Compliers & Interpreters

Types of Compilers

There are several main types of compilers:

Traditional compilers compile source code written in a high-level language into machine code for a specific CPU or architecture. Examples are C/C++ compilers, Java compilers, etc.

Just-in-time (JIT) compilers: These compile source code at runtime into machine code. Examples are Java JIT compilers,.NET JIT compilers and JavaScript JIT compilers in browsers.

Ahead-of-time (AOT) compilers compile source code before runtime into machine code. Examples are Go compilers and Android app compilers.

Partial compilers only partially compile source code and emit an intermediate format. The intermediate code is then compiled into machine code at runtime. Examples are .NET IL compilers and Java bytecode compilers.

Cross compilers: These compile source code for one platform to generate machine code that runs on a different platform. For example, an ARM cross compiler for an x86 machine.

Incremental compilers: This recompiles only the parts of the source code that have changed since the last compilation rather than compiling the source code from scratch.

Meta-compilers: also called compiler-compilers, are compilers that take a specification of a language and generate a compiler for that language. Examples are Flex/Bison, parser generators, and LLVM.

Those are the main types of compilers. The differences lie in when and how they compile source code and what their targets are. Traditional ahead-of-time compilation to native machine code is the most common.

Phases of a Compiler

A compiler goes through several main phases:

1. Linguistic Analysis: This phase converts the input characters into meaningful tokens like identifiers, keywords, constants, operators, etc. This is done using a lexical analyzer or scanner.

2. Syntax Analysis: This phase checks the tokens generated by the lexical analyzer and arranges them according to the language's syntax. It checks for syntax errors. This is done using a parser.

3. Semantic Analysis: This phase checks the semantics and meaning of the program. It checks for semantic errors like unused variables, redeclaration of variables, etc.

4. Intermediate Code Generation: This optional phase converts the source code into an intermediate representation. This helps with optimization and code generation for multiple targets.

5. Optimization: This optional phase performs various optimizations on the intermediate code to improve the performance and efficiency of the generated code.

6. Code Generation: This phase converts the optimized intermediate code into the target machine code. This is done using a code generator.

7. Code Optimization: This final optional phase performs machine-specific optimizations on the generated code.

So, in summary, a compiler goes through the following main phases:

• Lexical Analysis

• Syntax Analysis

• Semantic Analysis

• Optional: Intermediate Code Generation

• Optional: Optimization (on intermediate code)

• Code Generation

• Optional: Code Optimization (machine-specific)

To produce the desired machine code, each phase uses the output of the phase before it as input.

Architectures of Compilers

There are two main architectures for compilers:

1. One-pass compiler: The compiler compiles in a single pass in this architecture. It does lexical analysis, syntax analysis, semantic analysis, code generation, etc., in one go. This is a simpler architecture, but it can be inefficient.

2. Multi-pass compiler: The compiler makes multiple passes over the source code in this architecture. Each pass performs one specific task. For example:

• Pass 1 does lexical and syntax analysis.

• Pass 2 does semantic analysis.

• Pass 3 generates an intermediate code.

• Pass 4 optimizes the intermediate code.

• Pass 5 generates machine code from the optimized intermediate code.

The multi-pass architecture has a few advantages:

• Easier to implement and maintain since each pass has a focused task.

• Easier to add new optimizations and code generation targets.

• Errors are detected earlier since passes are separated.

The disadvantages are:

• More complex overall.

• Requires the compiler to store intermediate results between passes.

Overall, the multi-pass architecture is more common for modern compilers since it allows:

• Better optimization due to the separation of passes

• Easier maintenance and extension by decoupling compiler phases

• Earlier error detection by doing semantic analysis in a separate pass

Though a one-pass compiler is more straightforward, a multi-pass compiler with distinct phases for each task is a more common and effective architecture for modern compilers. The separation of concerns and the ability to easily add new optimizations make the multi-pass approach preferable.

Interpreter

An interpreter is a program that directly executes instructions written in a programming or scripting language without first compiling them into a machine language.

Some key points about interpreters:

• Interpreters read each instruction in a program, parse and validate the syntax, and then carry out the desired action.

• Interpreters execute code sequentially, line by line.

