運用圖形分類在檢測網頁程式之分析系統

Abstract

網頁及手機的普及使得在開發上面自動化的測試變得越發重要，快速和廣泛的測試活動一直在程式開發的流程中存在著。然而如何確保有效的分析與測試仍然需要許多人力及時間的投入，這一點上一直是一件十分耗時費力的事情。 在執行自動化測試的時候，會將測試分為兩種，一種是完全放任他自由地、隨機地讓程式在頁面上執行各種動作；另一種則是，規劃固定的運行模式讓一切行為模組化。得到的結果，前者是盡可能地做壓力測試得知系統或服務的極限或缺失；後者則是，測試已知的功能看是否健全完整。然而，兩者都有各自需要設定目標、對象及行為。對人類來說，辨識和分類是極其簡單的事情，可是對測試的過程來說卻是一件耗時費力的事。 在本文中，提出了一個針對網頁及手機頁面的視覺化檢視及測試方法，透過圖形分類的方法在整合及收集頁面資訊的同時，自動地分類給測試腳本做使用，並且提升測試的有效程度，不再只是盲目的隨機測試，進而做到快速、有效且有意義的測試功能。由於，目前並沒有相對應完整的資料庫，我們會事先在網站上搜集好目標的資料，然後對此作分析及學習。最後，用分類的方式將畫面的元素自動標示相對應的標籤，以加速測試的進行。

Nowadays, increasing number of developers are using software testing technology to ensure the quality of their products in both web and mobile applications. It is a technique that providing random event traces and observing to see if the system or applications crash or not. At the moment, analyzing testing traces is still a heavy time-consuming and labor-intensive work. When processing software testing, we follow two testing protocols: one is to randomly execute actions on the page and the other is to set up modules of actions. For the result, the former one we can know that whether the service or system is able to overcome this kind of stress test and the later one is to test if our defined functions work well. However, both behaviors require setting targets and labeled them ahead. For human beings, it is such an easy job to classify or detect contents but for software testing, it is not. And this is the reason why we still require labor force for doing so. In this thesis, we present Smart-Eye, a visualized analysis service for both web pages and mobile applications. With the advantage of image classification, Smart-Eye helps software testers in organizing data and labeling them for the later testing scripts. Not only the analysis but the analysis improves the time consumption and accuracy. Because there is no complete dataset in this domain, we first gathered needed information and then built a classifying model from them. Last, we used it to do our intense work and made it an auto-labeling tool for later software testing in order to speed up the process of software testing in both aspects above.