IDE Development Course
Andrew Vasilyev
Polymorphism is a concept in programming that refers to the ability of different classes to respond to the same function call or method invocation, each in their own class-specific way. This enables a single interface to interact with objects of different types.
The interaction between polymorphism and type systems involves how polymorphic features are handled within type hierarchies, and how overloading, overriding, and templating are managed.
Static polymorphism, also known as compile-time polymorphism, resolves method calls at compile time. Dynamic polymorphism, or runtime polymorphism, resolves method calls at runtime.
// Static polymorphism example in Java
class MathOperations {
public int multiply(int a, int b) {
return a * b;
}
// Overloaded method with different signature
public double multiply(double a, double b) {
return a * b;
}
}
// Dynamic polymorphism example in Java
class Animal {
public void sound() {
System.out.println("Animal makes a sound");
}
}
class Dog extends Animal {
public void sound() {
System.out.println("Dog barks");
}
}
Animal animal = new Dog();
animal.sound(); // Outputs: Dog barks
Ad-hoc polymorphism allows a single function symbol to have multiple implementations, with the compiler choosing the appropriate implementation based on the types of the arguments.
// Ad-hoc polymorphism example in Java (Method Overloading)
class MathOperations {
public int add(int a, int b) {
return a + b;
}
public double add(double a, double b) {
return a + b;
}
public String add(String a, String b) {
return a + b;
}
}
Parametric polymorphism enables the use of the same code with different types, commonly implemented using templates or generics.
// Parametric polymorphism example in Java (Generics)
class Box {
private T t;
public void set(T t) {
this.t = t;
}
public T get() {
return t;
}
}
Box integerBox = new Box();
Box stringBox = new Box();
Coercion polymorphism refers to the automatic conversion of a value from one data type to another. It allows different types to be treated as the same type in certain contexts, often occurring implicitly in many programming languages.
// Coercion polymorphism example in Java
public class CoercionExample {
public static void main(String[] args) {
int integerNumber = 42;
// Automatic conversion from int to double
double doubleNumber = integerNumber;
System.out.println(doubleNumber); // Outputs: 42.0
}
}
In this example, the integer value is automatically converted (coerced) to a double when assigned to a variable of type double.
Type inference is the automatic detection of the data type of an expression in a programming language without explicit type annotations by the programmer.
Type-checking verifies if a given expression matches a type, while type inference deduces the type of an untyped expression.
Type inference supports polymorphism by deducing the most general type, allowing the same code to be used with different data types and promoting code reuse.
Type inference involves deducing the type of an expression from the context in which it appears.
public void Foo(double value)
{
Console.WriteLine("double");
}
public void Foo(int value)
{
Console.WriteLine("int");
}
public void Boo()
{
// C# uses the 'var' keyword to infer the type of 'total'
var total = 10 + 5; // 'total' is inferred to be of type int
Foo(total); // int
Foo(total + 2); // int
Foo(total + 2.1f); // double
}
The IDE begins with no assumptions about type and assigns types to literals based on their value, such as inferring `int` for numerical literals.
For expressions where the type is not immediately apparent, the IDE uses type variables as placeholders during the inference process.
The compiler collects constraints for type variables based on how they are used in the code, influencing the final inferred type.
The unification step attempts to resolve type variables into concrete types by satisfying all gathered constraints without conflicts.
Post-unification, the compiler checks for type consistency. Conflicts or unsatisfiable constraints result in type errors.
Successful type checking leads to the final assignment of concrete types to previously unresolved type variables, completing the inference.
public static (T1, T2) Combine<T1, T2>(T1 first, T2 second)
{
return (first, second);
}
var combinedIntString = Combine(1, "apple");
var combinedBoolDouble = Combine(true, 3.14);
T1 and T2 for
method parameters.T1 as int, T2
as string for combinedIntString; and T1 as
bool, T2 as double for combinedBoolDouble.
In type systems, when an error is encountered, a type of "unknown" can be introduced.
Hindley-Milner Type System
Algorithm W
Formal verification
Derived types
Automated theorem proving
Static analysis is a process of examining code without running it to find errors, code smells, and security vulnerabilities.
AST verification checks the syntax tree of code for structural and logical correctness. For example, it can flag a potential error if an assignment is made in a conditional statement.
// Incorrect use of assignment in a conditional
if (a = 10) { ... } // Possible error
// Correct use of comparison
if (a == 10) { ... } // Expected check
CFA identifies unreachable code and other flow issues. For example, it detects code after a return statement that will never execute.
function example() {
return;
console.log('This will never be called');
}
A Control Flow Graph is a graphical representation of all paths that might be traversed through a program during its execution.
Symbolic execution tests program paths with symbolic inputs, identifying potential errors like division by zero.
Symbolic input is a variable used in program analysis that represents a range of possible values rather than a specific one.
function divide(x, y) {
return x / y; // Potential division by zero if y is symbolic and can be zero
}
Dataflow analysis tracks variable usage to prevent issues like uninitialized variables.
let x;
console.log(x); // Uninitialized variable usage
Interprocedural analysis checks interactions across functions, alerting to side effects or unintended usages.
// Command handler for creating an order
public class OrderCommandHandler {
private readonly Database db;
public OrderCommandHandler(Database database) {
db = database;
}
public void HandleCreateOrder(CreateOrderCommand command) {
var order = new Order(command.Data);
db.AddOrder(order);
}
}
// Query handler for fetching order details
public class OrderQueryHandler {
private readonly Database db;
public OrderQueryHandler(Database database) {
db = database;
}
public OrderDetails GetOrderDetails(Guid orderId) {
return db.GetOrderById(orderId);
}
}
// Interprocedural analysis would validate that OrderCommandHandler only modifies state and does not perform any queries.
// It would also check that OrderQueryHandler only reads state and does not modify it.
A call graph illustrates the calling relationships between different subroutines in a program.
%%{
init: {
'theme': 'base',
'themeVariables': {
'fontSize': '30px',
'darkmode': true,
'lineColor': '#F8B229'
}
}
}%%
graph LR
A[Code] --> B[Lexical Analysis]
B --> C[Tokens]
C --> D[Syntax Analysis]
D --> E[AST]
E --> G[Semantic Analysis]
G --> I[PSI]
I --> K[Type System]
I --> L[Annotated AST]
I --> M[Symbol Tables]
I --> N[Declared Elements]
I --> O[Resolved References]
I --> P[Control Flow Graphs]
I --> R[Call Graph]
I --> S[...]
K --> Z[Static Analysis]
L --> Z
M --> Z
N --> Z
O --> Z
P --> Z
R --> Z
S --> Z
The upcoming lecture will cover Dynamic Analysis, detailing its integral role in IDE development. We'll examine dynamic analysis tools, their application in real-time code evaluation, and their contribution to performance profiling.
Thank you for your attention!
I'm now open to any questions you might have.