# Separating Use and Reuse to Improve Both

**Authors:** Hrshikesh Arora (Victoria University of Wellington, New Zealand),, Marco Servetto (Victoria University Wellington, New Zealand), Bruno C. D. S., Oliveira (The University of Hong Kong, Hong Kong)

arXiv: 1902.00546 · 2019-02-05

## TL;DR

This paper introduces a new language, $42_$, that enhances code reuse and type safety in trait-based programming by separating use from reuse and supporting abstract state operations, addressing key limitations of traditional object-oriented languages.

## Contribution

It designs $42_$, a language that synthesizes existing trait composition approaches with improved state handling, enabling better separation of use and reuse in object-oriented programming.

## Key findings

- $42_$ supports abstract state operations for better state management.
- The model reduces type errors in trait composition.
- Case studies show improved usability and compactness.

## Abstract

Context: Trait composition has inspired new research in the area of code reuse for object oriented (OO) languages. One of the main advantages of this kind of composition is that it makes possible to separate subtyping from subclassing; which is good for code-reuse, design and reasoning. However, handling of state within traits is difficult, verbose or inelegant. Inquiry: We identify the this-leaking problem as the fundamental limitation that prevents the separation of subtyping from subclassing in conventional OO languages. We explain that the concept of trait composition addresses this problem, by distinguishing code designed for use (as a type) from code designed for reuse (i.e. inherited). We are aware of at least 3 concrete independently designed research languages following this methodology: TraitRecordJ, Package Templates and DeepFJig. Approach: In this paper, we design $42_\mu$ a new language, where we improve use and reuse and support the This type and family polymorphism by distinguishing code designed for use from code designed for reuse. In this way $42_\mu$ synthesise the 3 approaches above, and improves them with abstract state operations: a new elegant way to handle state composition in trait based languages. Knowledge and Grounding: Using case studies, we show that $42_\mu$'s model of traits with abstract state operations is more usable and compact than prior work. We formalise our work and prove that type errors cannot arise from composing well typed code. Importance: This work is the logical core of the programming language 42. This shows that the ideas presented in this paper can be applicable to a full general purpose language. This form of composition is very flexible and could be used in many new languages.

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Source: https://tomesphere.com/paper/1902.00546