LUCID: Clearer Software by Integrating Natural Language Analysis into Software Engineering

Developers spend most of their time maintaining code, with little tool support. To maintain code, one must understand it. Clear code is easier to read and understand, and therefore less expensive and risky to evolve and maintain; it is also notoriously difficult to write. We will help developers write clearer code to speed maintenance, and increase developer productivity. Source code unites two channels - the programming language and natural language - to describe algorithms. LUCID will advance the state of the art in software engineering by developing new analyses that exploit the interconnections between these channels to find uninformative names, stale comments, and bugs that manifest as discrepancies between the two channels.

Principle Investigator 

Earl Barr (UCL)

Charles Sutton (Edinburgh)


Santanu Dash (UCL)

Annie Louis (Edinburgh)




This project is funded by the EPSRC.



This page was last modified on 05 Dec 2018.