Exploring Functional Programming Languages vs Object-Oriented Programming Languages | by Isreal | Jul, 2023



Note: This article is quite lengthy but it’s worth your time to deeply understand the differences between these concepts in programming. Enjoy reading and coding alongside.

The choice between functional programming languages and object-oriented programming languages is a topic of debate among software developers. Both paradigms offer distinct approaches to programming, emphasizing different principles and design philosophies. In this article, we will delve into the characteristics, benefits, and use cases of functional programming languages and object-oriented programming languages. We will also explore code snippets to demonstrate the key concepts and features of each paradigm.

  1. Understanding Functional Programming Languages.
  2. Exploring Object-Oriented Programming Languages.
  3. Code Snippets: Functional Programming Concepts.
  4. Code Snippets: Object-Oriented Programming Concepts.
  5. Choosing the Right Paradigm for the Task.
  6. Conclusion.
  7. Reference

Key Characteristics and Principles:

Immutability: In functional programming, immutability refers to the practice of creating data structures that cannot be modified after they are created. This prevents accidental changes to data and promotes a safer and more predictable programming style.

Here’s an example of this:

Pure Functions and Avoidance of Side Effects: Pure functions are functions that always produce the same output for the same input and do not cause any side effects, such as modifying external state or variables. They rely only on their inputs and return a new value without modifying the existing data.

Here’s a code snippet:

First-Class and Higher-Order Functions: In functional programming, functions are treated as first-class citizens, meaning they can be assigned to variables, passed as arguments to other functions, and returned as values from other functions. Higher-order functions are functions that can accept other functions as arguments or return functions as results.

Check out this code snippet:

// First-class function example
const greet = function(name)
console.log(`Hello, $name!`);

greet("Alice"); // Output: Hello, Alice!

// Higher-order function example
function multiplier(factor)
return function(number)
return number * factor;

const double = multiplier(2);
console.log(double(5)); // Output: 10

These characteristics and principles in functional programming promote code clarity, reusability, and make it easier to reason about the behavior of the code. By embracing immutability, pure functions, and higher-order functions, developers can write more reliable and maintainable code.

Benefits and Advantages:

Enhanced Modularity and Reusability: Functional programming promotes modular code design by emphasizing the separation of concerns and the use of pure functions. This allows developers to break down complex problems into smaller, reusable functions that can be composed together to solve larger tasks.

// Example of modular and reusable functions
function add(a, b)
return a + b;

function multiply(a, b)
return a * b;

function calculateTotal(price, quantity)
const subTotal = multiply(price, quantity);
const tax = multiply(subTotal, 0.1);
const total = add(subTotal, tax);
return total;

const totalPrice = calculateTotal(10, 5);
console.log(totalPrice); // Output: 55

Easy Parallelization and Concurrency: Functional programming promotes writing code that is less dependent on shared state, making it easier to parallelize and execute code concurrently. With functional programming, you can write code that is naturally more thread-safe and avoids common concurrency issues.

// Example of modular and reusable functions
function add(a, b)
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Groundbreaking 3D Printing Technologies a “Game Changer” for Exploring and Manufacturing New Materials

High-Throughput Combinatorial Printing

Higher-throughput combinatorial printing illustration. The new 3D printing strategy, substantial-throughput combinatorial printing (HTCP), greatly accelerates the discovery and creation of new resources. Credit: College of Notre Dame

A novel 3D printing method identified as significant-throughput combinatorial printing (HTCP) has been produced that noticeably accelerates the discovery and manufacturing of new products.

The procedure entails mixing a number of aerosolized nanomaterial inks during printing, which enables for good control around the printed materials’ architecture and local compositions. This strategy generates products with gradient compositions and properties and can be utilized to a large array of substances like metals,

The time-honored Edisonian trial-and-error process of discovery is slow and labor-intensive. This hampers the development of urgently needed new technologies for clean energy and environmental sustainability, as well as for electronics and biomedical devices.

“It usually takes 10 to 20 years to discover a new material,” said Yanliang Zhang, associate professor of aerospace and mechanical engineering at the University of Notre Dame.

“I thought if we could shorten that time to less than a year — or even a few months — it would be a game changer for the discovery and manufacturing of new materials.”

Now Zhang has done just that, creating a novel 3D printing method that produces materials in ways that conventional manufacturing can’t match. The new process mixes multiple aerosolized nanomaterial inks in a single printing nozzle, varying the ink mixing ratio on the fly during the printing process. This method — called high-throughput combinatorial printing (HTCP) — controls both the printed materials’ 3D architectures and local compositions and produces materials with gradient compositions and properties at microscale spatial resolution.

His research was published on May 10, 2023, in the journal Nature.

The aerosol-based HTCP is extremely versatile and applicable to a broad range of metals, semiconductors, and dielectrics, as well as polymers and biomaterials. It generates combinational materials that function as “libraries,” each containing thousands of unique compositions.

Combining combinational materials printing and high-throughput characterization can significantly accelerate materials discovery, Zhang said. His team has already used this approach to identify a semiconductor material with superior thermoelectric properties, a promising discovery for energy harvesting and cooling applications.

In addition to speeding up discovery, HTCP produces functionally graded materials that gradually transition from stiff to soft. This makes them particularly useful in biomedical applications that need to bridge between soft body tissues and …

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Pittsburgh’s Town Theatre revisits 25-yr-outdated enjoy exploring media, technology

Town Theatre in Pittsburgh is bringing back a participate in that initial appeared on its stage 25 decades in the past.

