Zoetic Data and their Generators

Paul Bailes, Colin Kemp

2016

Abstract

Functional or “zoetic” representations of data embody the behaviours that we hypothesise are characteristic to all datatypes. The advantage of such representations is that they avoid the need, in order to realize these characteristic behaviours, to implement interpretations of symbolic data at each use. Zoetic data are not unheard-of in computer science, but support for them by current software technology remains limited. Even though the first-class function capability of functional languages inherently supports the essentials of zoetic data, the creation of zoetic data from symbolic data would have to be by repeated application of a characteristic interpreter. This impairs the effectiveness of the “Totally Functional” approach to programming of which zoetic data are the key enabler. Accordingly, we develop a scheme for synthesis of generator functions for zoetic data which correspond to symbolic data constructors but which entirely avoid the need for a separate interpretation stage. This avoidance allows us to achieve a clear separation of concerns between the definitions of datatypes on the one hand and their various applications on the other.

Paper Citation

in Harvard Style

Bailes P. and Kemp C. (2016). Zoetic Data and their Generators . In Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-189-2, pages 260-271. DOI: 10.5220/0005914902600271

in Bibtex Style

@conference{enase16,
author={Paul Bailes and Colin Kemp},
title={Zoetic Data and their Generators},
booktitle={Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,},
year={2016},
pages={260-271},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005914902600271},
isbn={978-989-758-189-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,
TI - Zoetic Data and their Generators
SN - 978-989-758-189-2
AU - Bailes P.
AU - Kemp C.
PY - 2016
SP - 260
EP - 271
DO - 10.5220/0005914902600271