagers?
In this session, I'll show how functional programming can transform all sorts of existing code into shapes that are plug-compatible and which can be bolted together effortlessly.
SAFETY NOTE: The techniques demonstrated are perfectly harmless and can even be used at your workplace -- no lightning bolts required.
The Functional Programming Toolkit (NDC Oslo 2019)Scott Wlaschin
(slides and video at https://fsharpforfunandprofit.com/fptoolkit)
The techniques and patterns used in functional programming are very different from object-oriented programming, and when you are just starting out it can be hard to know how they all fit together.
In this big picture talk for FP beginners, I'll present some of the common tools that can be found in a functional programmer's toolbelt; tools such as "map", "apply", "bind", and "sequence". What are they? Why are they important? How are they used in practice? And how do they relate to scary sounding concepts like functors, monads, and applicatives?
(Demo code and video available at http://fsharpforfunandprofit.com/cap/)
We all want to produce modular and robust code that is easy to test and refactor, and we have design principles such as SOLID that help us do that.
In this talk I'll look at a very different approach to design using "capabilities" and the principle of least authority. I'll show how using these design techniques throughout your core domain (and not just at your API boundary) also leads to well-designed and modular code.
I'll demonstrate how to design and use a capability based approach, how capabilities can be quickly combined and restricted easily, and how capabilities are a natural fit with a REST API that uses HATEAOS.
The document discusses clean coding practices for Java developers. It covers topics such as choosing meaningful names for variables, methods, and classes; writing code that is easy for others to understand; breaking methods down into single logical steps; and using fluent APIs to make code more readable. The presentation provides examples of clean code and ways to refactor code to follow best practices.
The document discusses monads and functional programming concepts. It begins by explaining that monads are structures that put values in computational contexts. It then provides a technical definition of a monad involving endofunctors, natural transformations, and laws. Several examples are given to illustrate monads, including the Optional monad in Java to handle null values, and the Stream monad to represent sequences. The document advocates using monads to make aspects like errors, state, and effects explicit in a program's type system.
(Video and code at http://fsharpforfunandprofit.com/composition)
Composition is a fundamental principle of functional programming, but how is it different from an object-oriented approach, and how do you use it in practice?
In this talk for beginners, we'll start by going over the basic concepts of functional programming, and then look at some different ways that composition can be used to build large things from small things.
After that, we'll see how composition is used in practice, beginning with a simple FizzBuzz example, and ending with a complete (object-free!) web application.
(Video available at https://fsharpforfunandprofit.com/composition/)
Composition is a fundamental building block of functional programming, but how is it different from an object-oriented approach, and how do you use it in practice?
In this talk for beginners, we'll start by going over the basic concepts of functional programming, and then look at some different ways that composition can be used to build large things from small things.
After that, we'll see how composition is used in practice, beginning with some basic examples, and ending with a complete (object-free!) web application.
Domain Modeling Made Functional (KanDDDinsky 2019)Scott Wlaschin
(video at https://fsharpforfunandprofit.com/ddd/)
Statically typed functional programming languages encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers. Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time. In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
Monoids - Part 1 - with examples using Scalaz and CatsPhilip Schwarz
A monoid is an algebraic structure consisting of a set and a binary operation that is associative and has an identity element. Some key properties of monoids include:
1) A monoid consists of a type A, a binary operation op that combines two values of type A, and a zero value that acts as an identity.
2) The binary operation must be associative, meaning op(op(x,y),z) = op(x,op(y,z)).
3) The zero value must satisfy the identity laws: op(x, zero) = x and op(zero, x) = x.
4) Common examples of monoids include string concatenation
The document provides idiomatic Kotlin coding style guidelines and best practices for expressions, classes, functions, and the standard library. Some key recommendations include using 'when' and 'try' as expression bodies, avoiding classes just for functions, extracting non-essential APIs to extensions, using data classes, type aliases, and destructuring declarations, and leveraging functions like 'apply', 'filterIsInstance', and 'groupBy' from the standard library. Overall the document advises organizing code in a concise and functional way that fully utilizes Kotlin language features.
Video and related blog posts at fsharpforfunandprofit.com/ettt
Follow along as I ridiculously over-engineer a simple game to demonstrate how functional programming can be used to create a real-world "enterprise-ready" application.
Topics covered include: encoding business rules into types, data hiding with parametric polymorphism, using functions for capability-based security, exposing a REST API with HATEAOS, the functional approach to logging, actors, scalability and more.
This document discusses principles of clean code based on the book "Clean Code" by Robert C. Martin. It provides examples of good and bad practices for naming variables and functions, structuring functions, using comments, and other topics. Key points include using meaningful names, keeping functions small and focused on a single task, avoiding deeply nested code and long argument lists, commenting to explain intent rather than state the obvious, and other guidelines for writing clean, readable code.
download for better quality - Learn how to use an Applicative Functor to handle multiple independent effectful values through the work of Sergei Winitzki, Runar Bjarnason, Paul Chiusano, Debasish Ghosh and Adelbert Chang
download for better quality - Learn about the sequence and traverse functions
through the work of Runar Bjarnason and Paul Chiusano, authors of Functional Programming in Scala https://www.manning.com/books/functional-programming-in-scala, and others (Martin Odersky, Derek Wyatt, Adelbert Chang)
Domain Modeling Made Functional (DevTernity 2022)Scott Wlaschin
(video at https://fsharpforfunandprofit.com/ddd/)
Statically typed functional programming languages encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers. Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time. In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
project 6/cards.py
import random
class Card( object ):
""" Model a playing card. """