“The Medium,” a postmodern deconstruction of the musings of author/thinker Marshall McLuhan, will operate from Jan. 22 as a result of Feb. 13 on the City Theatre Principal Stage on Pittsburgh’s South Aspect.

The 3rd present of the 2021-22 membership season is presented by New York Town-dependent SITI Business.

“The production was initially produced in 1993 and conceived to discover the then-burgeoning discipline of technologies by means of the lens of Marshall McLuhan,” mentioned Anne Bogart, SITI Organization co-creative director, who conceived the engage in. “We observe the renowned Canadian philosopher of media scientific studies on an Alice in Wonderland-like journey as a result of the landscape of his profound insights about the outcomes of media upon the human working experience.

“Now, just about 30 many years later on, the enjoy seems even more pertinent to the world that we inhabit right now than it did when we first created it,” she claimed.

Initial noticed at Town Theatre in 1996, “ ‘The Medium’ explores the impact of media and emerging technologies on our perceptions, our psyches, and our private life,” according to a release.

“ ‘The Medium’ is structured on the perfectly-known narrative structure of ‘the hero’s journey,’ which can be identified in tales and fairy tales from all-around the entire world and all over heritage,” Bogart explained. “Our hero is based mostly on the fantastic Canadian thinker Marshall McLuhan who, in the 1960s, was able to predict what would transpire to us when the media, digital technological innovation and the online would dominate our life.”

By the tv screen

In a bewildered point out right after struggling a stroke, the character of McLuhan finds himself transported, like “Alice By way of the Looking Glass,” into the earth of tv.

Not able to speak, McLuhan “moves from channel to channel, dealing with firsthand the success of his worst and most insightful dreams,” Bogart reported.

“The scenes in ‘The Medium’ are offered in the form of television genres, like vintage kinds like a Western, a hospital drama, a recreation exhibit, a loved ones exhibit, a chat show and so on,” she extra. “Each genre variety features as a container for different insights and themes from Marshall McLuhan’s writings. McLuhan himself, our principal character, travels as a result of this Tv set landscape.”


Courtesy of SITI Firm

Will Bond will seem in the SITI Company production of “The Medium,” Jan. 22-Feb. 13 at City Theatre in Pittsburgh.


Directed by Bogart, “The Medium” features performers William Bond, Gian-Murray Gianino, Ellen Lauren, Barney O’Hanlon, Violeta Picayo and Stephen Duff Webber.

“One can see the irony in the simple fact that this prescient thinker, who spoke and wrote so eloquently and playfully on the media and culture, need to go through the lack of ability to converse,” Bond stated. “In this way, just one may possibly call him a present day-day Cassandra

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Exploring Quantum Technology: Qiskit and RasQberry

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Proponents of quantum technology believe its will change the world. Others remain skeptical, as they do of technologies like fusion energy.

Speaking at a quantum developers’ forum, IBM Distinguished Engineer Jan-Rainer Lahmann retraced the history of quantum computing, reviewing IBM’s hardware and development roadmaps and describing the ingredients of “Raspberry Pi quantum”.

The history of quantum computing goes back four decades to a conference where the Nobel laureate Richard Feynman introduced the idea of simulating quantum mechanical systems on a traditional computer. At the time, this required a significant computational resources. Even with Moore’s Law scaling, it was clear to Feynman and many others that the road to quantum computing needed to be pursued. “What if we built completely different kinds of computers that made quantum mechanics’ effects such as superposition, interference, entanglement, directly accessible and controllable?” Lahmann recalled Feynman as asking.

Lahmann continued: “With such a different kind of computer, it should be much easier to simulate quantum mechanical systems. I think this idea is very clear, and it makes perfect sense.”

Since then, many scientists and engineers have pursued various approaches to building actual quantum computers. Feynman’s basic idea was that a quantum mechanical system, with several subsystems, for each qubit, provides as many traditional bits as would be needed on a traditional computer to express that state of a quantum mechanical system. For example, 2 qubits are equivalent to 512 bits, 10 qubits are equivalent to 16 kB and so on with exponential growth. Also understood at the time was how difficult it was to build large computers that could handle qubit demands.

“If you have a quantum mechanical system, you need a huge traditional computer to simulate the same things; if you have a traditional computer, then you can express this amount of information on a quantum computer under certain conditions,” said Lahmann.

Increasing the speed of a quantum computer only makes sense for very specific problems. In an example, Lahmann described how long a quantum computer and a traditional computer would take to multiply two numbers. P and Q are integers with 2,048 bits. On a traditional computer, it takes a few milliseconds. And on a fairly small and noisy quantum computer, it would take an estimated 75 seconds.

But as Lahmann noted, a similar but much more complicated problem illustrates the potential and speed of quantum computers. “We don’t want to multiply two numbers, we want to factor a large number. So we have a number of 2,048 bits and we want to derive the prime factors of that number. This is the core of our two big asymmetric encryption schemes. This takes a long time on the traditional computer, on the order of years – this takes a couple of billion CPU cores on a traditional computer.”

Citing Peter Shor’s quantum algorithm, if “we have a large enough quantum computer, this could be reduced to a few hours. That vividly

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