Mining Numerical Relations for Improving Software Reliability

Bo Zhang
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Abstract

This research aims to mine numerical relations from programs and use the relations to improve program reliability. We focus on two types of numerical relations: relations from program inputs and outputs (i.e., metamorphic relations) and workflow relations from software logs. For metamorphic relations from program inputs and outputs, we design two approaches: for polynomial relations, we propose a method to firstly parameterize the metamorphic relations, then use search-based method to find the suitable parameters; for general forms of numerical relations, we plan to adopt genetic programming techniques which have the potential to evolve and produce relations of various types. For workflow relations from program logs, we parse the raw logs to event sequences and propose an approach to mine numerical relations from the event-count-matrix of the sequences. To improve software reliability, the mined metamorphic relations can be used to detect bugs and the mined workflow relations can be used to detect anomalies.
挖掘数值关系提高软件可靠性
本研究旨在从程序中挖掘数值关系,并利用这些关系来提高程序的可靠性。我们关注两种类型的数值关系:来自程序输入和输出的关系(即,变形关系)和来自软件日志的工作流关系。对于程序输入和输出的变质关系,我们设计了两种方法:对于多项式关系,我们提出了一种方法,首先对变质关系进行参数化,然后使用基于搜索的方法找到合适的参数;对于一般形式的数值关系,我们计划采用具有进化和产生各种类型关系的潜力的遗传规划技术。对于程序日志中的工作流关系,我们将原始日志解析为事件序列,并提出了一种从序列的事件计数矩阵中挖掘数字关系的方法。为了提高软件的可靠性,挖掘出的变形关系可以用来检测错误,挖掘出的工作流关系可以用来检测异常。
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