Mining Software Repositories to Support the Development and Operation of Ultra Large Scale Software Systems
挖掘软件存储库以支持超大规模软件系统的开发和运营
基本信息
- 批准号:RGPIN-2014-06414
- 负责人:
- 金额:$ 3.93万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2018
- 资助国家:加拿大
- 起止时间:2018-01-01 至 2019-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The Mining Software Repositories (MSR) field explores innovative approaches to recover useful information from static record-keeping software repositories like source control and bug tracking systems. The recovered information is used to gain an empirically based understanding of software development practices. This knowledge helps practitioners predict, plan and understand various aspects of their project. Over the past decade, the international MSR community has explored innovative approaches to recover useful and actionable information from such static record-keeping repositories. MSR techniques are now integrated into developer toolkits at some of the world's largest and most successful organizations: Microsoft, BlackBerry, AT&T Labs, CISCO, Mozilla and Avaya.As one of the founders of the MSR field, I believe that the full potential of MSR can only be achieved by taking MSR results and techniques beyond software development challenges. My ultimate goal is to establish MSR as a strategic decision-making instrument throughout the lifetime of software systems. However, the focus of research today remains on traditional software development where a clear separation exists between the development of the software and its operation, with development cycles lasting months or years. This separation is a key challenge to Ultra Large Scale (ULS) software services where fast and frequent releases are the norm. There is a clear need to leverage knowledge from both the development and the operation of software services. Two examples of benefits arising from this knowledge integration are: i) developers can use operation knowledge (e.g., logs) to better understand how their code is used in the field so they can optimize it, and fix or prioritize the fixing of bugs more effectively; and ii) operators can make use of source code documentation to rapidly understand, triage and resolve field problems.The long-term vision of the proposed program is to systematically uncover the potential and to empirically demonstrate the benefits of MSR in delivering significant improvements in the reliability and cost-effectiveness of today's long-lived rapidly-evolving software. Short term goals over the next five years will focus on realizing this vision in collaboration with industry partners like BlackBerry, SAP and Avaya. Over the next five years the research program will progress along the following two themes: (1) the recovery, representation and linking of development and operation knowledge in a simple format in order to ease access to such knowledge; and (2) the development of methodologies, tools and approaches that explore and demonstrate the benefits of MSR in understanding and supporting software development and operation activities.In particular, the proposed research program will focus on the use of system logs as a mechanism to bridge the gap between software development and operation. Logs are messages generated from statements inserted by developers in the source code and are often used by operators for monitoring the field operation of a system. However, the rich knowledge in logs has not yet been fully-used because of their non-structured nature, their large scale, and the use of ad-hoc log analysis techniques.The research program proposed will train five highly qualified personnel (HQP): 3 PhD and 2 Master's students. All HQP will collaborate closely with Canadian companies, gaining an appreciation of the challenges facing practitioners on a daily basis and the potential of software data in addressing those challenges.
