Ruby vs C++

Ruby is one of the most popular languages for developing web sites. As a result, there's an abundant amount of documentation, sample code, and libraries available for learning the language and getting your project up and running. The most popular features are just 'gem install' away. Additionally, it is easier to find Ruby jobs because of this.

Ruby has a very clean syntax that makes code easier to both read and write than more traditional Object Oriented languages, such as Java. For beginning programmers, this means the focus is on the meaning of the program, where it should be, rather than trying to figure out the meaning of obscure characters.

presidents = ["Ford", "Carter", "Reagan", "Bush1", "Clinton", "Bush2"]
for ss in 0...presidents.length
    print ss, ": ", presidents[presidents.length - ss - 1], "\n";
end

Ruby has a large ecosystem of tools and libraries for just about every use. Such as ORMs (Active Record, DatabMapper), Web Application Frameworks(Rails, Sinatra, Volt), Virtualization Orchestration(docker-api, drelict), CLI tools(Thor, Commando), GUI Frameworks(Shoes, FXRuby) and the list goes on. If you can think of it, there is probably a gem for that ( and if not you can create your own and share with the community).

The Ruby language is equipped with the necessary features to learn the essence of algorithms.

In online playground environments like ideone.com, measures have been taken to prevent beginners from going astray by restricting the use of external libraries such as Python's NumPy and SymPy.
Even in such constrained Ruby execution environments, the required features for learning algorithms are fully available.

Many of the algorithms that should be learned are documented in the book "Hello Ruby: Adventures in Coding." For example, the cake serving problem in the book leads to topological sorting, which is a graph theory concept useful in project management for creating Gantt charts.

To evaluate the effectiveness of algorithms with a level of complexity comparable to topological sorting,
it is necessary to be able to solve mathematical computation problems up to the high school level easily.
As shown in the table below, using only Ruby's standard library, it is possible to solve high school-level math problems effortlessly.
However, other programming languages may not be able to perform such computations in online playground environments.

To experience the superior performance of algorithms, it is important to challenge oneself by reimplementing good algorithms. Ruby's standard library includes implementations of excellent algorithms. For instance, the algorithm for solving linear equations, which has been widely known since the era of Fortran, is used within the code of SolvingLinearEquations through the "/" operator. Reimplementing code from Ruby's standard library serves as an excellent learning resource with high reusability and efficiency.

The SolvingLinearEquations function mentioned above demonstrates the benefits of duck typing and forced type conversion between objects of different types in arithmetic operations. While Rust also has features like duck typing, the implementation of "forced type conversion" is still far from being realized.

# Title: "(1) Cake Serving Procedure Problem"
require 'tsort'

class Hash
  include TSort
  alias tsort_each_node each_key
  def tsort_each_child(node, &block)
    fetch(node).each(&block)
  end
end

puts 'Tasks'
task_names = {
  'A' => 'Arrange the plates.',
  'B' => 'Set the spoons.',
  'C' => 'Place the birthday cake on the table.',
  'D' => 'Spread the tablecloth.'
}
p task_names

puts 'Preceding Tasks'
preceding_tasks = {
  'A' => ['D'],
  'B' => ['C', 'A'],
  'C' => ['A', 'D'],
  'D' => []
}

steps = preceding_tasks.strongly_connected_components
puts 'The appropriate steps are as follows:'
steps.each do |task_candidates|
  p task_candidates.map { |task| [task, task_names[task]] }
end

p "#(2) Equation Solving Rule"
def SolvingLinearEquations(y, a, b)
   x = (y - b) / a
end

p "(2-1) Real Solution", SolvingLinearEquations(1.0, 5, 0.5)
# => 0.1

p "(2-2) Fraction Solution", SolvingLinearEquations(Rational(1, 1), Rational(5, 1), Rational(1, 2))
# =>  (1/10)

p "(2-3) Imaginary Solution", SolvingLinearEquations(1 + 1i, 5, 1.0 / (2 + 2i))
# => (0.15+0.25i)

p "(2-4) Complex & Fraction Solution", SolvingLinearEquations(Rational(1 + 1i, 1), Rational(5, 1), Rational(1, 2 + 2i))
# => ((3/20)+(1/4)*i)

p "(2-5) Matrix Solution with Large Integers", 
   SolvingLinearEquations(Matrix[[Rational(1234567890123456789890, 1), Rational(0, 1)]],
                                                Matrix[[Rational(1234567890123456789890, 1), Rational(1234567890123456789890 * 2, 1)],
                                                             [Rational(1234567890123456789890, 1), Rational(1234567890123456789890 * 3, 1)]],
                                                Matrix[[Rational(1234567890, 1), Rational(123456789, 1)]] )
# => Matrix[[(3703703670366790122789/1234567890123456789890), (-2469135780244567900789/1234567890123456789890)]]

p "(2-7) Matrix Solution with Large Integers, Complex Numbers, and Fractions", 
     SolvingLinearEquations(Matrix[[Rational(1234567890123456789890, 1i), Rational(0, 1)]],
                                                 Matrix[[Rational(1234567890123456789890, 1), Rational(1234567890123456789890 * 2, 1i)],
                                                               [Rational(1234567890123456789890, 1), Rational(1234567890123456789890 * 3, 1i)]],
                                                Matrix[[1234567890, 0 + 1i]] )
# => Matrix[[((-3703703671/1234567890123456789890)-(3/1)*i), ((2469135781/1234567890123456789890)+(2/1)*i)]]

Lays out an easy to follow and opinionated MVC pattern that teaches best practices through necessity.

It's the fore-runner and trend setter for TDD.

Object oriented programming is one of the most important concepts in programming.

Meta-programming provides efficiency and freedom.

No indentation increase development efficiency.

C++ is a large language with an even larger community and following. It has libraries for every kind of task that is possible to do with C++

Allows puting large arrays on the "heap" to avoid "stack overflow".

Teaches you to leverage object oriented programming.

Both open source compilers (such as Clang and GCC), and proprietary ones (like Intel's and Microsoft's) are very good at analyzing program flow and program optimization. This is mostly due to the widespread usage of C/C++ applications running everything from mobile/desktop/server Operating Systems, to search engines and webserver software, and the demand for performance.

The great STL is the most powerful Data Structure and Algorithms Library. It would benefit you very much in problem solving, your main main way to love programming. The code is much compact compared to Java and C#. No unnecessary classes are in your way; yet when you need classes they are available unlike C. The code runs very fast.

Teaches data types, low-level program flow and the so common C-style syntax while not being as much of a pain as C itself.

The functionalities keep growing throughout the years. C++11 gave us a soft type of garbage collecting with the smart pointers.

Most C code will work as C++.

Because C++ (and its precursor C) are "lower level" than a lot of popular programming languages they are also faster at executing code than Java or C# which require VMs and garbage collection threads.

C++ is mature and everything has standardized library.