摘要人类生活中到处都充斥着数据,比如医疗数据,科学数据,销售数据,金融数据,人口普查数据等等。随着信息化的深入,人们的关注点从单纯的数据转到如何处理这些数据。对于海量的,无规则杂乱的数据,人们十分需要一种技术将传统的数据分析知识与整理海量数据的复杂方法有机结合起来。于是,我们必需找到应用的要领,主动的分析数据,主动的把数据进行分类,主动的汇总数据,主动的发现并且描述数据中的走势,主动的标识出异常情况。这是数据最有价值的方面之一,但是仅仅依靠统计学方法和数据库的查询检索功能很难有效利用这些信息。78423
当代软件工程中,有很多问题无法使用传统的方法或者传统的工具来解决它,比如管理和分析非结构化的需求文件,协调并且优化管理开发团队,更加快速并且更加准确的自动编写代码等。随着软件工程数据日益积累,众多问题可以在软件测试的过程中通过数据挖掘技术进行解决。数据挖掘技术可在自动化脚本中辅助理解代码,自动推荐代码,在软件测试中发挥了极大的作用。
毕业论文关键词:数据挖掘,软件测试,自动化,脚本稳定性。
Abstract Human life everywhere is filled with data everywhere, such as medical data, scientific data, sales data, financial data, census data and so on。 With the development of information technology, people' attention varies from the simple data to how to deal with these data。 For the massive, irregular and disorderly data, people need a kind of technology to combine the traditional data analysis knowledge and the complex method of the mass data。 So, we must find the application essentials, actively analyze data, classify the data, aggregate the data, discover and describe the trend of the data, and identify the abnormal situation, which is also one of the most valuable aspects data。 But it is very difficult to apply the information effectively to just rely on statistical methods, query and search function of database。
In modern software engineering, there are many problems that cannot be solved by traditional methods or tools, such as managing and analyzing unstructured requirements documents, coordinating and optimizing the development team, writing the code rapidly and accurately etc。 With the increasing accumulation of software engineering data, many problems can be solved by the data mining technology in the process of software testing。 Data mining techniques can be assisted to understand the code in the automation scripts, recommended code automatically, played a great role in the software testing。
Keywords: Data mining, software testing, automation, stability of the script。
目 录
第一章 绪论 1
1。1 研究的背景,目的与研究意义 1
1。1。1 研究的背景 1
1。1。2 研究的目的与研究的意义 1
第二章 数据挖掘概论 2
2。1 数据挖掘概念 2
2。2 数据挖掘的发展过程 2
2。3 数据挖掘的应用 3
2。4 数据挖掘的基础流程 数据挖掘在自动化脚本稳定性中的应用:http://www.youerw.com/shuxue/lunwen_90367.html