The Complete Course of Compiler Design

Learn how a compiler translates high-level source code into machine code, exploring source-to-source and source-to-machine types and the full language processing pipeline from preprocessor to loader.

Compare compilers and interpreters: compilers analyze the whole program for optimization, producing faster executables, while interpreters translate one statement at a time for quick feedback and debugging.

Explore the six compilation phases—from lexical analyzer to code generation—and see how tokens, lexemes, syntax trees, semantic analysis, intermediate code, optimization, and symbol tables, with error handling, produce executable code.

Identify the compiler phases for the kinematic equation distance = v t + 1/2 a t^2 and explain what each phase outputs and does.

Understand six compiler phases, starting with lexical analysis that tokenizes input and removes whitespace, then syntax analysis, semantic analysis, intermediate code generation, code optimization, and target code generation.

Construct a lexical analyzer from first principles, using regular expressions to identify lexemes and produce tokens, while interfacing with the symbol table and parser, and stripping comments and whitespace.

Examine how regular expressions define tokens such as keywords, identifiers, literals, and operators, using union, concatenation, and repetition, and how regular languages and alphabets shape valid tokens.

Develop regular expressions to match examples like the sentence 'I like dancing' and a mathematical expression, as part of the compiler design course.

Explore regular expression construction by uniting character sets with whitespace, forming a subset of a to z, and combining a keyword, an identifier, digits, and the equal sign.

Explore finite automata as simple machines recognizing patterns, with states, transitions, an initial and accepting state, epsilon moves, and how regular expressions map to deterministic or nondeterministic automata.

Learn to convert regular expressions into nondeterministic finite automata, building starting points, transitions, and accepting states, including epsilon moves for union and concatenation.

Explore transition tables for deterministic finite automata, encoding states, inputs, initial and accepting states, and the transition function; read tables from diagrams and test strings for acceptance.

Convert a nondeterministic automaton to a deterministic automaton by forming composite states like AB and BC, and defining transitions to trap-free state sets. Identify accepting states that include C.

Convert regular expressions to nondeterministic finite automata, applying union, concatenation, and iteration, illustrated by two example expressions using brackets, union, and A union B.

Divide the equation into small parts and perform the NFA. Apply concatenation of three a and five f, then union, iteration, and epsilon moves to form the NFA diagram.

Construct the transition table from the transition diagram, identifying all necessary steps, extracting five tuples, and showing the transition function, then proceed to the transition diagram.

Identify states a to e and inputs a and b, derive transitions, and build transition table with start at a and finish at e (a→b on a, a→c on b).

Trace the conversion from an NFA to a DFA, identify the transition function, and build the diagram, illustrating the essential steps in deterministic automata.

Construct the NFA table from the diagram, then convert to the DFA by merging AB to Abd and removing ambiguous transitions, while defining new states and final states.

Understand syntax analysis and parsing as the compiler front end, using context free grammars to produce parse trees and abstract syntax trees from lexical token streams.

Explore parsing strategies, including leftmost and rightmost derivations, and top-down versus bottom-up parsing, while examining parse trees, ambiguity, left recursion, and left factoring.

Learn to remove left recursion from two grammars, using the pipe notation to represent alternative productions for a given non-terminal in compiler design.

Describe left recursion in grammars with left-placed nonterminals, show removing it via a transformation formula, and introduce a prime symbol (a', expression') to yield a non-left-recursive grammar.

Remove the left factoring in the given expression by analyzing two grammars and the pipes that denote two alternative productions for the given non-terminal.

Identify and remove left factoring to resolve ambiguity in given grammars, apply a formula to split into two productions with a new a prime, and present corrected grammar forms.

Explore top down and bottom up parsing, focusing on recursive descent and predictive parsers. Learn how leftmost derivation builds a parse tree in preorder, with backtracking and lookahead strategies.

Implement a c++ recursive descent parsing code in vscode, defining main, e and e' productions, match and error handling, and running with a dollar sign end marker.

Explore first and follow sets and their role in constructing predictive parsing tables for grammars, enabling lk parsers and clear handling of terminals, non-terminals, and epsilon.

