A Framework to Combine Semantic and Structural Information for Static Analysis

结合语义和结构信息进行静态分析的框架

• 批准号: 0204175
• 负责人: Jonathan Maletic
• 金额: $ 15万
• 依托单位: Kent State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2005-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0204175&HistoricalAwards=false
• 关键词: Framework; Combine; Semantic; Structural; Information

ABSTRACTJonathan I MaleticKent State U0204175A Framework to Combine Semantic and Structural Information for Static AnalysisJonathan I. MaleticThe research involves combining semantic and structural information of program source code for the static analysis of software. Static analysis normally takes into consideration only structural information of the source code. The research investigates the use of information concerning the domain semantics to enhance existing static analysis methods. The semantic information is derived from the comments, documentation, and identifier names associated with the source code. A framework will be developed that allows the combination of semantic and structural information of the source code. The framework will provide means to compute new measures and metrics that describe the software (e.g., cohesion and coupling). Additionally, the research will study different information retrieval methods and how they can be used to extract relevant semantic information from the source code. An empirical assessment of the framework and the use of semantic information for static analysis will be undertaken. Combining semantic information with existing static analysis methods will result in new and improved analysis tools. These tools will help software engineers better analyze, maintain, and assess the quality of large software systems.

AbstractJonathan I Maletickent State U0204175A框架结合了语义和结构信息以进行静态分析。 静态分析通常仅考虑源代码的结构信息。 该研究调查了有关域语义的信息的使用来增强现有的静态分析方法。 语义信息来自与源代码关联的注释，文档和标识符名称。 将开发一个框架，允许源代码的语义和结构信息组合。 该框架将提供计算描述软件的新措施和指标（例如，凝聚力和耦合）的方法。 此外，研究将研究不同的信息检索方法，以及如何使用它们从源代码中提取相关的语义信息。 将对框架和使用语义信息进行静态分析的经验评估。 将语义信息与现有的静态分析方法相结合将导致新的和改进的分析工具。 这些工具将帮助软件工程师更好地分析，维护和评估大型软件系统的质量。