Enhancing program comprehension with recovered state models
Enhancing program comprehension with recovered state models
复制标题
通过恢复的状态模型增强程序理解
DOI：
10.1109/wpc.2002.1021325
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
T. Lethbridge
中科院分区：
文献类型：
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作者：
S. Somé;T. Lethbridge
状态转换机是一种高级行为描述，通常用作设计和实现一大类软件系统的建模工具。一些状态转换机实现方法使得结果代码的静态结构与原始状态转换机的静态结构紧密匹配。因此，具有原始状态转换机的表示可能会提高相应代码的可理解性。我们提出了一种方法支持的原型工具，提取状态转换机的静态分析的源代码。这项工作的一个目标是提高程序的理解与视觉表示的行为的程序进行分析。
State transition machines are high-level behavior descriptions often used as modeling tools for the design and implementation of a large class of software systems. Some of the state transition machine implementation approaches are such that the static structure of the resulting code closely matches that of the original state transition machines. Therefore, having a representation of the original state transition machines is likely to improve the corresponding code understandability. We present an approach supported by a prototype tool, to extract state transition machines by static analysis of source code. An objective of this work is to enhance program comprehension with visual representations of the behavior of the programs being analyzed.