Explore how to compute the first and follow sets for a given grammar, as addressed in question 8.

Learn how to compute the first and follow sets for grammars, including bottom-up construction from the start symbol, handling epsilon, and marking the start with dollar signs.

Explore predictive parsers, especially LL(1), and how they choose productions using lookahead with k tokens, first and follow sets, and a parsing table, with a stack and input buffer.

Construct an L1 parsing table from the given grammar and determine whether the input string is acceptable.

Remove left factoring and left recursion, create first and follow sets, build the ll(1) parsing table, and parse the input string using a stack.

Explore bottom-up parsing with shift-reduce techniques and LR parsing, including LR0, SLR, LR(1), and canonical LR, plus augmented grammar, closure, and goto.

Build and interpret the lr parsing table using shift, go-to, and reduce actions. Apply augmented grammar and parse a a b b to produce the parse tree from the stack.

Construct an LR parsing table from the given grammar, then check whether the input string is acceptable, applying all required LR parsing procedures.

Build and analyze the LR parsing table for a given grammar, using augmented production and canonical collection of items, then verify input strings using a bottom-up LR parser.

Semantic analysis validates the meaning of code beyond syntax, performing type checks, scope resolution, and declaration verification to detect semantic errors and ensure language semantics.

Explore syntax directed translation driven by the parser, using attributed grammars and semantic rules to build annotated parse trees for semantic analysis, type checking, and intermediate code.

Assess the semantic correctness of given statements in compiler design, identify semantic errors, and explain the reasoning behind each error.

Identify semantic errors in code by examining type mismatches, such as using a string where an int is required, a float division yielding 2.5, undeclared variables, and function compatibility issues.

Learn how intermediate code generation creates a machine independent intermediate representation between the front end and back end, enabling optimization and easy retargeting across targets.

Represent expressions as directed acyclic graphs to share subexpressions and reduce computations. Enable efficient code generation via topological ordering and constant folding.

Explore the abstract syntax tree, a hierarchical tree-like data structure whose nodes represent language constructs such as expressions, statements, and declarations, serving as an intermediate representation in intermediate code generation.

Learn prefix (polish), infix, and postfix (reverse polish) notations for expressions, including how prefix and postfix place operators relative to operands, and how stack-based conversion supports intermediate code generation.

Practice converting a given infix expression to postfix notation, mastering the steps to transform infix expressions into postfix form.

Transform infix expressions to postfix by applying a left-to-right stack method or Bodmas rules, prioritize brackets, and demonstrate with examples such as a-b, c-d, and e+fgx.

Explore quadruples and triples by transforming expressions into three-address code, build a quadruple table with op, arg1, arg2, and result, and derive triples from the code.

Convert the given mathematical expression into quadruples and triples to illustrate intermediate representations in compiler design.

Demonstrate generating quadruples and triples from an expression by mapping t1 to minus b and t2 to c + d, deriving a = T3 and using positions for three-address code.

Examine how the runtime environment manages memory layout, activation records, and variable scope, coordinating stack and heap to support function calls, dynamic allocation, and cross-platform execution.

Understand how the stack manages runtime memory with last in, first out. Store local variables and activation records, while push and pop govern function calls and control flow.

Implement a stack in c++ using a vector to provide push, pop, top, and empty operations, illustrating last-in, first-out behavior with a practical test.

The heap is a dynamic memory region for runtime allocation, distinct from the stack, where data persists until explicitly deallocated, with fragmentation and memory leaks from improper deallocation.

Explore activation records, or stack frames, as the data structure that manages function calls on the runtime call stack through creation, execution, and destruction, storing locals, parameters, and return addresses.

Understand how managing scopes controls where identifiers are valid, differentiate lexical/static scope from dynamic scope, and relate local, global, and static variable lifetimes to robust code.

Analyze how local, global, and static variables behave in the given c++ code within the compiler design course.

Local variables exist within their declaring block or function; global variables endure for the whole program, and static variables persist and retain values between calls.

Explore optimization techniques that improve compiler performance by boosting execution speed. Learn how optimization reduces memory usage, minimizes code size, lowers power consumption, and enhances resource utilization.