# Rank is an integer (1-13), where aces are 1 and kings are 13.
# Suit is an integer (1-4), where clubs are 1 and spades are 4.
# Value is an integer (1-10), where aces are 1 and face cards are 10.
# List to map integer rank to printable character (index 0 used for no rank)
rank_list = ['x','A','2','3','4','5','6','7','8','9','10','J','Q','K']
# List to map integer suit to printable character (index 0 used for no suit)
# The commented-out list prints symbols rather than characters. You may use either.
suit_list = ['x','c','d','h','s']
#suit_list = ['x',u'\u2660',u'\u2665',u'\u2666',u'\u2663']
def __init__( self, rank=0, suit=0 ):
""" Initialize card to specified rank (1-13) and suit (1-4). """
self.__rank = 0
self.__suit = 0
# Verify that rank and suit are integers and that they are within
# range (1-13 and 1-4), then update instance variables if valid.
if type(rank) == int and type(suit) == int:
if rank in range(1,14) and suit in range(1,5):
self.__rank = rank
self.__suit = suit
def rank( self ):
""" Return card's rank (1-13). """
return self.__rank
def value( self ):
""" Return card's value (1 for aces, 2-9, 10 for face cards). """
# Use ternary expression to determine value.
return self.__rank if self.__rank < 10 else 10
def suit( self ):
""" Return card's suit (1-4). """
return self.__suit
def __eq__( self, other ):
""" Return True if ranks are equal. """
return self.__rank == other.__rank
def __ne__( self, other ):
""" Return True if ranks are not equal. """
return self.__rank != other.__rank
def __le__( self, other ):
""" Return True if rank of self <= rank of other. """
return self.rank() <= other.rank()
def __lt__( self, other ):
""" Return True if rank of self < rank of other. """
return self.rank() < other.rank()
def __ge__( self, other ):
""" Return True if rank of self >= rank of other. """
return self.rank() >= other.rank()
def __gt__( self, other ):
""" Return True if rank of self > rank of other. """
return self.rank() > other.rank()
def __str__( self ):
""" Convert card into a string (usually for printing). """
# Use rank to index into rank_list; use suit to index into suit_list.
return "{}{}".format( (self.rank_list)[self.__rank], (self.suit_list)[self.__suit] )
def __repr__( self ):
""" Convert card into a string for use in the shell. """
return self.__str__()
class Deck( object ):
""" Model a deck of 52 playing cards. """
# Implement the deck as a list.
Domain Driven Design with the F# type System -- NDC London 2013Scott Wlaschin
(Video of these slides here http://fsharpforfunandprofit.com/ddd)
Statically typed functional programming languages like F# encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers.
Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time.
In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
Code, links to video, etc., at http://fsharpforfunandprofit.com/ddd
For more on DDD and F# see:
http://fsharpforfunandprofit.com/ddd/
http://tomasp.net/blog/type-first-development.aspx/
http://gorodinski.com/blog/2013/02/17/domain-driven-design-with-fsharp-and-eventstore/
The Functional Programmer's Toolkit (NDC London 2019)Scott Wlaschin
(slides and video at https://fsharpforfunandprofit.com/fptoolkit)
The functional programming community has a number of patterns with strange names such as monads, monoids, functors, and catamorphisms.
In this beginner-friendly talk, we'll demystify these techniques and see how they all fit together into a small but versatile "tool kit".
We'll then see how the tools in this tool kit can be applied to a wide variety of programming problems, such as handling missing data, working with lists, and implementing the functional equivalent of dependency injection.
Composition is a fundamental principle of functional programming, but how is it different from an object-oriented approach, and how do you use it in practice?
In this talk for beginners, we'll start by going over the basic concepts of functional programming, and then look at some different ways that composition can be used to build large things from small things.
After that, we'll see how composition is used in practice, beginning with a simple FizzBuzz example, and ending with a complete (object-free!) web application.
Domain Driven Design with the F# type System -- F#unctional Londoners 2014Scott Wlaschin
(Video of these slides here http://fsharpforfunandprofit.com/ddd)
Statically typed functional programming languages like F# encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers.
Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time.
In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
Code, links to video, etc., at http://fsharpforfunandprofit.com/ddd
NEW AND IMPROVED - added sections on:
* why OO, not FP is scary
* designing with states and transitions
Functional Programming Patterns (NDC London 2014)Scott Wlaschin
(video of these slides available here http://fsharpforfunandprofit.com/fppatterns/)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID.
The functional programming community has design patterns and principles as well.
This talk will provide an overview of some of these, and present some demonstrations of FP design in practice.
(video of these slides available here http://fsharpforfunandprofit.com/fppatterns/)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID.
The functional programming community has design patterns and principles as well.
This talk will provide an overview of some of these, and present some demonstrations of FP design in practice.
(Video available at http://fsharpforfunandprofit.com/monadster/)
You've got a pile of assorted functions lying around. Each one is useful and reliable, but they just don't fit together properly. How can you assemble them into a complete system that can stand on its own two feet and terrorize the local villagers?
In this session, I'll show how functional programming can transform all sorts of existing code into shapes that are plug-compatible and which can be bolted together effortlessly.
SAFETY NOTE: The techniques demonstrated are perfectly harmless and can even be used at your workplace -- no lightning bolts required.
The Functional Programming Toolkit (NDC Oslo 2019)Scott Wlaschin
(slides and video at https://fsharpforfunandprofit.com/fptoolkit)
The techniques and patterns used in functional programming are very different from object-oriented programming, and when you are just starting out it can be hard to know how they all fit together.
In this big picture talk for FP beginners, I'll present some of the common tools that can be found in a functional programmer's toolbelt; tools such as "map", "apply", "bind", and "sequence". What are they? Why are they important? How are they used in practice? And how do they relate to scary sounding concepts like functors, monads, and applicatives?
