Low-Level vs High-Level Programming Languages

• A program is a collection of detailed instructions that provides direction to a computer to perform a specific task.
• A programming language defines a set of instructions compiled together for the CPU to use to perform a task.
• Computers understand only binary numbers (0, 1).
• Programming languages are classified into two levels based on their proximity to computers or human understanding.

Low-Level Languages

• These are programming languages closer to the hardware and architecture of a computer.

Machine Language

• The lowest-level programming language
• Consists of binary code (0s and 1s)
• Directly corresponds to instructions executed by the computer's CPU
• Each instruction corresponds to a specific operation the CPU can perform
• Writing programs is extremely tedious and error-prone, making it impractical for most software development.

Assembly Language

• A slightly higher-level language than machine language
• Uses symbolic names (mnemonics) for instructions and memory addresses instead of binary code
• Mnemonics are easier for humans to understand and remember than raw binary code
• It is specific to the computer's architecture and requires a translator called an assembler to convert it into machine code
• Provides a more human-friendly syntax for programming, but still requires a deep understanding of computer architecture.

High-Level Languages

• These are designed to be more human-readable and developer-friendly compared to low-level languages like machine or assembly language
• Provide a level of abstraction from the hardware and are closer to natural language making it easier for programmers to write, read, and maintain code
• Offers built-in features and abstractions that simplify complex tasks allowing developers to focus on solving problems rather than dealing with low-level hardware details

Translators

• A programming language processor that converts a computer program from high-level language to low-level language
• Translators take a program written in source code and converts it into machine code.
• They can discover and identify errors during translation.

Assembler

• A translator used to translate assembly language to machine language
• Translates a low-level language (assembly language) to an even lower-level language (machine code)
• Machine code can be directly understood by the CPU.
• Examples include: Fortran Assembly Program, Macro Assembly Program, Symbolic Optimal Assembly Program.

Compiler

• A translator used to convert high-level programming language to low-level programming language
• Converts a whole program in one session and reports errors detected after the conversion
• Translating high-level code to lower-level code all at once and then saves it to memory
• It is both processor-dependent and platform-dependent.
• There are special compilers like the cross-compiler and source-to-source compiler
• Before choosing a compiler, identify first, the Instruction Set Architecture (ISA), the operating system (OS), and the programming language being used to ensure compatibility.
• Examples include: Microsoft Visual Studio, GNU Compiler Collection (GCC), C/C++

Interpreter

• A translator used to convert high-level programming language to low-level programming language
• It converts a program one line at a time and reports errors detected at once
• Translating and reporting errors line by line makes it easier to detect them.
• It's generally faster because it immediately executes the converted code
• It's often used as a debugging tool for software development as it can execute a single line of code at a time
• It is more portable than a compiler as it is not processor-dependent, so it can work between hardware architectures
• Examples: PHP, Python, and JavaScript

Summary

• Compilation translates code all at once.
• Interpretation translates code line-by-line.
• Assembly translates into machine code.
• Interpreters and Assemblers execute programs directly
• Compilers create executable file for later execution
• Compilation generally results in faster execution speeds
• Interpretation execution speed is slower since code must be translated at runtime
• Assembler execution speed is fast due to direct execution
• Compilers report errors after full compilation
• Interpreters report errors line-by-line
• Assemblers report errors during assembly
• C, C++, and Java (bytecode) are examples of languages using compilation
• Python, Ruby and JavaScript use interpreters
• x86 Assembly and ARM Assembly use Assemblers
• Compilation is used for large programs requiring optimized performance
• Interpretation is often favored for scripting or quick development processes
• Assembly is used for low-level programming on specific hardware

Problem Solving

• Involves identifying challenges and finding effective solutions
• Structured problem-solving techniques ensure efficient and error-free results.

Steps of Problem Solving

• Identify the Problem, eg "The WI-FI is not working"
• Understand the Problem. Gather relevant information. Check if other devices can connect or if the router is powered on.
• Identify Alternative Solutions by brainstorming multiple ways to solve the problem, such as restarting the router, checking cables, and calling customer support.
• Select and Evaluate the Best Solution by choosing the most effective one. Restarting the router is a quick and common fix.
• Implement the Solution by following step-by-step instructions. Turn off the router, wait 30 seconds, and turn it back on.
• Evaluate the Solution, and check if the problem is resolved. If not, return to the earlier steps and try another approach or move on to checking cables

Algorithmic Solutions

• Well-defined instructions for carrying out a specific task.
• Solutions reached by completing a sequence of steps
• Predictible and always produces the same result

Heuristic Solutions

• Employs a self-learning approach based on knowledge and experience
• Often uses the process of trial and error
• Does not always provide the best solution but helps to find a workable one quickly

Feature Summary of Algorithmic and Heuristic Solutions

• Algorithmic solutions always produce the same outcome whereas Heuristic solutions can vary based on experience
• Efficiency can be optimized when using algorithmic solutions but it may take longer using a trial and error approach with heuristic solutions
• Algorithmic solutions use defined sequences of actions whereas heuristic is flexible
• Algorithmic solutions can be used when writing sorting algorythms or solving arithmetic formulas
• Heuristic soluttions are used in decision making in real life and AI-based learning

Problem Solving Tools in Programming

• Pseudocode (a human-readable representation of the logic)
• Flowcharts (a graphical representation of the steps).

