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A Theory of Dual Channel Constraints

Casalnuovo, C; Barr, ET; Dash, SK; Devanbu, P; Morgan, E; (2020) A Theory of Dual Channel Constraints. In: ICSE-NIER '20: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: New Ideas and Emerging Results. (pp. pp. 25-28). ACM: Seoul, Korea. Green open access

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The surprising predictability of source code has triggered a boom in tools using language models for code. Code is much more predictable than natural language, but the reasons are not well understood. We propose a dual channel view of code; code combines a formal channel for specifying execution and a natural language channel in the form of identifiers and comments that assists human comprehension. Computers ignore the natural language channel, but developers read both and, when writing code for longterm use and maintenance, consider each channel's audience: computer and human. As developers hold both channels in mind when coding, we posit that the two channels interact and constrain each other; we call these dual channel constraints. Their impact has been neglected. We describe how they can lead to humans writing code in a way more predictable than natural language, highlight pioneering research that has implicitly or explicitly used parts of this theory, and drive new research, such as systematically searching for cross-channel inconsistencies. Dual channel constraints provide an exciting opportunity as truly multi-disciplinary research; for computer scientists they promise improvements to program analysis via a more holistic approach to code, and to psycholinguists they promise a novel environment for studying linguistic processes.

Type: Proceedings paper
Title: A Theory of Dual Channel Constraints
Event: ICSE 2020 - New Ideas and Emerging Results
Dates: 23 May 2020 - 29 May 2020
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3377816.3381720
Publisher version: https://doi.org/10.1145/3377816.3381720
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10092853
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