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Conceptual complexity measures and software maintenance tools for rule-based programs

机译:基于规则的程序的概念复杂性度量和软件维护工具

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This paper presents an approach for measuring and controlling the conceptual complexity of rule-based programs. A program representation, a collection of complexity measures, and a workbench of software maintenance tools are described.;The program representation consists of transformations and an abstracted initial working memory configuration. Our representation does not retain knowledge of the individual facts stored in working memory. Instead, all of the facts that belong to the same class are abstracted into a single conceptual object. Transformations are rule abstractions that retain knowledge of the conceptual objects matched, created, and modified by a rule.;Ten conceptual complexity measures, based on our program representation, were defined. These measures were divided into three broad classes: bulk measures, which measure program size; rule measures, which measure the degree of complexity within and between program rules; and group measures, which are concerned with the complexity of collections of rules.;Restricted Flow Graphs (RFG) were defined for rule-based programs, and algorithms for their computation were presented. These graphs consist of nodes representing abstracted working memory configurations together with edges that represent program rules. These graphs are designed to capture the way rule-based programs execute and are analogous to control flow graphs for procedural programs. A measure of RFG complexity based on McCabe's measure was defined.;A workbench of software maintenance tools was developed from the measures of conceptual complexity. The Bulk Analysis Tool computes and displays a summary of the bulk measures for a program, together with the names of the conceptual objects used by that program and their frequency of occurrence. Similarly, the Rule Summary Tool presents the rule-based measures for each rules in the program being analyzed. The Rule Analysis Tool displays a graphical representation of the way in which a single rule interacts with other rules in a program, through the conceptual objects it manipulates. All of these tools were implemented in C on Sun workstations and are fully integrated into the SunWindows environment.;A pilot study was conducted to determine the applicability of the measures and the effectiveness of the tools. Several of the measures correlated well with participant responses.
机译:本文提出了一种用于测量和控制基于规则的程序的概念复杂性的方法。描述了程序表示,复杂性度量的集合和软件维护工具的工作台。该程序表示包括转换和抽象的初始工作内存配置。我们的表示不保留对工作内存中存储的各个事实的了解。而是将属于同一类的所有事实抽象为单个概念对象。转换是规则抽象,保留了由规则匹配,创建和修改的概念对象的知识。基于我们的程序表示,定义了十个概念复杂性度量。这些措施分为三大类:总体措施,用于衡量计划规模;以及规则度量,用于度量程序规则内部和程序规则之间的复杂程度;针对规则集的复杂性,定义了受限流图(RFG),并给出了其计算算法。这些图由代表抽象工作内存配置的节点以及代表程序规则的边组成。这些图旨在捕获基于规则的程序的执行方式,并类似于过程程序的控制流程图。定义了基于McCabe测度的RFG复杂度测度。从概念复杂度测度开发了软件维护工具工作台。批量分析工具计算并显示程序的批量度量的摘要,以及该程序使用的概念对象的名称及其出现的频率。同样,规则摘要工具为要分析的程序中的每个规则提供基于规则的度量。规则分析工具通过其操纵的概念对象显示单个规则与程序中其他规则交互方式的图形表示。所有这些工具都是在Sun工作站的C语言中实现的,并且已完全集成到SunWindows环境中。进行了一项初步研究,以确定这些措施的适用性和工具的有效性。几种措施与参与者的反应密切相关。

著录项

  • 作者

    O'Neal, Micheal B.;

  • 作者单位

    University of Southwestern Louisiana.;

  • 授予单位 University of Southwestern Louisiana.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 1989
  • 页码 157 p.
  • 总页数 157
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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