Pseudocode

• Writing algorithms in a structured format using plain English that resembles a programming language without specific syntax rules
• It helps programmers logically plan their code before starting the actual programming process.

Characteristics

• Uses structured language (not actual programming syntax).
• Does not follow strict syntax rules.
• Makes it easy to convert into real code.
• Improves understanding and debugging before coding.

Flowchart

• A visual representation of an algorithm that uses symbols to represent different steps in the process.

Characteristics

• They make complex logic easier to understand.
• Help in debugging and refining algorithms.
• Provide a clear sequence of execution.
• Useful for team discussions.

Problem Solving in Computers

• Involves designing efficient algorithms to solve real-world problems.
• The three primary approaches used in programming are:
  • Computational Thinking
  • Logical Thinking
  • Repetitive Thinking (Iteration & Recursion)

Computational Thinking

• Problem-solving that breaks down problems into smaller steps that a computer can process.
• Decomposition: Breaking the problem into smaller, manageable parts.
  • Pattern Recognition: Finding similarities in different problems
  • Abstraction: Focusing on important details while ignoring unnecessary ones.
  • Algorithm Design: Creating a step-by-step solution to solve the problem.

Logical Thinking

• Involves making decisions based on conditions.
• Boolean Logic (True/False Decision)
• Conditional Statements: IF-ELSE, SWITCH-CASE
• Comparison and Logical Operators: >, <, ==, &&, ||

Repetitive Thinking

• Involves executing the same task multiple times until a condition is met.
• With Loops (Iteration), a process is repeated a fixed number of times or until a condition is met.
• With Recursion, a function calls itself until a base condition is met.

Approach To Solving a Problem in Programming

• Define the problem and develop a solution.
• Design a Python program and translate it into code
• Test the program and compare it with the expected outputs
• Locate errors and then correct

Python

• It is a high-level, interpreted programming language known for its simplicity, readability, and versatility
• It was created by Guido van Rossum and first released in 1991
• It is widely used in web development, data science, artificial intelligence, automation, and more.
• Named after Monty Python's Flying Circus

Strengths of Python

• Easy to Learn and Use due to its simple syntax
• Extensive Libraries and Frameworks such as NumPy, Pandas, TensorFlow, and OpenCV
• Cross-Platform Compatibility, that ensures programs can run on Windows, macOS, and Linux
• Interpreted Language and the ability to execute it directly
• Large Community Support and a large community for help
• Versatility across use cases in web development, AI, ML, data analysis, scripting, among others

Weaknesses of Python

• Slower Execution than compiled languages because it is Interpreted
• High Memory Consumption, making it not ideal for memory-intensive tasks
• Not the best for Mobile Development because it is less commonly used in those applications
• Global Interpreter Lock (GIL) which limits multi-threading efficiency
• Weak in Database Access Layers compared to JDBC in Java

IDLE

• Python's default Integrated Development and Learning Environment (IDLE), comes bundled with Python
• Provides a simple yet effective interface for writing, running, and debugging Python programs
• Useful for beginners due to its ease of accessibility and use

Features

• Python Shell (Interactive Mode)
• Script Editor (allowing file editing)
• Debugger for Error Detection
• Syntax Highlighting
• Auto-Completion & Indentation
• Find and Replace Functionality
• Customizable setting

Basic Python Commands

• print('text')
• print(variable_name)
• print('text', variable_name')
• print('text', 'text',..., 'text',)
• print('text', 'text',..., 'text', variable1, variable2,..., variableN)
• Variable_name = input("Prompt Message")

Basic Python Arithmetic Operators

• x + y Sum Integer
• x - y Difference Integer
• x * y Product Integer
• x / y Division FLoat
• x // y Integer division Integer
• x % y Remainder of x // y Integer
• -x Negative x Integer
• abs(x) Absolute value of x Integer
• x**y x to the power y Integer

Explore the differences between machine language, assembly language, and high-level languages. Understand their advantages, appropriate use cases, and the importance of translators. Identifying the best language level based on project needs and hardware interaction.