采矿软件存储库(MSR)领域探索了从静态记录保存软件存储库(如源代码控制和错误跟踪系统)中恢复有用信息的创新方法。恢复的信息用于获得基于经验的软件开发实践的理解。这些知识可以帮助从业者预测,计划和理解他们项目的各个方面。在过去的十年中,国际MSR社区探索了创新的方法来从这种静态记录保存库中恢复有用和可操作的信息。MSR技术现已集成到世界上一些最大和最成功的组织的开发人员工具包中:Microsoft,BlackBerry,AT&T Labs,CISCO,Mozilla和Avaya。作为MSR领域的创始人之一,我相信只有将MSR结果和技术超越软件开发挑战才能实现MSR的全部潜力。我的最终目标是在软件系统的整个生命周期中将MSR作为一种战略决策工具。然而,今天的研究重点仍然是传统的软件开发,其中软件的开发和运行之间存在着明显的分离,开发周期持续数月或数年。这种分离是超大规模(ULS)软件服务的一个关键挑战,在这种服务中,快速和频繁的发布是常态。显然需要利用软件服务的开发和运营方面的知识。从这种知识集成产生的益处的两个示例是:i)开发人员可以使用操作知识(例如,日志),以更好地了解他们的代码是如何在现场使用的,这样他们就可以优化它,并更有效地修复或优先修复错误;以及ii)操作员可以利用源代码文档来快速理解,分流和解决现场问题。长期-该计划的长期目标是系统地揭示MSR的潜力,并通过经验证明MSR在实现重大改进方面的好处,可靠性和成本效益的今天的长寿快速发展的软件。未来五年的短期目标将集中在与BlackBerry,SAP和Avaya等行业合作伙伴合作实现这一愿景。在今后五年中,研究计划将沿着以下两个主题取得进展:(1)以简单的格式恢复、表示和连接开发和运营知识,以便于获取这些知识;以及(2)开发方法、工具和方法,以探索和展示MSR在理解和支持软件开发和操作活动方面的好处。特别是,拟议的研究计划将集中于使用系统日志作为一种机制,以弥合软件开发和操作之间的差距。消息是由开发人员在源代码中插入的语句生成的消息,通常由操作员用于监视系统的现场操作。然而,由于日志的非结构化性质,其庞大的规模,并使用ad-hoc日志分析技术,丰富的知识尚未得到充分利用。所有HQP将与加拿大公司密切合作,了解从业人员每天面临的挑战以及软件数据在应对这些挑战方面的潜力。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Hassan, Ahmed其他文献
Efficacy of Histidine-Tryptophan-Ketoglutarate Solution Versus Blood Cardioplegia in Cardiac Surgical Procedures: A Randomized Controlled | Parallel Group Study
- DOI:
10.1532/hsf.3495 - 发表时间:
2021-01-01 - 期刊:
- 影响因子:0.6
- 作者:
Ali, Ihab;Hassan, Ahmed;Khorshed, Ramy - 通讯作者:
Khorshed, Ramy
USE OF CARBON NANOTUBES IN THE RETROFITTING OF REINFORCED CONCRETE BEAMS WITH AN OPENING AND THE EFFECT OF DIRECT FIRE ON THEIR BEHAVIOUR
- DOI:
10.21660/2018.44.01175 - 发表时间:
2018-04-01 - 期刊:
- 影响因子:0.7
- 作者:
Hassan, Ahmed;Shoeib, Ata El-kareim;Abd El-Magied, Mostafa - 通讯作者:
Abd El-Magied, Mostafa
Thermal and Structural Characterization of Geopolymer-Coated Polyurethane FoamPhase Change Material Capsules/Geopolymer Concrete Composites
- DOI:
10.3390/ma12050796 - 发表时间:
2019-03-01 - 期刊:
- 影响因子:3.4
- 作者:
Hassan, Ahmed;Rashid, Yasir;Laghari, Mohammad Shakeel - 通讯作者:
Laghari, Mohammad Shakeel
A dynamic thermal response on thermal conductivity at different temperature and moisture levels of EPS insulation
- DOI:
10.1016/j.csite.2019.100481 - 发表时间:
2019-09-01 - 期刊:
- 影响因子:6.8
- 作者:
Khoukhi, Maatouk;Hassan, Ahmed;Abdelbaqi, Shaimaa - 通讯作者:
Abdelbaqi, Shaimaa
Impact of fentanyl use on initiation and discontinuation of methadone and buprenorphine/naloxone among people with prescription-type opioid use disorder: secondary analysis of a Canadian treatment trial.
- DOI:
10.1111/add.15954 - 发表时间:
2022-10 - 期刊:
- 影响因子:6
- 作者:
Socias, M. Eugenia;Wood, Evan;Le Foll, Bernard;Lim, Ron;Choi, Jin Cheol;Mok, Wing Yin;Bruneau, Julie;Rehm, Juergen;Wild, T. Cameron;Bozinoff, Nikki;Hassan, Ahmed;Jutras-Aswad, Didier - 通讯作者:
Jutras-Aswad, Didier
Hassan, Ahmed的其他文献
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{{ truncateString('Hassan, Ahmed', 18)}}的其他基金
Leveraging development and field knowledge to assist developers and operators of large software systems
利用开发和现场知识来协助大型软件系统的开发人员和操作人员
- 批准号:
RGPIN-2019-05174 - 财政年份:2022
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
Ensuring the Trustworthiness of Data Science Systems in a Cost Effective Manner
以具有成本效益的方式确保数据科学系统的可信度
- 批准号:
533280-2018 - 财政年份:2021
- 资助金额:
$ 3.93万 - 项目类别:
Collaborative Research and Development Grants
Leveraging development and field knowledge to assist developers and operators of large software systems
利用开发和现场知识来协助大型软件系统的开发人员和操作人员
- 批准号:
RGPIN-2019-05174 - 财政年份:2021
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
Ensuring the Trustworthiness of Data Science Systems in a Cost Effective Manner
以具有成本效益的方式确保数据科学系统的可信度
- 批准号:
533280-2018 - 财政年份:2020
- 资助金额:
$ 3.93万 - 项目类别:
Collaborative Research and Development Grants
Leveraging development and field knowledge to assist developers and operators of large software systems
利用开发和现场知识来协助大型软件系统的开发人员和操作人员
- 批准号:
RGPIN-2019-05174 - 财政年份:2020
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
Nomination for NSERC Steacie Memorial Fellowship
NSERC Steacie 纪念奖学金提名
- 批准号:
522373-2018 - 财政年份:2019
- 资助金额:
$ 3.93万 - 项目类别:
EWR Steacie Fellowships - Supplement
Leveraging development and field knowledge to assist developers and operators of large software systems
利用开发和现场知识来协助大型软件系统的开发人员和操作人员
- 批准号:
RGPIN-2019-05174 - 财政年份:2019
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
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Applying Machine Learning Algorithms in Mining Software Repositories
在挖掘软件存储库中应用机器学习算法
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- 资助金额:
$ 3.93万 - 项目类别:
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挖掘软件存储库和信息可视化,以对可变软件进行实证稳健测试
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