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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 電機工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83131
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dc.contributor.advisor王凡zh_TW
dc.contributor.advisorFarn Wangen
dc.contributor.author許凱荃zh_TW
dc.contributor.authorKai-Quan XUen
dc.date.accessioned2023-01-09T06:30:55Z-
dc.date.available2023-11-09-
dc.date.copyright2023-01-06-
dc.date.issued2022-
dc.date.submitted2022-12-15-
dc.identifier.citation[1] S. Murugesan (2007), "Understanding Web 2.0," in IT Professional, vol. 9, no. 4, pp. 34-41, , doi: 10.1109/MITP.2007.78.
[2] O'reilly, T. (2009). What is web 2.0. " O'Reilly Media, Inc.".
[3] Andriole, S. J. (2010). Business impact of Web 2.0 technologies. Communications of the ACM, 53(12), 67-79.
[4] S. Delcev and D. Draskovic (2018), "Modern JavaScript frameworks: A Survey Study," 2018 Zooming Innovation in Consumer Technologies Conference (ZINC), pp. 106-109, doi: 10.1109/ZINC.2018.8448444.
[5] J. T. Howerton (2007), "Service-Oriented Architecture and Web 2.0," in IT Professional, vol. 9, no. 3, pp. 62-64, May-June 2007, doi: 10.1109/MITP.2007.54.
[6] F. Aloul, S. Zahidi and W. El-Hajj (2009), "Two factor authentication using mobile phones," 2009 IEEE/ACS International Conference on Computer Systems and Applications, pp. 641-644, doi: 10.1109/AICCSA.2009.5069395.
[7] K. Sawant, R. Tiwari, S. Vyas, P. Sharma, A. Anand and S. Soni (2021), "Implementation of Selenium Automation & Report Generation Using Selenium Web Driver & ATF," 2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp. 1-6, doi: 10.1109/ICAECT49130.2021.9392455.
[8] Herbold, S., & Hoffmann, A. (2017). Model-based testing as a service. International Journal on Software Tools for Technology Transfer, 19 (3), 271-279.
[9] Vaandrager, F. (2017). Model learning. Communications of the ACM, 60(2), 86–95.
[10] Raggett, D., Le Hors, A., & Jacobs, I. (1999). HTML 4.01 Specification. W3C recommendation, 24.
[11] Chowdhary, K. R. (2020). Natural Language Processing. In K. R. Chowdhary (Ed.), Fundamentals of Artificial Intelligence (pp. 603–649). Springer India.
[12] Eisenstein, J. (2019). Introduction to Natural Language Processing. MIT Press.
[13] Automata, Languages, and Machines. (1974). Academic Press.
[14] Salomaa, A. (2014). Theory of Automata. Elsevier.
[15] Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
[16] Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2021). Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. arXiv preprint arXiv:2107.13586.
[17] O'Shea, K., & Nash, R. (2015). An introduction to convolutional neural networks. arXiv preprint arXiv:1511.08458.
[18] Albawi, S., Mohammed, T. A., & Al-Zawi, S. (2017). Understanding of a convolutional neural network. In 2017 international conference on engineering and technology (ICET) (pp. 1-6). IEEE.
[19] Lin, J. W., Wang, F., & Chu, P. (2017). Using semantic similarity in crawling-based web application testing. In 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST) (pp. 138-148). IEEE.
[20] Schmidt, R. M. (2019). Recurrent neural networks (rnns): A gentle introduction and overview. arXiv preprint arXiv:1912.05911.
[21] Schuster, M., & Paliwal, K. K. (1997). Bidirectional recurrent neural networks. IEEE transactions on Signal Processing, 45(11), 2673-2681.
[22] Jain, A. K., Mao, J., & Mohiuddin, K. M. (1996). Artificial neural networks: A tutorial. Computer, 29(3), 31-44.