Explore constant folding, an optimization that evaluates constant expressions at compile time and replaces them with computed values, and declare constants to enable further optimization in modern C++ compilers.

Identify and perform dead code elimination during optimization to remove unreachable blocks. Reduce code size, improve execution, and simplify maintenance.

Common subexpression elimination identifies and eliminates redundant subexpressions in compiled code by computing them once, storing the result, reducing memory use and boosting runtime efficiency.

Apply previously learned optimization methods to optimize the given C++ code provided in the question.

Explore constant folding, dead code elimination, and common subexpression elimination to optimize C plus plus code. See how merging constants, removing unused results, and sharing repeated subexpressions yields streamlined code.

Explore how code generation translates intermediate code into machine or assembly language, preserving semantics while optimizing resource use through instruction selection, register allocation, and instruction ordering.

Identify the input to the code generator as the well-defined intermediate representation plus symbol table data, enabling language independence, transformations, optimizations, and correctness checks.

Explore target program code in compiler design. Understand absolute and relocatable machine code, assembly output, and Java bytecodes interpreted by the Java Virtual Machine.

Master memory management in code generation by balancing resource optimization, memory safety, and correctness, focusing on stack and heap allocation, memory organization, data alignment, and global and static data.

Instruction selection in code generation translates high-level constructs into target machine instructions, balancing intermediate representation complexity, architecture constraints, and optimization costs to produce efficient assembly code.

Derive a strategy score from the expression using non-terminals, then generate and optimize assembly code by eliminating redundant moves and sequence operations on registers and memory.

Build a strategy score from an expression using t1, t2, t3, generate assembly code, and optimize by removing redundancies for a compact sequence of move, add, multiply, subtract, store.

Master register allocation and assignment to maximize speed by keeping variables in registers, minimize memory access, and leverage techniques like graph coloring, linear scan, and spill-cost strategies.

Explore how evaluation order shapes code generation, subexpression evaluation, side effects, and dependencies, and learn how optimized ordering can improve performance, parallelism, and code size.

Evaluate and optimize the provided code by analyzing the expression and assembly code to derive an optimized version.

Learn how to evaluate and optimize an expression by reshuffling strategy and assembly code, comparing evaluation orders to minimize instructions and generate threaded code using registers like t1 and r0.

Explore how just in time compilation dynamically translates code during execution to adapt to runtime conditions. See how interpreters, selective compilation, thresholds, and profiling drive adaptive optimization.

Explore the differences between static and dynamic compilation, including how static compilation creates a self-contained executable and slower startup, while dynamic (jit) compilation adapts at runtime using profiling.

Explore hotspot compilation in the Java Virtual Machine, a dynamic JIT technique that identifies hotspots, uses adaptive optimizations like inlining and loop unrolling, and adjusts decisions based on runtime profiling.

Explore domain-specific languages (DSLs) that tailor code to a domain, including external and internal DSLs, their abstractions, syntax and semantics, benefits, and design steps.

Learn to design a C++ domain-specific language for mathematical expressions, supporting constants, variables, and binary operations like addition, subtraction, multiplication, and division, and evaluate expressions.

The lecture demonstrates a dsl for building expressions by creating variables and constants and composing binary operations like plus, minus, times, and divide via operator overloads with unique_ptr ownership.

Demonstrates building a simple internal DSL in C++ to express and evaluate binary operations with constants and variables, printing results to the console for the complete course of compiler design.

Build a simple domain specific language from the given problem by identifying nouns and verbs, then implement an internal DSL in C++ to manage products, quantity, and inventory.

Create a simple inventory system in C++ using a domain-specific language (DSL) function, featuring a product class, an inventory class, and operations to add, update, and list products.

Build a simple c++ inventory management system with a main function, inventory class, and menu-driven interface, showcasing vector usage, user input, and basic control flow for testing the dsl.

Propose a DSL program for Angela to log and manage her daily tasks, solving forgetfulness. Implement it with C++ or an internal DSL.

Design a simple c++ task management dsl with a task class and a task list. Use a vector to store tasks and a menu to add, complete, and list them.