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Details of Grant 

EPSRC Reference: EP/P005659/1
Title: LUCID: Clearer Software by Integrating Natural Language Analysis into Software Engineering
Principal Investigator: Barr, Professor ET
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Microsoft
Department: Computer Science
Organisation: UCL
Scheme: Standard Research
Starts: 01 December 2016 Ends: 31 January 2020 Value (£): 337,411
EPSRC Research Topic Classifications:
Artificial Intelligence Fundamentals of Computing
Software Engineering
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
EP/P005314/1
Panel History:
Panel DatePanel NameOutcome
10 Jun 2016 EPSRC ICT Prioritisation Panel - Jun 2016 Announced
Summary on Grant Application Form
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.

Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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