• Since the code is not compiled beforehand, interpreters tend to be slower than compiled programs.

• Interpreted languages are easier to develop and debug since no compilation step is required.

• Popular interpreted languages include Python, Ruby, PHP, and JavaScript (in browsers).

How does an interpreter work?

• The interpreter reads a line of source code.

• It parses the line to determine the instruction type - an assignment, function call, etc.

• It then interprets the instruction by performing the appropriate action - evaluating expressions, looking up variables, calling functions, etc.

• This process repeats for each line of code in the program.

Advantages of interpreters:

• Faster development time since no compile step is required
• Easier debugging since you can execute and test code interactively
• More portable since the interpreter handles running code on different systems

Disadvantages of interpreters:

• Slower execution speed compared to compiled programs
• Uses more system resources like CPU and memory during execution

An interpreter directly executes instructions written in a programming language. This contrasts with a compiler, which converts source code into machine code ahead of time. Interpreters tend to be simpler but slower, while compilers produce faster but more complex programs.

Common issues with compilers

Here are some common issues that can arise with compilers:

1. Syntax errors - These are errors in the syntax of the source code, like missing parentheses, curly braces, or semicolons. The compiler detects these and throws an error.

2. Semantic errors - These are errors in the meaning or logic of the source code, like using an undeclared variable, assigning a value of the wrong type, etc. The compiler detects these and throws an error.

3. Runtime errors occur when executing the compiled code, including dividing by zero, indexing out of the bounds of an array, etc. The compiler cannot detect these; they only appear at runtime.

4. Bugs in the compiler itself - Even well-tested compilers can have bugs that cause incorrect code generation. This can lead to hard-to-find issues at runtime.

5. Inefficiencies in generated code - Compilers make many choices that impact the efficiency and performance of the generated code. Optimization levels can help, but compilers are not perfect.

6. Inability to optimize across modules - Compilers optimize within source files but struggle to optimize functions that span multiple modules. This can lead to suboptimal performance.

7. Target platform issues - The generated code may have issues running on the target platform due to register allocation issues, endianness differences, etc.

8. Floating point precision issues - Compilers make choices for floating point calculations that can sometimes lead to minor precision differences vs a program execution by hand.

9. Memory leaks - Compilers sometimes struggle to detect memory leaks that require complex analysis of pointers, references, memory allocation, etc.

10. Security issues - Generated code can sometimes have buffer overflows if the compiler fails to insert proper bounds checks.

These cover some of the significant issues that can occur with compilers. The solutions generally involve improving and testing compilers, using linting tools to detect issues earlier, running code in a debugger, and performing thorough testing of the generated code.

Issues with Interpreters

Here are some common issues with interpreters:

1. Performance - Since the code is interpreted at runtime, executables produced by interpreters tend to be slower than compiled code. This is because no optimization can be performed ahead of time.

2. Memory usage - Interpreters also tend to use more memory than compilers. This is because the interpreter needs to load and parse the entire program before executing it.

3. Debugging - While easy to debug initially, tracking down performance issues in interpreted code can be tricky since no optimized machine code is available for inspection.

4. Security - Interpreted code is essentially human-readable, making it easier for malicious attackers to exploit. Compiled code is more secure.

5. Portability - While interpreters aim to be portable, differences in interpreter implementations can sometimes lead to portability issues across platforms.

6. Immaturity - Interpreter implementations sometimes lack advanced features like compilers' extensive optimization techniques.

7. Versioning - Version changes in interpreters can sometimes break existing code by changing APIs or behaviour in incompatible ways.

8. Multithreading - Interpreters sometimes struggle to support multithreaded applications since they lack advanced compiler analysis efficiently.

9. Extension support - Extending the language supported by interpreters often requires modifying the interpreter, which can be complex.

10. Predictability - Since interpretation is a sequential process, it can be challenging to predict the performance of interpreted code in all situations.

While interpreters have advantages like easy development and portability, they often suffer from issues with performance, memory usage, debugging, security, and predictability compared to compilers.

However, interpreters excel in rapid development turnaround and the ability to execute programs immediately without a build step. So there are tradeoffs between the two approaches.