Lightweight Modeling to Improve Requirements Engineering of Enterprise Software

轻量级建模改进企业软件的需求工程

基本信息

  • 批准号:
    262100-2012
  • 负责人:
  • 金额:
    $ 3.06万
  • 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:
    2015
  • 资助国家:
    加拿大
  • 起止时间:
    2015-01-01 至 2016-12-31
  • 项目状态:
    已结题

项目摘要

The Standish Group's 1994 CHAOS Report cites requirements-related problems as the main reason for the failure of over half of the 8,380 surveyed projects, with a majority of them in the enterprise software domain. According to Boehm, correcting requirements errors in later development phases can cost up to 200 times as much as correcting them in the requirements phase. Thus, finding requirements errors early is critical. The overarching goal of this research is to improve the effectiveness (fewer errors) and efficiency (higher speed) of requirements engineering for enterprise software (REES) via lightweight modeling. We will develop a combination of a method, language, and tools to create precise models and designed to deliver maximum value while focusing on usability. Precise models reduce errors due miscommunication among project stakeholders, avoiding rework and improving software quality. Wide adoption of precise modeling has the potential to significantly improve the effectiveness and efficiency of engineering complex software-intensive systems. The proposed research will have immediate benefit for our industrial collaborators, improving their capabilities to determine requirements of enterprise systems. In the longer term, lightweight modeling will contribute to the wide adoption of precise modeling across different domains and the entire engineering cycle, reducing software faults-which impact negatively the society today-and allowing the software industry to build even more complex systems to address tomorrow's needs.
Standish Group在1994年的CHAOS报告中指出,需求相关的问题是8,380个被调查项目中一半以上失败的主要原因,其中大部分是在企业软件领域。根据Boehm的说法,在后期开发阶段纠正需求错误的成本可能是在需求阶段纠正的200倍。因此,尽早发现需求错误是至关重要的。 本研究的总体目标是通过轻量级建模提高企业软件需求工程(REES)的有效性(更少的错误)和效率(更高的速度)。我们将开发一种方法,语言和工具的组合,以创建精确的模型,并旨在提供最大的价值,同时专注于可用性。精确的模型减少了由于项目涉众之间的错误沟通而导致的错误,避免了返工并提高了软件质量。 广泛采用精确建模有可能显着提高工程复杂的软件密集型系统的有效性和效率。拟议的研究将为我们的工业合作者带来直接利益,提高他们确定企业系统需求的能力。从长远来看,轻量级建模将有助于在不同领域和整个工程周期中广泛采用精确建模,减少对当今社会产生负面影响的软件故障,并允许软件行业构建更复杂的系统以满足未来的需求。

项目成果

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Czarnecki, Krzysztof其他文献

A fast time-frequency multi-window analysis using a tuning directional kernel
  • DOI:
    10.1016/j.sigpro.2018.01.019
  • 发表时间:
    2018-06-01
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    Czarnecki, Krzysztof;Fourer, Dominique;Rojewski, Miroslaw
  • 通讯作者:
    Rojewski, Miroslaw
A Study of Variability Models and Languages in the Systems Software Domain
  • DOI:
    10.1109/tse.2013.34
  • 发表时间:
    2013-12-01
  • 期刊:
  • 影响因子:
    7.4
  • 作者:
    Berger, Thorsten;She, Steven;Czarnecki, Krzysztof
  • 通讯作者:
    Czarnecki, Krzysztof
A three-dimensional taxonomy for bidirectional model synchronization
  • DOI:
    10.1016/j.jss.2015.06.003
  • 发表时间:
    2016-01-01
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Diskin, Zinovy;Gholizadeh, Hamid;Czarnecki, Krzysztof
  • 通讯作者:
    Czarnecki, Krzysztof
The instantaneous frequency rate spectrogram
A case study on consistency management of business and IT process models in banking
银行业业务与IT流程模型一致性管理案例研究
  • DOI:
    10.1007/s10270-013-0318-8
  • 发表时间:
    2014-07
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Xiong, Yingfei;Czarnecki, Krzysztof;Kuster, Jochen;Volzer, Hagen
  • 通讯作者:
    Volzer, Hagen

Czarnecki, Krzysztof的其他文献

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{{ truncateString('Czarnecki, Krzysztof', 18)}}的其他基金

A safety-assured architecture for AI-enabled autonomous vehicles
支持人工智能的自动驾驶汽车的安全架构
  • 批准号:
    RGPIN-2022-03944
  • 财政年份:
    2022
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Discovery Grants Program - Individual
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    RGPIN-2017-04733
  • 财政年份:
    2021
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Discovery Grants Program - Individual
Scalable and Interoperable Simulation for Testing Automated Vehicles
用于测试自动驾驶车辆的可扩展且可互操作的仿真
  • 批准号:
    571264-2022
  • 财政年份:
    2021
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Idea to Innovation
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    RGPIN-2017-04733
  • 财政年份:
    2020
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Discovery Grants Program - Individual
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    RGPIN-2017-04733
  • 财政年份:
    2019
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Discovery Grants Program - Individual
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    507922-2017
  • 财政年份:
    2019
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    DGDND-2017-00077
  • 财政年份:
    2019
  • 资助金额:
    $ 3.06万
  • 项目类别:
    DND/NSERC Discovery Grant Supplement
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    RGPIN-2017-04733
  • 财政年份:
    2018
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Discovery Grants Program - Individual
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    DGDND-2017-00077
  • 财政年份:
    2018
  • 资助金额:
    $ 3.06万
  • 项目类别:
    DND/NSERC Discovery Grant Supplement
Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles
自动驾驶汽车智能控制器的基于模型的综合和安全保证
  • 批准号:
    507922-2017
  • 财政年份:
    2018
  • 资助金额:
    $ 3.06万
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements

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