GISMO: Genetic Improvement of Software for Multiple Objectives

Lead Research Organisation: University College London
Department Name: Computer Science


Humans find it hard to develop systems that balance many competing and conflicting operational objectives. Even meeting a single objective requires automated support. For example, there has been a long and rich history of research into techniques to optimise compiled code size and speed. Unfortunately, speed and size are but two of many objectives that the next generation of software systems will have to meet. Emergent computing application paradigms require systems that are not only reliable, compact and fast, but also which optimise many different competing and conflicting objectives such as response time, throughput and consumption of resources. Humans cannot be expected to optimally balance these multiple competing constraints and may miss potentially valuable solutions. Techniques are therefore required that can either automatically create code that balances many conflicting objectives or that can provide support to the human who seeks to do so. The GISMO project seeks to do both. It will develop automated techniques to produce new versions of components of existing systems that meet newly defined objectives. After a period of running the old and new component in parallel, the programmer may decide to adopt the newly evolved component. However, the beauty of the GISMO approach is that it does not insist that the programmer must accept the evolved solution in order to be useful. The programmer can also use GISMO to explore the multi-objective candidate solution space, gaining insight into what can be achieved by balancing several competing constraints.

Planned Impact

The initial industrial beneficiaries of this work will be the industrial partners of the project. However, the UCL CREST centre has many other very close links to the industrial sector. These will constitute an initial pool of industrial beneficiaries. Ultimately, through more flexible and multipurpose software, and reduced software production costs, the IT-centric areas of the wider economy and the general public will benefit. We will also exploit our extensive network of industrial champions from established on-going projects. The pathways to impact plan list 24 such companies with which we have existing active research work. The project will also maximise impact on the academic sector. Naturally, the results of the project will be published in leading journals and conference proceedings. An indicative list is given in the pathways to impact plan. The project team will also organise two workshops to deepen collaboration, widen the research base in Genetic Programming for Software Engineering and to disseminate the results of the GISMO research programme. The first of these will be held within the UK. The second workshop will be co-located with an international conference, with the aim of broadening the community with international participation. This will ensure that the project creates a sustained international community with UK research and industry at its heart.


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Langdon W (2015) Optimizing Existing Software With Genetic Programming in IEEE Transactions on Evolutionary Computation

Description This project is ongoing. We have achieved a number of breakthroughs in genetic programming, and I will provide a more complete account once the project is completed.
Exploitation Route The project is ongoing, and we're working with our partners to develop the uptake of the work.
Sectors Digital/Communication/Information Technologies (including Software)

Description There has been significant recent industrial impact for the research underpinning these grant and others for which Prof. Harman was PI. The Prof Harman became engineering manager at Facebook London, where he leads the Sapienz team, working on Search Based Software Engineering (SBSE) for automated test case design and fault fixing. The development of SBSE was a key research direction for this grant that underpinned the work. Sapienz has been deployed to continuously test Facebook's apps, leading to thousands of bugs being automatically found and fixed (mostly by developers, but more recently, some of these faults have also been automatically fixed by Sapienz). The software tackled by Sapienz consists of tens of millions of lines of code; apps that are among the largest and most complex in the app store and that are used by over a billion people worldwide every day for communication, social networking and community building. Work is underway to developer this research agenda at Facebook.
First Year Of Impact 2020
Sector Digital/Communication/Information Technologies (including Software)
Impact Types Economic

Title GP Bibliography 
Description The GP Bibliography is a repository of all publications on the topic of genetic programming, which is maintained by Bill Langdon (William B. Langdon). The repository has been available since before 2006, but since 2011, its maintenance has been supported by the EPSRC project GISMO, which funds, in full, Dr Langdon. It was started by Dr langdon when he was at the University of Birmingham, though he has been at University College London since 2010. The University of Birmingham continues to host the repository, while support for its maintenance and update by Dr langdon comes from UCL, through GISMO Project. Before the GISMO Project, Dr langdon was funded by the CREST platform grant and SEBASE projects. 
Type Of Material Database/Collection of data 
Provided To Others? Yes  
Impact Repository contains over 7000 entries, and is widely used by other researchers. It is the first point of call for any researcher working in genetic programming, in order to search for and find relevant information on previous research in this area.