(Demo code and video available at http://fsharpforfunandprofit.com/cap/)
We all want to produce modular and robust code that is easy to test and refactor, and we have design principles such as SOLID that help us do that.
In this talk I'll look at a very different approach to design using "capabilities" and the principle of least authority. I'll show how using these design techniques throughout your core domain (and not just at your API boundary) also leads to well-designed and modular code.
I'll demonstrate how to design and use a capability based approach, how capabilities can be quickly combined and restricted easily, and how capabilities are a natural fit with a REST API that uses HATEAOS.
The document discusses clean coding practices for Java developers. It covers topics such as choosing meaningful names for variables, methods, and classes; writing code that is easy for others to understand; breaking methods down into single logical steps; and using fluent APIs to make code more readable. The presentation provides examples of clean code and ways to refactor code to follow best practices.
The document discusses monads and functional programming concepts. It begins by explaining that monads are structures that put values in computational contexts. It then provides a technical definition of a monad involving endofunctors, natural transformations, and laws. Several examples are given to illustrate monads, including the Optional monad in Java to handle null values, and the Stream monad to represent sequences. The document advocates using monads to make aspects like errors, state, and effects explicit in a program's type system.
(Video and code at http://fsharpforfunandprofit.com/composition)
Composition is a fundamental principle of functional programming, but how is it different from an object-oriented approach, and how do you use it in practice?
In this talk for beginners, we'll start by going over the basic concepts of functional programming, and then look at some different ways that composition can be used to build large things from small things.
After that, we'll see how composition is used in practice, beginning with a simple FizzBuzz example, and ending with a complete (object-free!) web application.
(Video available at https://fsharpforfunandprofit.com/composition/)
Composition is a fundamental building block of functional programming, but how is it different from an object-oriented approach, and how do you use it in practice?
In this talk for beginners, we'll start by going over the basic concepts of functional programming, and then look at some different ways that composition can be used to build large things from small things.
After that, we'll see how composition is used in practice, beginning with some basic examples, and ending with a complete (object-free!) web application.
Domain Modeling Made Functional (KanDDDinsky 2019)Scott Wlaschin
(video at https://fsharpforfunandprofit.com/ddd/)
Statically typed functional programming languages encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers. Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time. In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
Monoids - Part 1 - with examples using Scalaz and CatsPhilip Schwarz
A monoid is an algebraic structure consisting of a set and a binary operation that is associative and has an identity element. Some key properties of monoids include:
1) A monoid consists of a type A, a binary operation op that combines two values of type A, and a zero value that acts as an identity.
2) The binary operation must be associative, meaning op(op(x,y),z) = op(x,op(y,z)).
3) The zero value must satisfy the identity laws: op(x, zero) = x and op(zero, x) = x.
4) Common examples of monoids include string concatenation
The document provides idiomatic Kotlin coding style guidelines and best practices for expressions, classes, functions, and the standard library. Some key recommendations include using 'when' and 'try' as expression bodies, avoiding classes just for functions, extracting non-essential APIs to extensions, using data classes, type aliases, and destructuring declarations, and leveraging functions like 'apply', 'filterIsInstance', and 'groupBy' from the standard library. Overall the document advises organizing code in a concise and functional way that fully utilizes Kotlin language features.
Video and related blog posts at fsharpforfunandprofit.com/ettt
Follow along as I ridiculously over-engineer a simple game to demonstrate how functional programming can be used to create a real-world "enterprise-ready" application.
Topics covered include: encoding business rules into types, data hiding with parametric polymorphism, using functions for capability-based security, exposing a REST API with HATEAOS, the functional approach to logging, actors, scalability and more.
This document discusses principles of clean code based on the book "Clean Code" by Robert C. Martin. It provides examples of good and bad practices for naming variables and functions, structuring functions, using comments, and other topics. Key points include using meaningful names, keeping functions small and focused on a single task, avoiding deeply nested code and long argument lists, commenting to explain intent rather than state the obvious, and other guidelines for writing clean, readable code.
download for better quality - Learn how to use an Applicative Functor to handle multiple independent effectful values through the work of Sergei Winitzki, Runar Bjarnason, Paul Chiusano, Debasish Ghosh and Adelbert Chang
download for better quality - Learn about the sequence and traverse functions
through the work of Runar Bjarnason and Paul Chiusano, authors of Functional Programming in Scala https://www.manning.com/books/functional-programming-in-scala, and others (Martin Odersky, Derek Wyatt, Adelbert Chang)
Domain Modeling Made Functional (DevTernity 2022)Scott Wlaschin
(video at https://fsharpforfunandprofit.com/ddd/)
Statically typed functional programming languages encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers. Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time. In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
project 6/cards.py
import random
class Card( object ):
""" Model a playing card. """
