Automated Software Specialisation Using Genetic Improvement

使用遗传改进的自动化软件专业化

基本信息

  • 批准号:
    EP/P023991/1
  • 负责人:
  • 金额:
    $ 113.6万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Fellowship
  • 财政年份:
    2017
  • 资助国家:
    英国
  • 起止时间:
    2017 至 无数据
  • 项目状态:
    已结题

项目摘要

This fellowship will change the face of software development by transferring the challenging and time-consuming task of software specialisation from human to machine. It will develop novel approaches for specialising and improving efficiency of generalist software for particular application domains in an automated way. The developed techniques will be program-agnostic and thus applicable to any type of software. Therefore, they will allow to speed-up computationally intensive calculations that arise, for instance, in the field of bioinformatics or healthcare. This fellowship thus can contribute to driving research development in other fields of research by providing an automated way of adapting and speeding-up existing software used in a plethora of areas, both in research and in the industry. The project will utilise and develop novel methods in the field of software engineering, called genetic improvement, to achieve the goals of the project. Genetic improvement is a novel field of research that only arose as a standalone area in the last few years. Several factors contributed to the development and success of this field, one of which is the sheer amount of code available online and focus on automated improvement of non-functional properties of software, such as energy or memory consumption. Dr. Petke is a world-leading expert on genetic improvement, publishing award-winning work on automated software specialisation and transplantation. She won two `Humies' awarded for human-competitive results produced by genetic and evolutionary computation and a best paper award at the International Symposium on Software Testing and Analysis. This work was also widely covered in media, including the Wired magazine and BBC Click. The potential of genetic improvement for automating certain aspects of the software development process has thus been already recognised in the academic community and beyond.Dr. Petke will collaborate with a UK-based company, called Satalia, which provides the latest optimisation techniques to the industry. She will apply deliverables of this project to automatically adapt and speed-up their generalist optimisation algorithms to particular classes of real-world problems. An example is specialisation of a general routing program to devising an optimal network for broadband connections. Therefore, the deliverables of this project will contribute to the UK economy by providing techniques that will automate the process of software specialisation for real-world optimisation problems.
该奖学金将通过将软件专业化的挑战性和耗时的任务从人类转移到机器来改变软件开发的面貌。它将开发新的方法,以自动化的方式专门化和提高特定应用领域的通用软件的效率。开发的技术将是程序不可知的,因此适用于任何类型的软件。因此,它们将允许加速例如在生物信息学或医疗保健领域中出现的计算密集型计算。因此,该奖学金可以通过提供一种自动化的方式来适应和加速在研究和工业领域中大量使用的现有软件,从而有助于推动其他研究领域的研究开发。该项目将利用和开发软件工程领域的新方法,称为遗传改进,以实现项目的目标。遗传改良是一个新的研究领域,在过去几年中才作为一个独立的领域出现。有几个因素促成了这一领域的发展和成功,其中之一是大量的在线代码,并专注于自动改进软件的非功能属性,如能源或内存消耗。Petke博士是世界领先的遗传改良专家,在自动化软件专业化和移植方面发表了获奖作品。她因遗传和进化计算产生的与人类竞争的结果而获得两项“Humies”奖,并在国际软件测试与分析研讨会上获得最佳论文奖。这项工作也被媒体广泛报道,包括《连线》杂志和BBC点击。因此,基因改良在软件开发过程某些方面的自动化潜力已经得到学术界和其他领域的认可。Petke博士将与一家名为Satalia的英国公司合作,该公司为行业提供最新的优化技术。她将应用这个项目的交付成果,自动适应和加速他们的通才优化算法,以特定类别的现实世界的问题。一个例子是专门的一般路由程序,以设计一个最佳的网络宽带连接。因此,该项目的交付成果将有助于英国经济提供技术,将自动化的过程中,软件专业化的现实世界的优化问题。

项目成果

期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Refining Fitness Functions for Search-Based Program Repair
Synthetic Benchmarks for Genetic Improvement
遗传改良的综合基准
  • DOI:
    10.1145/3387940.3392175
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Blot A
  • 通讯作者:
    Blot A
Stack-Based Genetic Improvement
基于堆栈的遗传改进
  • DOI:
    10.1145/3387940.3392174
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Blot A
  • 通讯作者:
    Blot A
Using Genetic Improvement to Optimise Optimisation Algorithm Implementations
使用遗传改进来优化优化算法的实现
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Blot A.
  • 通讯作者:
    Blot A.
Genetic Programming - 23rd European Conference, EuroGP 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15-17, 2020, Proceedings
基因编程 - 第 23 届欧洲会议,EuroGP 2020,作为 EvoStar 2020 的一部分,于 2020 年 4 月 15-17 日在西班牙塞维利亚举行,会议记录
  • DOI:
    10.1007/978-3-030-44094-7_5
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Blot A
  • 通讯作者:
    Blot A
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Justyna Petke其他文献

SearchGEM5: Towards Reliable Gem5 with Search Based Software Testing and Large Language Models
SearchGEM5:通过基于搜索的软件测试和大型语言模型迈向可靠的 Gem5
Large language model based mutations in genetic improvement
  • DOI:
    10.1007/s10515-024-00473-6
  • 发表时间:
    2025-01-21
  • 期刊:
  • 影响因子:
    3.100
  • 作者:
    Alexander E. I. Brownlee;James Callan;Karine Even-Mendoza;Alina Geiger;Carol Hanna;Justyna Petke;Federica Sarro;Dominik Sobania
  • 通讯作者:
    Dominik Sobania
Hot Patching Hot Fixes: Reflection and Perspectives
热补丁Hot Fix:反思与视角
On Reducing Network Usage with Genetic Improvement
通过基因改进减少网络使用
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    James Callan;W. B. Langdon;Justyna Petke
  • 通讯作者:
    Justyna Petke
Comparative Analysis of Constraint Handling Techniques for Constrained Combinatorial Testing
约束组合测试的约束处理技术的比较分析
  • DOI:
    10.1109/tse.2019.2955687
  • 发表时间:
    2019-11
  • 期刊:
  • 影响因子:
    7.4
  • 作者:
    Huayao Wu;Changhai Nie;Justyna Petke;Yue Jia;Mark Harman
  • 通讯作者:
    Mark Harman

Justyna Petke的其他文献

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