CSC1024 Week 01: Programming Principles

• Programming Principles (CSC1024) - Week 01, taught by Dr. Danish Mahmood Khan, Senior Lecturer at the Academic Staff Office (UW 3-2)
• Contact: [email protected]

Dr Danish Mahmood Khan's Research Interests:

• Neuroscience
• Electroencephalography
• Signal Processing
• Brain Disorders
• Artificial Intelligence
• Image Processing and Computer Vision

Course Software

• Python 3.x is used for developing and debugging software.
• All assessments will be verified using Python 3.x.
• Optional IDEs: Anaconda Cloud, Pycharm, VS Code, SPYDER.
• Download: https://www.python.org/downloads/

Course Learning Outcomes

• CLO 1: Explain basic programming concepts using specific programming language terminology.
• CLO 2: Design computational solutions compliant with the coding standards of a specific programming language.
• CLO 3: Implement computational solutions using decision statements, control structures, and user-defined functions in a specific programming language.

Assessment Dates and Mark Allocation:

• Quiz 1: 25% of the final grade, Week 3 (February 26th, 2025), covers weeks 1-2
• Quiz 2: 25% of the final grade, Week 6 (March 20th or 21st, 2025), covers weeks 3-6
• Final Project: 50% of the final grade, released in Week 4, submission on March 23rd, 2025, demonstration during a lab session in Week 7

Course Requirements

• Students must pass both the coursework and the final project components.
• The passing grade is 40/100.
• Lab sessions begin in Week 2.

Programming Concepts

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

Low-Level Languages

• Closer to hardware and architecture.
• Machine language:
  • It is the lowest-level programming language, consisting of binary code (0s and 1s).
  • Each instruction corresponds to a specific CPU operation.
  • Writing programs in machine language is tedious, error-prone, and impractical.
• Assembly language:
  • It is a slightly higher-level language than machine language.
  • It uses symbolic names (mnemonics) for instructions and memory addresses.
  • Assembly language requires an assembler to convert it into machine code.
  • It provides more human-friendly syntax but requires deep understanding of computer architecture.

High-Level Languages

• Designed to be more human-readable and developer-friendly.
• They provide a level of abstraction from the hardware, making it easier to write, read, and maintain code.
• High-level languages offer built-in features and abstractions for simplifying complex tasks, allowing developers to focus on solving problems rather than hardware.

Translators

• Translators convert computer programs from high-level to low-level languages.
• They take source code and convert it into machine code, identifying errors during translation.
• Assembler:
  • Translates assembly language to machine language.
• Compiler:
  • Converts the whole program in one session.
  • Reports errors detected after the conversion.
  • Compilers are processor and platform-dependent.
• Interpreter:
  • Converts the program one line at a time.
  • Reports errors immediately, making debugging easier.
  • Interpreters are generally more portable.

Summary of Translators

• Compiler: translates the whole program at once, creates an executable file, has fast execution after compilation, reports errors after full compilation, and is commonly used in C, C++, and Java (bytecode) for large programs when performance is key.
• Interpreter: translates line-by-line, executes the program directly, is slower runtime, reports errors line-by-line, and is used in Python, Ruby, and JavaScript for scripting.
• Assembler: translates assembly language to machine code, directly generates machine code that can be executed, is fast, reports errors during assembly, is used in x86 Assembly and ARM Assembly, and in for low-level programming on particular hardware.

Top Programming Languages (based on the TIOBE Index):

• The TIOBE Index measures programming language popularity and is updated monthly.
• It ranks by the number of skilled engineers, courses, and third-party vendors using data from major websites.
• Python is the most popular, with a rating of 23.28%.
• C++ has a rating of 10.29%.
• Java has a rating of 10.15%.
• C has an 8.86% rating.
• C# has a 4.45% rating.

Problem Solving

• Problem-solving is a crucial skill that involves identifying challenges and finding effective solutions.
• Structured problem-solving techniques ensure efficient and error-free code in programming.