# Rank is an integer (1-13), where aces are 1 and kings are 13.
# Suit is an integer (1-4), where clubs are 1 and spades are 4.
# Value is an integer (1-10), where aces are 1 and face cards are 10.
# List to map integer rank to printable character (index 0 used for no rank)
rank_list = ['x','A','2','3','4','5','6','7','8','9','10','J','Q','K']
# List to map integer suit to printable character (index 0 used for no suit)
# The commented-out list prints symbols rather than characters. You may use either.
suit_list = ['x','c','d','h','s']
#suit_list = ['x',u'\u2660',u'\u2665',u'\u2666',u'\u2663']
def __init__( self, rank=0, suit=0 ):
""" Initialize card to specified rank (1-13) and suit (1-4). """
self.__rank = 0
self.__suit = 0
# Verify that rank and suit are integers and that they are within
# range (1-13 and 1-4), then update instance variables if valid.
if type(rank) == int and type(suit) == int:
if rank in range(1,14) and suit in range(1,5):
self.__rank = rank
self.__suit = suit
def rank( self ):
""" Return card's rank (1-13). """
return self.__rank
def value( self ):
""" Return card's value (1 for aces, 2-9, 10 for face cards). """
# Use ternary expression to determine value.
return self.__rank if self.__rank < 10 else 10
def suit( self ):
""" Return card's suit (1-4). """
return self.__suit
def __eq__( self, other ):
""" Return True if ranks are equal. """
return self.__rank == other.__rank
def __ne__( self, other ):
""" Return True if ranks are not equal. """
return self.__rank != other.__rank
def __le__( self, other ):
""" Return True if rank of self <= rank of other. """
return self.rank() <= other.rank()
def __lt__( self, other ):
""" Return True if rank of self < rank of other. """
return self.rank() < other.rank()
def __ge__( self, other ):
""" Return True if rank of self >= rank of other. """
return self.rank() >= other.rank()
def __gt__( self, other ):
""" Return True if rank of self > rank of other. """
return self.rank() > other.rank()
def __str__( self ):
""" Convert card into a string (usually for printing). """
# Use rank to index into rank_list; use suit to index into suit_list.
return "{}{}".format( (self.rank_list)[self.__rank], (self.suit_list)[self.__suit] )
def __repr__( self ):
""" Convert card into a string for use in the shell. """
return self.__str__()
class Deck( object ):
""" Model a deck of 52 playing cards. """
# Implement the deck as a list.
This document discusses domain typing in Ruby through the lens of functional programming and domain-driven design. It introduces concepts like defining types as sets of possible values, using types to improve safety and intellectual manageability, and modeling domains and behavior through state machines and explicit state transitions. While typing is not native to Ruby, libraries like dry-types, dry-struct, and dry-logic make it possible to integrate these approaches and reap their benefits, moving Ruby code in a more functional direction.
FaceUp card game In this assignment we will implement a made.pdfabifancystore
FaceUp card game
In this assignment we will implement a made-up card game we'll call FaceUp. When the game
starts, you deal five cards face down. Your goal is to achieve as high a score as possible. Your
score only includes cards that are face up. Red cards (hearts and diamonds) award positive
points, while black cards (clubs and spades) award negative points. Cards 2-10 have points worth
their face value. Cards Jack, Queen, and King have value 10, and Ace is 11.
The game is played by flipping over cards, either from face-down to face-up or from face-up to
face-down. As you play, you are told your total score (ie, total of the face-up cards) and the total
score of the cards that are face down. The challenge is that you only get up to a fixed number of
flips and then the game is over.
Here is an example of the output from playing the game:
At each point where the program asks the user to pick a card, the game waits for user input.
Code
Well implement the game using five classes, three of which you'll leave unchanged, and two you
will modify and submit:
Card: Leave this code unchanged.
CardDealer: Leave this code unchanged.
FaceUpCard: This class extends the Card class with additional functionality. You will add two
methods needed for the FaceUp game.
FaceUpHand: This class keeps track of the state of the game. Most of the methods you will
implement are here.
FaceUpGame: This class implements the game interface. It gets data from the user, updates the
board, and repeats the process. Leave this code unchanged.
How to proceed
You may fill in the details of the FaceUpCard and FaceUpHandclasses however youd like, but
heres what we recommend.
Add the two methods to the FaceUpCard class (described in comments in the code). Add a main
method to this class and test them to make sure they work.
Read through the other two new classes FaceUpHand and FaceUpGame. Make sure you
understand what all of the methods in FaceUpHand are supposed to do and that you understand
how theyre used in the FaceUpGame class.
Implement methods in the FaceUpHand class incrementally. Write one method and then test it!
To test it, again, add a main method and write a small test or two to make sure it behaves like
youd expect. If you try to implement all of the methods and then test it by simply running
FaceUpGame, 1) its very unlikely youll get it perfect the first time and then 2) its going to be very
hard to figure out where the problem is.
Card.java
public class Card {
// min/max for the card number range
private static final int MIN_NUMBER = 1;
private static final int MAX_NUMBER = 13;
private int number;
private String suit;
/**
* Create a new card with number and suit. If the a valid
* suit/number is not input, the card defaults to 1 of hearts.
*
* @param number the card number
* @param suit the card suit
*/
public Card(int number, String suit){
this.number = number;
this.suit = suit.toLowerCase();
if (!isValidSuit(suit)) {
System.out.println(suit + "Is not a valid suit!").
This is the final code which meets your requirement.Than youCard.j.pdfaplolomedicalstoremr
This is the final code which meets your requirement.Than you
Card.java
import java.util.Random;
public class Card {
//declaring instance variables
private String suit;
private int face_value;
public static int count=52;
//Creating an instance of Random class reference
Random rand;
//Default Constructor
public Card() {
super();
//Passing random class object to the Random class reference
rand = new Random();
}
//Getters and setters
public String getSuit() {
return suit;
}
public void setSuit(String suit) {
this.suit = suit;
}
public int getFace_value() {
return face_value;
}
public void setFace_value(int face_value) {
this.face_value = face_value;
}
public int getCount() {
return count;
}
//This shuffle() method will shuffle the deck
public void shuffle()
{
//Picking a card from the deck randomly and find its face value and suit
this.face_value = 1 + rand.nextInt((9) + 1);
int suit_random_value = 1 + rand.nextInt((3) + 1);
if(suit_random_value==1)
{
this.suit=\"Clubs\";
}
else if(suit_random_value==2)
{
this.suit=\"hearts\";
}
else if(suit_random_value==3)
{
this.suit=\"Spades\";
}
else if(suit_random_value==4)
{
this.suit=\"diamonds\";
}
this.count=count-1;
}
}
________________________________________________________________________
DriverClass.java
public class DriverClass {
public static void main(String[] args) {
//creating an array which can hold 52 Card class Objects
Card c[]=new Card[52];
//Creating 52 card class objects and storing them into an array
for(int i=0;i<52;i++)
{
//Creating Card class Object
c[i]=new Card();
}
//Displaying each card face value and its suit.
