Language Design: Equality & Identity

Part 2: Problems

Published on 2017-10-31. Last updated on 2022-06-08


The core issue is that equality on its own is insufficient to implement some, rather mundane, algorithms.

Asking the simple question “is some element contained in this data structure” in different languages demonstrates the problem:

Java:     List.of(Float.NaN).contains(Float.NaN);   // true
Scala:    List(Float.NaN).contains(Float.NaN)       // false
Rust:     &[0.0/0.0].contains(0.0/0.0)              // false
C#:       var list = new List<float>() { float.NaN };
          list.Contains(float.NaN);                 // true
Haskell:  elem (0.0/0.0) [0.0/0.0]                  // false

Only Java and C# get this right, and the reason why it works in Java is quite incidental:

Methods like equals or contains box the arguments before comparison, first check for reference equality, then call equals. Without boxing, it would not be possible to find a NaN value in a data structure in Java.


The design decisions made by languages also come with a large footprint in language complexity. For instance:

  • There are many, often confusing options which equals method should be overridden or how == should be overloaded.
  • It is hard to know which of the many methods to use, and which semantics have been implemented by the author of the type.
  • Value types are often unnecessarily boxed for equality operations.
  • Generic code has to decide at declaration-site whether it requires arguments to be reference or value types.
    • Java works around this by only supporting reference types in generics.
    • Scala requires explicit bounds (<: AnyRef) to mark types that require reference equality.
    • C# provides class (reference type) and struct (value type) constraints on generic types.
  • Language creators (Java) or users (Scala) need to decide whether interfaces support value types, or require that all subtypes are reference types.