Compilation

1. Lexical Analysis: The compiler analyzes the source code and breaks it down into smaller meaningful units called tokens. This process is known as lexical analysis or tokenization. Tokens can include keywords, identifiers, operators, constants, etc.
2. Syntax Analysis: The compiler then performs syntax analysis, also known as parsing. It checks whether the arrangement of tokens follows the rules defined by the language's grammar. This step ensures that the code is structurally correct and creates a parse tree or an abstract syntax tree (AST).
3. Semantic Analysis: In this phase, the compiler examines the semantics or meaning of the code. It checks for any logical errors or inconsistencies that cannot be identified during syntax analysis. The type compatibility, variable declarations, scoping rules, and other language-specific rules are verified at this stage.
4. Code Optimization: Once the code has been analyzed and verified, the compiler may perform code optimization. Optimization techniques aim to improve the efficiency of the generated machine code by reducing redundant operations, eliminating unreachable code, or rearranging instructions to enhance performance.
5. Code Generation: The final step of compilation involves generating machine code or bytecode. Machine code is specific to the target hardware architecture, whereas bytecode is an intermediate representation that can be interpreted by a virtual machine. The generated code is ready for execution.

Interpretation

1. Lexical Analysis: Similar to compilation, interpretation starts with lexical analysis, breaking down the source code into tokens.
2. Parsing and Execution: Once the tokens are generated, the interpreter reads and analyzes them line by line, executing the code in real-time. It follows the control flow of the program, interpreting each statement and performing the corresponding actions.
3. Just-In-Time (JIT) Compilation: Some interpreted languages, like JavaScript, employ a technique called Just-In-Time (JIT) compilation. JIT compilation dynamically translates frequently executed code segments into machine code for improved performance. The interpreter identifies hotspots in the code and optimizes them by converting them into machine code on the fly.

Key Differences

• Execution Speed: Compiled languages tend to execute faster than interpreted languages since the compilation process optimizes the code in advance. Interpreted languages, on the other hand, have the overhead of analyzing and executing the code simultaneously.
• Portability: Interpreted languages, often using bytecode or a virtual machine, offer better portability as they can be executed on any system with a compatible interpreter. Compiled languages generate machine code specific to the target hardware and may require recompilation for different platforms.
• Development Workflow: Compilation provides early detection of syntax and semantic errors before the program runs, helping developers identify issues during the development phase. Interpretation allows for dynamic and interactive programming, enabling developers to experiment and modify code on the go without the need for a separate compilation step.
• Debugging: Interpreted languages generally offer better debugging capabilities, as the interpreter can provide detailed runtime information, such as variable values and stack traces. Compiled languages may require additional debugging tools or techniques to extract similar information.

Example

• Python, being an interpreted language, does not undergo a traditional compilation process. However, it does undergo a form of compilation known as "bytecode compilation". When a Python script is run, it is first compiled into bytecode, which is a low-level representation of the code. This bytecode is then executed by the Python interpreter. This approach allows Python to be platform-independent, as the bytecode can be executed on any system with a compatible interpreter.
• Java programs are compiled into bytecode using the Java compiler (javac). The resulting bytecode is platform-independent and can be executed on any system with the Java Virtual Machine (JVM) installed. The JVM acts as an interpreter for the bytecode, converting it into machine code at runtime. This process of compiling Java source code into bytecode allows for "write once, run anywhere" portability.