for(int i=0;i<52;i++)
{
//Shuffling the deck before every card picking from the deck
c[i].shuffle();
//Displaying randomly picked card face value and its suit
System.out.println(c[i].getFace_value()+\" of \"+c[i].getSuit()+\" Cards remaining
\"+c[i].getCount());
}
}
}
_________________________________________________________________________
Output:
8 of diamonds
Cards remaining 51
4 of Clubs
Cards remaining 50
9 of Clubs
Cards remaining 49
7 of Spades
Cards remaining 48
9 of diamonds
Cards remaining 47
7 of diamonds
Cards remaining 46
4 of diamonds
Cards remaining 45
9 of Clubs
Cards remaining 44
5 of hearts
Cards remaining 43
7 of Spades
Cards remaining 42
10 of Clubs
Cards remaining 41
7 of diamonds
Cards remaining 40
8 of diamonds
Cards remaining 39
6 of hearts
Cards remaining 38
4 of hearts
Cards remaining 37
6 of Spades
Cards remaining 36
4 of Clubs
Cards remaining 35
3 of diamonds
Cards remaining 34
9 of diamonds
Cards remaining 33
3 of diamonds
Cards remaining 32
5 of Spades
Cards remaining 31
4 of Clubs
Cards remaining 30
3 of Spades
Cards remaining 29
6 of diamonds
Cards remaining 28
3 of hearts
Cards remaining 27
9 of hearts
Cards remaining 26
7 of hearts
Cards remaining 25
3 of hearts
Cards remaining 24
10 of Clubs
Cards remaining 23
2 of hearts
Cards remaining 22
9 of Clubs
Cards remaining 21
8 of diamonds
Cards remaining 20
8 of Clubs
Cards remaining 19
2 of h.
Intellectual playing cards - Not for everyonedrstevenquay
A thrilling pile of cards that encourages creativity and critical thinking using mathematical combinatorics, this deck is near-heaven. Truth be told, it is not for everyone. It would however be the delight of card gamer who are intrigued by randomness, creativity and spontaneity. Gamer who love to think outside the box and are bored of playing regular traditional playing cards.
Building confidence in concurrent code with a model checker: TLA+ for program...Scott Wlaschin
As developers, we have a number of well-known practices to ensure code quality, such as unit tests, code review and so on. But these practices often break down when we need to design concurrent systems. Often, there can be subtle and serious bugs that are not found with conventional practices.
But there’s another approach that you can use -- model-checking -- that can detect potential concurrency errors at design time, and so dramatically increase your confidence in your code. In this talk, I’ll demonstrate and demystify TLA+, a powerful design and model-checking system. We’ll see how it can check your concurrent designs for errors, saving you time up front and frustration later!
The lazy programmer's guide to writing thousands of testsScott Wlaschin
We are all familiar with example-based testing, as typified by TDD and BDD, where each test is hand-crafted.
But there's another approach to writing tests. In the "property-based testing" approach, a single test is run hundreds of times with randomly generated inputs. Property-based testing is a great way to find edge cases, and also helps you to understand and document the behavior of your code under all conditions.
This talk will introduce property-based testing, show you how it works, and demonstrate why you should consider adding this powerful technique to your toolbelt.
Reinventing the Transaction Script (NDC London 2020)Scott Wlaschin
The Transaction Script pattern organizes business logic as a single procedure. It has always been considered less sophisticated and flexible than a layered architecture with a rich domain model. But is that really true?
In this talk, we'll reinvent the Transaction Script using functional programming principles. We'll see that we can still do domain-driven design, and still have code which is decoupled and reusable, all while preserving the simplicity and productivity of the original one-script-per-workflow approach.
Four Languages From Forty Years Ago (NewCrafts 2019)Scott Wlaschin
(More info and video at fsharpforfunandprofit.com/fourfromforty)
The 1970's were a golden age for new programming languages, but do they have any relevance to programming today? Can we still learn from them?
In this talk, we'll look at four languages designed over forty years ago -- SQL, Prolog, ML, and Smalltalk -- and discuss their philosophy and approach to programming, which is very different from most popular languages today.
We'll come away with some practical principles that are still very applicable to modern development. And you might discover your new favorite programming paradigm!
(More info and video at fsharpforfunandprofit.com/fourfromforty)
The 1970's were a golden age for new programming languages, but do they have any relevance to programming today? Can we still learn from them?
In this talk, we'll look at four languages designed over forty years ago -- SQL, Prolog, ML, and Smalltalk -- and discuss their philosophy and approach to programming, which is very different from most popular languages today.
We'll come away with some practical principles that are still very applicable to modern development. And you might discover your new favorite programming paradigm!
(Video and more at fsharpforfunandprofit.com/csharp)
Curious about F# and want to understand how is it different from C#?
In this talk, we'll look at the basics of coding in F#, and how functional programming differs from object-oriented programming. Along the way, there will be many examples showing the same code written in C# and F# so that you can see for yourself how the two languages differ in style and approach.
(Video and code available at http://fsharpforfunandprofit.com/cap)
In this talk I'll look at a unusual approach to designing internal interfaces and external APIs -- a "capability-based" approach that takes the Principle Of Least Authority and applies it to software design.
When this approach is used, it produces a robust and modular design which captures the domain constraints, resulting in an API which is self-documenting and hard to misuse.
I'll demonstrate how to design and implement a capability based approach, how capabilities can be quickly combined and restricted easily, and how capabilities are a natural fit with a REST API that uses HATEOAS.
