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软件专业实训课程体系研究
  • ISSN号:1672-5913
  • 期刊名称:《计算机教育》
  • 时间:0
  • 分类:TP311[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]福建工程学院,福州350108, [2]厦门理工学院,福建厦门361024, [3]复旦大学软件学院,上海201203
  • 相关基金:国家自然科学基金项目(61402108); 福建省中青年教师教育科研项目(JA14221,JA13238); 福建工程学院科研启动基金项目(GYZ13113,GY-Z14068)
作者: 王金水[1]
中文摘要:

软件需求跟踪已被公认为影响软件项目成败的一个关键因素.针对大多数基于信息检索的需求跟踪方法都严重依赖于软件制品中的文本质量,提出了一种基于句法分析的动态需求跟踪方法.该方法能够从制品中抽取最有可能刻画自身特征的标引词,并减少制品中噪音对需求跟踪带来的不利影响.为了验证该方法的有效性,在多个来自不同项目且类型不同的软件制品上,比较了基于不同标引词集合的动态需求跟踪方法所建立的跟踪关系.实验结果表明,基于句法分析的动态需求跟踪方法能够有效地提高跟踪关系的准确性.

英文摘要:

Software requirement traceability has been globally recognized as a key factor of affecting the success of software projects.The generated traceability links are vital to many software engineering and software verification and validation(VV)activities such as change impact analysis,software reuse and consistency checking. Addressing most existing requirement traceability approaches based on information retrieval are strongly affected by the quality of the documentation of different types of software artifacts,this paper presents a dynamic requirement traceability approach based on syntactic analysis.The proposed approach is able to extract terms which are most likely to characterize itself from text-based software artifacts such as source code and requirement document,and then reduce the adverse effects of noise in artifacts to the requirement tracing process.In order to verify the effectiveness of the proposed approach,we have compared the quality of the trace links produced by several dynamic requirement traceability approaches on three open source software systems and six types of software artifacts.The result suggests that the dynamic requirement traceability approach based on syntactic analysis can effectively improve the accuracy of the produced trace links.

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期刊信息
  • 《计算机教育》
  • 主管单位:教育部
  • 主办单位:清华大学
  • 主编:奚春燕
  • 地址:北京市海淀区双清路清华大学学研大厦B座606室
  • 邮编:100084
  • 邮箱:jsjjy@vip.163.com
  • 电话:010-62770175-3402-3406
  • 国际标准刊号:ISSN:1672-5913
  • 国内统一刊号:ISSN:11-5006/TP
  • 邮发代号:80-171
  • 获奖情况:
  • 国内外数据库收录:
  • 被引量:26095