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Details of Grant 

EPSRC Reference: EP/W015927/1
Title: MUSE: Multi-Modal Software Evolution
Principal Investigator: Dash, Dr SK
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Indian Institute of Technology Kanpur Turing Intelligence Technology Limited UCL
University of Edinburgh
Department: Information Security
Organisation: Royal Holloway, Univ of London
Scheme: New Investigator Award
Starts: 01 October 2022 Ends: 30 September 2025 Value (£): 421,797
EPSRC Research Topic Classifications:
Software Engineering
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
18 Jan 2022 EPSRC ICT Prioritisation Panel January 2022 Announced
Summary on Grant Application Form
Software systems are heterogeneous, combining components developed by independent teams. Software developers rely on third-party libraries to cut development time and cost. The synergy between these components is crucial for the overall maintainability and health of the software system. Unfortunately, popular libraries are typically fast-moving and grow rapidly in size while catering to a diversity of client software. As libraries evolve and grow in size, developers tend to defer upgrades despite clear upgrade directives from the libraries, citing the cost of upgrade in both time and money.

To build large and sustainable software systems, it is crucial that independently evolving software systems are synchronised automatically. Multi-Modal Software Evolution (MUSE) is a transformative step towards autonomous software maintenance where directives in software documentation for human developers will guide automated software upgrade. In MUSE, we will develop a novel approach to software upgrade that integrates upgrade directives for human developers into formal frameworks for program synthesis, generation and repair. We will include directives in documentation for libraries as first class objects in frameworks for reasoning and transformation of software. We will produce hybrid statistical-formal reasoning frameworks which will make human-to-human communication the main driver in automatic program transformation.

Working closely with stakeholders through engagement events, we will develop both the theory and the tooling for automatic software upgrade to use newer versions of libraries. We will demonstrate the tools by upgrading client software that relies on fast-moving libraries and distribute the tools that we develop in multiple forms for developers at all skills levels, from enthusiasts to experienced developers, making our outputs widely accessible.

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