[23] Sablotny, M., Jensen, B. S., & Johnson, C. W. (2018). Recurrent neural networks for fuzz testing web browsers. In International Conference on Information Security and Cryptology (pp. 354-370). Springer, Cham.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83131-
dc.description.abstract登入,是一個需要向應用程式輸入自己的身分證明並提交給系統的流程。系統會記錄此行為並提供相應的服務和操作權限。在現今的網頁應用程式中,擁有登入與註冊模組的身分驗證系統已經非常常見。而在應用程式開發的過程中,進行測試是一個必要的環節。現今的測試方式主要分為兩種:人工手動測試、撰寫腳本進行測試。兩種都會需要花大量的人力資源來完成。在本論文中,我們提出了一個叫 AAPA的自動化的方法來通過登入與註冊的流程。透過自動建構的 Automata,AAPA能夠實時的分析當前遇到的頁面來選擇最有可能完成流程的行動,不再只是一連串的固定觸發流程。並且,我們整合了讀取電子郵件和簡訊的認證碼之流程,以擴大自動化的涵蓋範圍。最後,我們進行了實驗來評估我們方法的有效性,實驗證明了這樣的方式能夠讓流程更為彈性。zh_TW
dc.description.abstractLogging in is a process that requires you to submit your identity to the system. The system records this action and provides the corresponding service and operation privileges. In today's web applications, identity verification systems with login and registration modules are very common. In the process of application development, testing is necessary. Nowadays, there are two mainstream testing methods: manual testing and scripting. Both of them require a lot of human resources to complete. In this paper, we propose an automated method named AAPA to go through the login and registration process. With the automatically constructed Automata, AAPA can analyze the current page encountered in real time to select the most likely action to complete the process, instead of just a series of fixed triggers. Moreover, we integrate the process of reading the verification code and URL of e-mail and SMS to expand the scope of automation. Finally, we conduct experiments in order to evaluate the effectiveness of our approach. This approach proved to make the process more robust.en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-01-09T06:30:55Z
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dc.description.provenanceMade available in DSpace on 2023-01-09T06:30:55Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontents口試委員會審定書 #
誌謝 i
中文摘要 ii
ABSTRACT iii
CONTENTS iv
LIST OF FIGURES vi
LIST OF TABLES viii
Chapter 1 Introduction 1
1.1 Background ………………………………………………...1
1.2 Motivation 3
1.3 Contribution 3
1.4 Organization 4
Chapter 2 Related Work 6
2.1 Academic Research 6
2.2 Industrial Solutions 7
2.3 Test-Dragon Algorithm for Predicting Actions (Baseline) 9
Chapter 3 Preliminaries 11
3.1 Document Object Model ………………………………………….11
3.2 Natural Language Processing 12
3.3 Automata 13
Chapter 4 Methodology 17
4.1 Automatic Authentication Procedure Algorithm 17
4.2 How to Find the A-State which is Most Similar to the Current Page in Automata 18
4.3 How to Select an Action after Getting a Similar State 22
4.4 How to Make the Page Topic Better Differentiated 24
4.5 How to Recognize the Verification Code in the E-mail 25
Chapter 5 Implementations 27
5.1 Python and Related Library 27
5.2 Test-Dragon 27
5.3 Verification process 28
5.4 BERT Pre-trained Model 29
Chapter 6 Experiment 30
6.1 Dataset 30
6.2 Performance of Predicting Actions and States 30
6.3 Performance of Recognizing Verification Code/Link 33
6.4 Some Examples of Traces 34
Chapter 7 Conclusion and Future Work 37
Chapter 8 Reference 38
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dc.language.isoen-
dc.subject登入zh_TW
dc.subject自動化測試zh_TW
dc.subject網頁應用程式zh_TW
dc.subject簡訊驗證zh_TW
dc.subject信箱驗證zh_TW
dc.subject註冊zh_TW
dc.subjectE-mail Verificationen
dc.subjectWeb Applicationen
dc.subjectAutomated Testingen
dc.subjectLoginen
dc.subjectRegistrationen
dc.subjectSMS Verificationen
dc.title應用在網頁應用程式的身分驗證流程的自動化模型zh_TW
dc.titleAutomatic Modeling of Authentication Process for Web Application Testingen
dc.title.alternativeAutomatic Modeling of Authentication Process for Web Application Testing-
dc.typeThesis-
dc.date.schoolyear111-1-
dc.description.degree碩士-
dc.contributor.oralexamcommittee李允中;江介宏;顏嗣鈞;陳郁方;黃俊傑zh_TW
dc.contributor.oralexamcommitteeJONATHAN LEE;JIE-HONG JIANG;HSU-CHUN YEN;Yu-Fang Chen;RobertCC Huangen
dc.subject.keyword網頁應用程式,自動化測試,登入,註冊,簡訊驗證,信箱驗證,zh_TW
dc.subject.keywordWeb Application,Automated Testing,Login,Registration,SMS Verification,E-mail Verification,en
dc.relation.page40-
dc.identifier.doi10.6342/NTU202210136-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2022-12-16-
dc.contributor.author-college電機資訊學院-
dc.contributor.author-dept電機工程學系-
dc.date.embargo-lift2027-01-01-
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