(Video and code available at http://fsharpforfunandprofit.com/turtle)
In this fast-paced talk, I'll start with the well known API for turtle graphics, and then stretch it to the breaking point by creating 13 different implementations, each demonstrating a different functional programming technique.
Along the way, we'll use partial application, functional dependency injection, validation
with Success/Failure results, the Either monad, the State monad, agents with message queues, event sourcing, stream processing, capability-based design, and the interpreter pattern (aka free monad). Phew!
Video and more content at fsharpforfunandprofit.com/pbt
"The lazy programmer's guide to writing 1000's of tests: An introduction to property based testing"
We are all familiar with example-based testing, as typified by TDD and BDD. Property-based testing takes a very different approach, where a single test is run hundreds of times with randomly generated inputs.
Property-based testing is a great way to find edge cases, and also helps you to understand and document the behaviour of your code under all conditions.
This talk will introduce property-based testing and show how it works, and why you should consider adding it to your arsenal of testing tools.
The document compares the Swift programming language to an unknown language X, describing various features and capabilities. It poses questions about language X that hint it is focused on cross-platform development, open source, safety, and functional programming. It is eventually revealed that language X is F#, and provides links to learn more about F# and its use for both front-end and back-end development across platforms like iOS, Android, and Azure.
This document discusses the key concepts of domain-driven design (DDD) including bounded contexts, ubiquitous language, entities, aggregates, repositories, services, anti-corruption layers, and continuous integration. It emphasizes that DDD focuses on modeling the core domain and collaboratively developing a shared language within and across bounded contexts to ensure alignment between technical and business goals.
🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
Here's a more detailed explanation:
Key Features and Capabilities:
Vector-Based Design:
Illustrator's foundation is its use of vector graphics, meaning designs are created using paths, lines, shapes, and curves defined mathematically.
Scalability:
This vector-based approach allows for designs to be resized without any loss of resolution or quality, making it suitable for various print and digital applications.
Design Creation:
Illustrator is used for a wide variety of design purposes, including:
Logos and Brand Identity: Creating logos, icons, and other brand assets.
Illustrations: Designing detailed illustrations for books, magazines, web pages, and more.
Marketing Materials: Creating posters, flyers, banners, and other marketing visuals.
Web Design: Designing web graphics, including icons, buttons, and layouts.
Text Handling:
Illustrator offers sophisticated typography tools for manipulating and designing text within your graphics.
Brushes and Effects:
It provides a range of brushes and effects for adding artistic touches and visual styles to your designs.
Integration with Other Adobe Software:
Illustrator integrates seamlessly with other Adobe Creative Cloud apps like Photoshop, InDesign, and Dreamweaver, facilitating a smooth workflow.
Why Use Illustrator?
Professional-Grade Features:
Illustrator offers a comprehensive set of tools and features for professional design work.
Versatility:
It can be used for a wide range of design tasks and applications, making it a versatile tool for designers.
Industry Standard:
Illustrator is a widely used and recognized software in the graphic design industry.
Creative Freedom:
It empowers designers to create detailed, high-quality graphics with a high degree of control and precision.
Meet the Agents: How AI Is Learning to Think, Plan, and CollaborateMaxim Salnikov
Imagine if apps could think, plan, and team up like humans. Welcome to the world of AI agents and agentic user interfaces (UI)! In this session, we'll explore how AI agents make decisions, collaborate with each other, and create more natural and powerful experiences for users.
⭕️➡️ FOR DOWNLOAD LINK : http://drfiles.net/ ⬅️⭕️
Maxon Cinema 4D 2025 is the latest version of the Maxon's 3D software, released in September 2024, and it builds upon previous versions with new tools for procedural modeling and animation, as well as enhancements to particle, Pyro, and rigid body simulations. CG Channel also mentions that Cinema 4D 2025.2, released in April 2025, focuses on spline tools and unified simulation enhancements.
Key improvements and features of Cinema 4D 2025 include:
Procedural Modeling: New tools and workflows for creating models procedurally, including fabric weave and constellation generators.
Procedural Animation: Field Driver tag for procedural animation.
Simulation Enhancements: Improved particle, Pyro, and rigid body simulations.
Spline Tools: Enhanced spline tools for motion graphics and animation, including spline modifiers from Rocket Lasso now included for all subscribers.
Unified Simulation & Particles: Refined physics-based effects and improved particle systems.
Boolean System: Modernized boolean system for precise 3D modeling.
Particle Node Modifier: New particle node modifier for creating particle scenes.
Learning Panel: Intuitive learning panel for new users.
Redshift Integration: Maxon now includes access to the full power of Redshift rendering for all new subscriptions.
In essence, Cinema 4D 2025 is a major update that provides artists with more powerful tools and workflows for creating 3D content, particularly in the fields of motion graphics, VFX, and visualization.
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi
A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
Pixologic ZBrush Crack Plus Activation Key [Latest 2025] New Versionsaimabibi60507
Copy & Past Link👉👉
https://dr-up-community.info/
Pixologic ZBrush, now developed by Maxon, is a premier digital sculpting and painting software renowned for its ability to create highly detailed 3D models. Utilizing a unique "pixol" technology, ZBrush stores depth, lighting, and material information for each point on the screen, allowing artists to sculpt and paint with remarkable precision .
Proactive Vulnerability Detection in Source Code Using Graph Neural Networks:...Ranjan Baisak
As software complexity grows, traditional static analysis tools struggle to detect vulnerabilities with both precision and context—often triggering high false positive rates and developer fatigue. This article explores how Graph Neural Networks (GNNs), when applied to source code representations like Abstract Syntax Trees (ASTs), Control Flow Graphs (CFGs), and Data Flow Graphs (DFGs), can revolutionize vulnerability detection. We break down how GNNs model code semantics more effectively than flat token sequences, and how techniques like attention mechanisms, hybrid graph construction, and feedback loops significantly reduce false positives. With insights from real-world datasets and recent research, this guide shows how to build more reliable, proactive, and interpretable vulnerability detection systems using GNNs.
