發(fā)布時(shí)間：2018-04-28 08:40

  本文選題：用戶會(huì)話 + Web測(cè)試用例�。� 參考：《中國(guó)礦業(yè)大學(xué)》2014年碩士論文

【摘要】：隨著Web應(yīng)用系統(tǒng)廣泛應(yīng)用于教育、商業(yè)、工業(yè)等領(lǐng)域，Web系統(tǒng)變得越來(lái)越復(fù)雜，一個(gè)項(xiàng)目的失敗將可能導(dǎo)致Web危機(jī)的發(fā)生。在Web工程過(guò)程中，基于Web系統(tǒng)的測(cè)試任務(wù)是一項(xiàng)重要而富有挑戰(zhàn)性的工作，也越來(lái)越得到人們的關(guān)注與重視。Web測(cè)試需要從最終用戶的角度對(duì)Web應(yīng)用系統(tǒng)進(jìn)行可用性及安全性測(cè)試，基于用戶會(huì)話的Web測(cè)試技術(shù)綜合考慮了用戶的訪問(wèn)行為與訪問(wèn)興趣等因素，測(cè)試過(guò)程結(jié)合用戶的真實(shí)數(shù)據(jù)，避免了模擬用戶行為帶來(lái)的測(cè)試偏差，極大的增加了測(cè)試的有效性。 Web測(cè)試的數(shù)據(jù)來(lái)源于IIS服務(wù)器，首先將Web應(yīng)用站點(diǎn)通過(guò)IIS服務(wù)器發(fā)布，并對(duì)日志記錄按需設(shè)置，經(jīng)過(guò)用戶訪問(wèn)站點(diǎn)生成日志文件并進(jìn)行數(shù)據(jù)采集；然后通過(guò)行刪除和列刪除兩項(xiàng)工作對(duì)日志數(shù)據(jù)進(jìn)行數(shù)據(jù)清洗，刪除文件中冗余的信息；其次利用用戶IP、代理類型和引用頁(yè)面集對(duì)數(shù)據(jù)中的隱含用戶進(jìn)行識(shí)別，并利用時(shí)間閾值法對(duì)數(shù)據(jù)信息進(jìn)行劃分形成用戶會(huì)話；最后通過(guò)不同的測(cè)試用例生成策略生成原始的測(cè)試用例集。 由于測(cè)試用例集合中存在著大量冗余的測(cè)試用例，這使測(cè)試過(guò)程在資源及成本方面存在著很大的浪費(fèi)問(wèn)題,所以測(cè)試用例優(yōu)化工作是必不可少的。首先利用頁(yè)面集合和會(huì)話集合得到頁(yè)面訪問(wèn)矩陣V；其次應(yīng)用K-means算法將矩陣化的數(shù)據(jù)信息進(jìn)行劃分，得到合理的聚類集合；最后通過(guò)約簡(jiǎn)方法從各個(gè)分組中選出代表性實(shí)例組成優(yōu)化測(cè)試用例集。針對(duì)新增數(shù)據(jù)信息則采用馬氏增量聚類進(jìn)行處理，，將原始聚類集的k個(gè)中心點(diǎn)作為增量聚類的初始聚類中心，對(duì)新增數(shù)據(jù)進(jìn)行劃分，并不斷調(diào)整變化的聚類集最終完成增量聚類。 通過(guò)對(duì)開(kāi)源Web應(yīng)用系統(tǒng)（Bookshop）進(jìn)行處理分析，并結(jié)合測(cè)試用例生成及優(yōu)化技術(shù)對(duì)數(shù)據(jù)進(jìn)行處理，通過(guò)對(duì)原始用例集和約簡(jiǎn)用例集的比較分析，證實(shí)約簡(jiǎn)技術(shù)的應(yīng)用既能維持測(cè)試用例集的功能覆蓋率與錯(cuò)誤檢測(cè)率，又能減少了資源及成本的消耗。
[Abstract]:As Web applications become more and more complex in the fields of education, commerce, industry and so on, the failure of a project may lead to the occurrence of Web crisis. In the process of Web engineering, testing task based on Web system is an important and challenging task. More and more attention has been paid to the need to test the usability and security of Web applications from the point of view of end users. The Web testing technology based on user session takes into account the user's access behavior and access interest and so on. The testing process combines the user's real data to avoid the test deviation caused by simulating the user's behavior and greatly increases the effectiveness of the test. The data of the Web test comes from the IIS server. Firstly, the Web application site is published through the IIS server, and the log record is set up on demand, and the log file is generated through the user visiting the site and the data is collected. Then the log data is cleaned by row deletion and column deletion, and redundant information in the file is deleted. Secondly, the implicit users in the data are identified by means of user IPs, proxy types and reference page sets. The data information is divided into user sessions by time threshold method, and the original test case set is generated by different test case generation strategies. Because there are a lot of redundant test cases in the set of test cases, there is a great waste of resources and cost in the test process, so it is necessary to optimize the test cases. Firstly, the page access matrix is obtained by using the page set and session set, and then the K-means algorithm is used to divide the data information of the matrix to obtain a reasonable clustering set. Finally, we select representative examples from each group to form the optimized test case set by reduction method. The new data information is processed by Mahalanobis incremental clustering. The k centers of the original clustering set are taken as the initial clustering centers of the incremental clustering, and the new data are divided. Finally, the incremental clustering is completed by adjusting the changing clustering sets. Through processing and analysis of open source Web application system, and combining with test case generation and optimization technology, the data is processed, and the comparison between original use case set and reduction use case set is analyzed. It is proved that the application of reduction can not only maintain the function coverage and error detection rate of test case set, but also reduce the consumption of resources and cost.
【學(xué)位授予單位】：中國(guó)礦業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.09

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 尹文潔;崔冬華;;測(cè)試用例集的約簡(jiǎn)方法研究[J];電腦開(kāi)發(fā)與應(yīng)用;2011年05期

2 吳琪;高瀅;王曉濤;左萬(wàn)利;;一種基于距離的增量聚類算法[J];解放軍理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2005年06期

3 羅可,蔡碧野,吳一帆,謝中科,張麗;數(shù)據(jù)挖掘中聚類的研究[J];計(jì)算機(jī)工程與應(yīng)用;2003年20期

4 許蕾;徐寶文;陳振強(qiáng);;Web測(cè)試綜述[J];計(jì)算機(jī)科學(xué);2003年03期

5 李守振;張南平;常國(guó)鋒;;Web應(yīng)用分層與開(kāi)發(fā)框架設(shè)計(jì)研究[J];計(jì)算機(jī)工程;2006年22期

6 武晉南;高建華;;基于用戶行為和會(huì)話的Web應(yīng)用測(cè)試方法[J];計(jì)算機(jī)工程;2010年08期

7 聶長(zhǎng)海,徐寶文;一種最小測(cè)試用例集生成方法[J];計(jì)算機(jī)學(xué)報(bào);2003年12期

8 鄭宏亮;王建英;;一種基于Mahalanobis距離的增量聚類算法[J];計(jì)算機(jī)應(yīng)用與軟件;2011年12期

9 李桃迎;陳燕;秦勝君;李楠;;增量聚類算法綜述[J];科學(xué)技術(shù)與工程;2010年35期

10 陳陽(yáng)梅;丁曉明;;一種基于K中心點(diǎn)算法的測(cè)試用例集約簡(jiǎn)方法[J];計(jì)算機(jī)科學(xué);2012年S1期

本文編號(hào)：1814558