Steps of Problem Solving

• Identify the Problem
• Understand the Problem
• Identify Alternative Solutions
• Select the Best Solution
• Implement the Solution
• Evaluate the Solution

Approaches to problem solving

• Algorithmic Solutions:
  • Uses well-defined instructions to perform a particular job.
  • It produces a predictable and deterministic outcome.
• Heuristic Solutions:
  • Employs a self-learning approach based on knowledge and experience.
  • It may not provide the best solution but helps find a workable solution quickly.

Algorithmic Solutions vs Heuristic Solutions

• Predictability: Algorithmic is always the same, Heuristic will vary on experience
• Steps: Algorithmic has defined sequence, Heuristic is flexible an adaptable
• Time Efficiency: Algorithmic can be optimised, Heuristic may take longer to trial and error
• Examples Algorithmic are sorting algorithims and arithmetic formulas, Heuristic is decision making and Al-based learning

Problem-Solving Tools in Programming:

• Pseudocode: Human-readable representation of the logic.
• Flowcharts: Graphical representation of the steps.

Pseudocode

• It is a way of writing algorithms in a structured format using plain English, resembling a programming language but without specific syntax rules.
• Characteristics:
  • Uses structured language.
  • Does not follow strict syntax rules.
  • Makes it easy to convert into real code.
  • Improves understanding and debugging before coding.

Flowcharts

• A flowchart is a visual representation of an algorithm.
• Characteristics:
  • It is a way of writing algorithms in a structured format using.
  • They help debugging and refining algorithms.
  • They provide a clear sequence of execution.
  • Useful for team discussions.

Problem Solving in Computers

• Problem-solving in computers involves designing efficient algorithms to solve real-world problems.
• The three primary approaches: computational thinking, logical thinking, and repetitive thinking

Computational Thinking

• A problem-solving approach that involves breaking complex problems into smaller steps.
• It involves:
  • Decomposition: Breaking down the problem into smaller 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.

Logical Thinking

• Decision-making involves the use of computers, based on condition
• Boolean Logic: True/False Decision
• Conditional Statements: IF-ELSE, SWITCH-CASE
• Comparison and Logical Operators

Repetitive Thinking

• Repetitive thinking involves performing the same job several times until a condition is achieved.
• It uses:
  • Loops (Iteration): Repeating a process multiple times
  • Recursion: When a function calls itself

Approach to solving a problem in programming

• Programming cycle: think, code, test, debug, repeat
  • STEP 1: THINK → Problem Definition, Solution Development
  • STEP 2: CODE → Designing the Python program, Writing the code
  • STEP 3: TEST → Testing the program, Checking the outputs
  • STEP 4: DEBUG → Finding the errors, Correcting the errors
  • STEP 5: REPEAT → STEP 1

Python

• Python is a high-level, interpreted programming language.
• Python has simplicity, readability, and versatility.
• Python was created by Guido van Rossum and first released in 1991.
• Python is widely used in web development, data science, artificial intelligence, and automation.

Python Origin

• Python derived it's name from :Monty Python's Flying Circus.
• Python aims to be easy to use yet powerful.

Python Strengths

• It's Easy to Learn and Use due to its simple syntax
• A large range on extensive Libraries and Frameworks
• Has Cross-Platform Compatibility
• Interpreted Language does not need compilation
• Dynamic Typing
• Large Community Support
• Versatility

Python Weaknesses

• Slower Execution due to it being an interpreted language
• High Memory Consumption, not ideal for memory-intensive tasks
• it's Not Ideal for Mobile Development
• Has a Global Interpreter Lock (GIL)
• Weak in Database Access Layers

Python IDLE

• IDLE is the default Integrated Development and Learning Environment bundled with Python.
• IDLE provides an easy way for writing, running, and debugging Python programs.
• IDLE particularly serves beginners because of it's simplicity and ease of use.
• Features:
  • Python Shell (Interactive Mode)
  • Script Editor (File Editing Mode)
  • Debugger for Error Detection
  • Syntax Highlighting
  • Auto-Completion & Indentation
  • Find and Replace Functionality
  • Customizable Settings

Basic Python Commands

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

Basic 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 programming principles in CSC1024 with Dr. Danish Mahmood Khan. This introductory week covers essential programming concepts and software setup using Python 3.x. Course outcomes include explaining basic concepts and designing computational solutions.