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers
Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach.
Read More:- https://www.esofttools.com/nsf-to-pst-converter.html
Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
This presentation explores code comprehension challenges in scientific programming based on a survey of 57 research scientists. It reveals that 57.9% of scientists have no formal training in writing readable code. Key findings highlight a "documentation paradox" where documentation is both the most common readability practice and the biggest challenge scientists face. The study identifies critical issues with naming conventions and code organization, noting that 100% of scientists agree readable code is essential for reproducible research. The research concludes with four key recommendations: expanding programming education for scientists, conducting targeted research on scientific code quality, developing specialized tools, and establishing clearer documentation guidelines for scientific software.
Presented at: The 33rd International Conference on Program Comprehension (ICPC '25)
Date of Conference: April 2025
Conference Location: Ottawa, Ontario, Canada
Preprint: https://arxiv.org/abs/2501.10037
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora
Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
Adobe Lightroom Classic Crack FREE Latest link 2025kashifyounis067
🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
Here's a more detailed breakdown:
Key Features and Functions:
Organization:
Lightroom Classic provides robust tools for organizing your photos, including creating collections, using keywords, flags, and color labels.
Editing:
It offers a wide range of editing tools for making adjustments to color, tone, and more.
Processing:
Lightroom Classic can process RAW files, allowing for significant adjustments and fine-tuning of images.
Desktop-Focused:
The application is designed to be used on a computer, with the original photos stored locally on the hard drive.
Non-Destructive Editing:
Edits are applied to the original photos in a non-destructive way, meaning the original files remain untouched.
Key Differences from Lightroom (Cloud-Based):
Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
Workflow:
Lightroom Classic is designed for a desktop workflow, while Lightroom is designed for a cloud-based workflow.
Connectivity:
Lightroom Classic can be used offline, while Lightroom requires an internet connection to sync and access photos.
Organization:
Lightroom Classic offers more advanced organization features like Collections and Keywords.
Who is it for?
Professional Photographers:
PCMag notes that Lightroom Classic is a popular choice among professional photographers who need the flexibility and control of a desktop-based application.
Users with Large Collections:
Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
Users who prefer a traditional workflow:
Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri
AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
How Valletta helped healthcare SaaS to transform QA and compliance to grow wi...Egor Kaleynik
This case study explores how we partnered with a mid-sized U.S. healthcare SaaS provider to help them scale from a successful pilot phase to supporting over 10,000 users—while meeting strict HIPAA compliance requirements.
Faced with slow, manual testing cycles, frequent regression bugs, and looming audit risks, their growth was at risk. Their existing QA processes couldn’t keep up with the complexity of real-time biometric data handling, and earlier automation attempts had failed due to unreliable tools and fragmented workflows.
We stepped in to deliver a full QA and DevOps transformation. Our team replaced their fragile legacy tests with Testim’s self-healing automation, integrated Postman and OWASP ZAP into Jenkins pipelines for continuous API and security validation, and leveraged AWS Device Farm for real-device, region-specific compliance testing. Custom deployment scripts gave them control over rollouts without relying on heavy CI/CD infrastructure.
The result? Test cycle times were reduced from 3 days to just 8 hours, regression bugs dropped by 40%, and they passed their first HIPAA audit without issue—unlocking faster contract signings and enabling them to expand confidently. More than just a technical upgrade, this project embedded compliance into every phase of development, proving that SaaS providers in regulated industries can scale fast and stay secure.
What Do Contribution Guidelines Say About Software Testing? (MSR 2025)Andre Hora
Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.
AgentExchange is Salesforce’s latest innovation, expanding upon the foundation of AppExchange by offering a centralized marketplace for AI-powered digital labor. Designed for Agentblazers, developers, and Salesforce admins, this platform enables the rapid development and deployment of AI agents across industries.
Email: [email protected]
Phone: +1(630) 349 2411
Website: https://www.fexle.com/blogs/agentexchange-an-ultimate-guide-for-salesforce-consultants-businesses/?utm_source=slideshare&utm_medium=pptNg
Copy & Paste On Google >>> https://dr-up-community.info/
EASEUS Partition Master Final with Crack and Key Download If you are looking for a powerful and easy-to-use disk partitioning software,
9. • Agile contribution:
– Rapid feedback during design
• DDD contribution:
– Stakeholders have a shared mental model
– …which is also represented in the code
How can we do design right?
14. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight
| Nine |Ten | Jack | Queen | King
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = Deck –› (Deck * Card)
type PickupCard = (Hand * Card) –› Hand
Sharedlanguage What DDD source code should look like
15. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight
| Nine |Ten | Jack | Queen | King
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = Deck –› (Deck * Card)
type PickupCard = (Hand * Card) –› Hand
* means a pair. Choose one from each type
list type is built in
18. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight
| Nine |Ten | Jack | Queen | King
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = Deck –› (Deck * Card)
type PickupCard = (Hand * Card) –› Hand
19. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight
| Nine |Ten | Jack | Queen | King
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = Deck –› (Deck * Card)
type PickupCard = (Hand * Card) –› Hand
20. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight
| Nine |Ten | Jack | Queen | King
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = Deck –› (Deck * Card)
type PickupCard = (Hand * Card) –› Hand
Can non-programmers provide
useful feedback?
29. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight | ...
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = ShuffledDeck –› (ShuffledDeck * Card)
type ShuffledDeck = Card list
type Shuffle = Deck –› ShuffledDeck
type PickupCard = (Hand * Card) –› Hand
30. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight | ...
