1. Introduction to Programming Languages
A programming language (PL) is a formal language comprising a set of instructions used to produce various kinds of output. Programming languages are used to implement algorithms. They serve as the vehicle for communication between humans and computers.
Key Components
- Syntax: The set of rules that defines which combinations of symbols are considered a correctly structured program in that language. (e.g., semicolons at the end of statements, proper use of brackets).
- Semantics: The meaning of the code, defining how a program is expected to behave when executed.
- Pragmatics: The aspects of a language concerned with its practical use, such as its suitability for a specific domain, ease of writing, and maintenance.
Language Levels
- Machine Language (Low-Level): Instructions directly executed by the CPU, consisting of binary code (1s and 0s). Extremely fast but difficult for humans to read and write.
- Assembly Language (Low-Level): Uses mnemonics (e.g.,
ADD,MOV) that correspond one-to-one with machine language instructions. Requires an Assembler to translate. - High-Level Language (HLL): Uses syntax closer to natural human language (e.g., C, Java, Python). Easier to read, write, and maintain. Requires a Compiler or Interpreter for execution.
2. Language Translation and Execution
Programs written in high-level languages must be translated into machine code for the computer to execute them.
| Process | Tool | Description |
|---|---|---|
| Compilation | Compiler | Translates the entire source code into machine code (object code) before execution. The resulting executable runs quickly. |
| Interpretation | Interpreter | Executes source code line by line without a prior compilation step. Slower execution but allows for easier debugging and dynamic code modification. |
| Hybrid (e.g., Java, C#) | Compiler + Virtual Machine (VM) | Source code is first compiled into an intermediate form (e.g., bytecode). The VM (e.g., JVM for Java) then interprets the bytecode, offering platform independence. |
3. Programming Paradigms
A programming paradigm is a fundamental style of computer programming, not a specific language.
A. Imperative Programming
Focuses on how a program operates by describing a sequence of steps (statements) that change the program's state.
- Procedural Programming: Organizes code into procedures (functions or routines) that perform computations.
- Examples: C, Pascal, Fortran.
- Object-Oriented Programming (OOP): Organizes code around objects, which are instances of classes.
- Examples: Java, C++, Python, C#.
B. Declarative Programming
Focuses on what the program should accomplish without describing all the explicit control flow.
- Functional Programming: Treats computation as the evaluation of mathematical functions and avoids changing state and mutable data. Key concepts include first-class functions, immutability, and recursion.
- Examples: Haskell, Scheme, Lisp, functional features in Python/JavaScript.
- Logic Programming: Expresses program logic in terms of facts and rules, using a system of inference to answer queries.
- Example: Prolog.
| Paradigm | Focus | Key Idea |
|---|---|---|
| Imperative | Control flow and State Change | Sequence of instructions to modify data. |
| OOP | Objects and Classes | Encapsulation of data and behavior. |
| Functional | Function evaluation | Avoids side effects; data is immutable. |
| Logic | Facts and Rules | Answers queries based on defined logic. |
4. Fundamental Language Concepts
These concepts are common across most high-level programming languages.
Data Types and Variables
- Data Types: Define the kind of data a variable can hold (e.g., integer, float, boolean, string).
- Variables: Named storage locations that hold a value of a specific data type.
- Static vs. Dynamic Typing:
- Static: Type checking is done at compile time (e.g., C++, Java).
- Dynamic: Type checking is done at run time (e.g., Python, JavaScript).
Control Flow
Statements that dictate the order in which instructions are executed.
- Conditional Statements: Execute different code blocks based on a condition (e.g.,
if,else,switch). - Loops: Repeat a block of code multiple times (e.g.,
for,while,do-while).
Subprograms (Functions/Methods)
Named blocks of code that perform a specific task, promoting code reuse and modularity.
- Parameters: Values passed into the subprogram.
- Return Value: The result passed out of the subprogram.
- Recursion: A function calling itself.
Object-Oriented Concepts (OOP)
- Abstraction: Hiding complex implementation details and showing only essential information.
- Encapsulation: Bundling data (attributes) and methods (functions) that operate on the data into a single unit (class/object).
- Inheritance: A mechanism where one class acquires the properties and methods of another class (parent/base class).
- Polymorphism: The ability of a method or object to take on many forms (e.g., method overloading, method overriding).
5. Tools of the Trade
Developers use a collection of software tools to write, test, and manage code efficiently.
A. Development Environments
- Text Editor: A basic tool for writing code files (e.g., Notepad++, Sublime Text, VS Code).
- Integrated Development Environment (IDE): A comprehensive tool that integrates all necessary features for software development.
- Features: Source code editor, build automation tools, debugger, syntax highlighting, and code completion.
- Examples: Visual Studio, IntelliJ IDEA, Eclipse, PyCharm.
B. Version Control Systems (VCS)
Software that tracks and manages changes to code over time, allowing multiple developers to collaborate and revert to previous states.
- Git: The most popular distributed VCS.
- GitHub/GitLab/Bitbucket: Web-based platforms for hosting Git repositories and facilitating collaboration.
C. Debuggers
Tools used to inspect the execution of a program, locate errors (bugs), and trace the flow of execution.
- Functionality: Setting breakpoints, stepping through code line-by-line, and inspecting variable values.
D. Build Tools
Software that automates the process of creating an executable application from source code and other resources. This includes compiling, linking, and packaging.
- Examples: Make, Maven (Java), Gradle (Java/Android), npm (JavaScript), pip (Python).
E. Documentation Tools
Essential for professional development, these tools help generate and manage documentation for code, APIs, and overall system design.
- Examples: Javadoc, Doxygen, Sphinx (Python).
F. Testing Frameworks
Tools that aid in writing, running, and reporting on automated tests (unit tests, integration tests, etc.) to ensure software quality and reliability.
- Examples: JUnit (Java), Pytest (Python), Jest (JavaScript).