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Toward Scalable Software Engineering Disciplines

Toward Scalable Software Engineering Disciplines
迈向可扩展的软件工程学科
批准号:
9311702
负责人:
Bruce Weide
金额:
$32.39万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1993
资助国家:
美国
项目状态:
已结题
起止时间:
1993-09-01 至 1997-08-31

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中文摘要
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英文摘要
9311702 Weide Zweben Ogden This research addresses the technical problems impeding the development of software systems as assemblages of off-the- shelf reusable components. Substantial progress has been made in defining component engineering principles and in developing a collection of interoperable components. Each component is designed for maximal reusability and, before inclusion in a component library, is subjected to quality control procedures by which it is certified to have certain properties: correctness with respect to a formal specification, freedom from storage leaks, an essential level of efficiency, etc. The purpose of a component's certification is to give prospective clients critical assurance that the component is truly suitable for reuse. The primary goals of the work are to: * Identify specific properties for which local certifiability is essential or advantageous to the process of obtaining high-quality software systems from high-quality components. * Determine and state precisely those characteristics that a client program and the other components it employs must possess, in order that locally certified components can be guaranteed to behave as advertised in that client's context. * Investigate specific techniques for the local certification of various important properties of software. ***
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会议论文
SHF: Medium: Collaborative Research: Specification and Mathematics Engineering for the Verified Software End-Game
  • 批准号:
    1162331
  • 项目类别:
    Standard Grant
  • 资助金额:
    $47.61万
  • 财政年份:
    2012
  • 负责人:
    Bruce Weide
  • 依托单位:
Automated Support for Developing Logical Reasoning Skills in Discrete Mathematics Courses
CPA-SEL: Collaborative Research - Continuing Progress Toward Verified Software
Collaborative Research: Logical Support for Formal Verification
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海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis