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An assistant framework for procuring components and code samples.

机译:用于采购组件和代码示例的辅助框架。

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摘要

Software reuse has been targeted as a panacea for reducing software costs and for improving both software quality and programmer productivity. Today, it is accepted practice for software developers to reuse software units, that range from ascii units such as code fragments, to binary units such as functions, modules and even entire application systems, to both guide and reduce their development efforts. These software units are typically bundled with library or framework packages, are available as in-house and off-the-shelf components, or are accessible via books, manuals, web sites, live application code and code that the developer has written previously. Software unit procurement is the first key step of the reuse process at the software implementation stage, and is often broken down into component procurement and code sample procurement based on the two popular types of software units. While tools exist to assist developers in this procurement process, the tools are limited in their capabilities by the type of queries they provide, the efficient matching/mining techniques that underlie the procurement process and the effective ranking techniques used to evaluate the procured units. We broadly classify these limitations as quality of procured units and the effective ranking of the same.; This dissertation contributes solutions that address the quality and ranking of retrieved software units. As part of this dissertation, we have developed two assistant frameworks, the XML-based Component Discovery and Evaluation (XCoDE) framework and the XML-based Code Snippet Mining and Ranking (XSnippet) framework for procuring components and code samples, respectively.; The XCoDE framework allows developers to query for components based on the component information. Our approach is based on a unique Quality of Match (QoM) metric that qualitatively and quantitatively evaluates the match of two given components. The QoM metric forms the basis for a disciplined application of different matching techniques to all aspects of a component, thereby exploiting the diversity of syntactic and semantic information inherent in a component. Our experiments have shown that XCoDE has significant potential to provide higher accuracy than individual matching techniques and other combination techniques.; The XSnippet framework allows developers to query for code samples based on the context of code under development. Our approach is based on a novel graph-based code mining algorithm that supports the range of object instantiation-specific queries, and an innovative context-sensitive ranking heuristic that has been experimentally proven to provide better ranking of best-fit code samples than context-independent heuristics. Our experimental evaluation has shown that XSnippet has significant potential to assist developers, and provides better coverage of tasks and better rankings for best-fit code samples than other code assistant systems.
机译:软件重用已成为降低软件成本,提高软件质量和提高程序员生产率的灵丹妙药。如今,软件开发人员可以重用软件单元,从代码片段之类的ascii单元到功能,模块乃至整个应用系统之类的二进制单元,以指导和减少他们的开发工作,这是公认的惯例。这些软件单元通常与库或框架软件包捆绑在一起,可以作为内部和现成的组件使用,也可以通过书籍,手册,网站,实时应用程序代码和开发人员先前编写的代码进行访问。软件单元采购是软件实现阶段重用过程的第一步,这是基于两种常见的软件单元类型而分为的组件采购和代码样本采购。虽然存在可协助开发人员进行此采购过程的工具,但这些工具的功能受到其提供的查询类型,作为采购过程基础的有效匹配/挖掘技术以及用于评估采购单位的有效排名技术的限制。我们将这些限制大致归类为采购单位的质量及其有效排名。本文为解决检索到的软件单元的质量和排名提供了解决方案。作为本论文的一部分,我们开发了两个辅助框架,分别是基于XML的组件发现和评估(XCoDE)框架和基于XML的代码片段挖掘和排名(XSnippet)框架,用于分别获取组件和代码样本。 XCoDE框架允许开发人员根据组件信息查询组件。我们的方法基于独特的匹配质量(QoM)指标,该指标定性和定量地评估两个给定组件的匹配。 QoM度量构成了将不同的匹配技术严格应用到组件各个方面的基础,从而利用了组件固有的语法和语义信息的多样性。我们的实验表明,XCoDE具有比单独的匹配技术和其他组合技术更高的准确性的巨大潜力。 XSnippet框架允许开发人员根据正在开发的代码的上下文来查询代码示例。我们的方法基于一种新颖的基于图的代码挖掘算法,该算法支持特定于对象实例化查询的范围,以及一种经过创新证明的上下文敏感排名启发式方法,该方法已被实验证明比上下文上下文提供更好的最佳匹配代码样本排名。独立启发式。我们的实验评估表明,与其他代码助手系统相比,XSnippet具有极大的潜力来协助开发人员,并提供最佳的代码示例更好的任务覆盖范围和更好的排名。

著录项

  • 作者

    Tansalarak, Naiyana.;

  • 作者单位

    University of Massachusetts Lowell.;

  • 授予单位 University of Massachusetts Lowell.;
  • 学科 Computer Science.
  • 学位 Sc.D.
  • 年度 2006
  • 页码 189 p.
  • 总页数 189
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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