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = ShuffledDeck –› (ShuffledDeck * Card)
type ShuffledDeck = Card list
type Shuffle = Deck –› ShuffledDeck
type PickupCard = (Hand * Card) –› Hand
31. In the real world
Suit
Rank
Card
Hand
Deck
Player
Deal
In the code
Suit
Rank
Card
Hand
Deck
Player
Deal
32. In the real world
Suit
Rank
Card
Hand
Deck
Player
Deal
In the code
Suit
Rank
Card
Hand
Deck
Player
Deal
ShuffledDeck
Shuffle
ShuffledDeck
Shuffle
33. In the real world
Suit
Rank
Card
Hand
Deck
Player
Deal
In the code
Suit
Rank
Card
Hand
Deck
Player
Deal
PlayerController
DeckBase
AbstractCardProxyFactoryBean
34. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight | ...
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = ShuffledDeck –› (ShuffledDeck * Card)
type ShuffledDeck = Card list
type Shuffle = Deck –› ShuffledDeck
type PickupCard = (Hand * Card) –› Hand
35. module CardGame =
type Suit = Club | Diamond | Spade | Heart
type Rank = Two |Three | Four | Five | Six | Seven | Eight | ...
type Card = Suit * Rank
type Hand = Card list
type Deck = Card list
type Player = { Name:string; Hand:Hand }
type Game = { Deck:Deck; Players: Player list }
type Deal = ShuffledDeck –› (ShuffledDeck * Card)
type ShuffledDeck = Card list
type Shuffle = Deck –› ShuffledDeck
type PickupCard = (Hand * Card) –› Hand
36. The process of building the shared
mental model is critical!
Collaboration!
66. Modeling simple values
• Avoid "Primitive Obsession"
• Simple values should not be modelled with
primitive types like "int" or "string" or "float"
"Does 'float' have
something to do
with water?"
67. Modeling constrained values
• It's rare to have an unconstrained int or string:
– An EmailAddress must not be empty,
it must match a pattern
– A PhoneNumber must not be empty,
it must match a pattern
– A CustomerId must be a positive integer
69. type EmailAddress = EmailAddress of string
Use wrapper types to keep domain concepts
distinct from their representation
type CustomerId = CustomerId of int
type String50 = String50 of string
70. type EmailAddress = EmailAddress of string
type PhoneNumber = PhoneNumber of string
type CustomerId = CustomerId of int
type OrderId = OrderId of int
Two benefits:
- Clearer domain modelling
- Can't mix them up accidentally
77. What about this?
type EmailContactInfo = {
EmailAddress : EmailAddress
IsEmailVerified : bool }
78. • Rule 1: If the email is changed, the verified flag
must be reset to false.
• Rule 2: The verified flag can only be set by a
special verification service
type EmailContactInfo = {
EmailAddress : EmailAddress
IsEmailVerified : bool }
79. "Email contact info is either Verified OR Unverified"
Listen closely to what the domain expert says...
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
80. "Email contact info is either Verified OR Unverified"
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
81. "Email contact info is either Verified OR Unverified"
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
82. Q: Is a Verified email different?
Are there different business rules?
A: Yes, it must not be mixed up with unverified.
type VerifiedEmail = VerifiedEmail of EmailAddress
"there is no problem that can’t be
solved by wrapping it in another type"
84. type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
type VerificationService =
(EmailAddress * VerificationHash) –› VerifiedEmail option
Q: Are the business rules clear now?
85. type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
type VerificationService =
(EmailAddress * VerificationHash) –› VerifiedEmail option
Those business rules are automatically enforced by the design!
87. type EmailAddress = ...
type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
type PersonalName = {
FirstName: String50
MiddleInitial: String1 opt
LastName: String50 }
type Contact = {
Name: PersonalName
Email: EmailContactInfo }
88. type EmailAddress = ...
type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
type PersonalName = {
FirstName: String50
MiddleInitial: String1 opt
LastName: String50 }
type Contact = {
Name: PersonalName
Email: EmailContactInfo }
89. type PersonalName = {
FirstName: String50
MiddleInitial: String1 opt
LastName: String50 }
type Contact = {
Name: PersonalName
Email: EmailContactInfo }
type EmailAddress = ...
type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
90. type PersonalName = {
FirstName: String50
MiddleInitial: String1 opt
LastName: String50 }
type Contact = {
Name: PersonalName
Email: EmailContactInfo }
type EmailAddress = ...
type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
91. type PersonalName = {
FirstName: String50
MiddleInitial: String1 opt
LastName: String50 }
type Contact = {
Name: PersonalName
Email: EmailContactInfo }
type EmailAddress = ...
type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
92. type PersonalName = {
FirstName: String50
MiddleInitial: String1 opt
LastName: String50 }
type Contact = {
Name: PersonalName
Email: EmailContactInfo }
type EmailAddress = ...
type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
93. type PersonalName = {
FirstName: String50
MiddleInitial: String1 opt
LastName: String50 }
type Contact = {
Name: PersonalName
Email: EmailContactInfo }
type EmailAddress = ...
type VerifiedEmail =
VerifiedEmail of EmailAddress
type EmailContactInfo =
| Unverified of EmailAddress
| Verified of VerifiedEmail
94. Summary
• Represent the shared mental model in code
– The developers should become domain experts too
– Write code collaboratively to build the shared
mental model
• Use the power of a composable type system
– Options instead of null
– Wrappers for constrained types
– Choice types rather than inheritance or flags
– Static types give you confidence when refactoring
95. More "Domain Modeling Made Functional" at
– fsharpforfunandprofit.com/ddd
Thanks!
Twitter: @ScottWlaschin