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--- 2023-24:fall [2023/08/31 16:50] – ruppert
+++ 2023-24:fall [2023/11/30 20:58] (current) – ruppert
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 **Required skills or prerequisites:**
-Good programming and data analysis skills overall, and experience in using Jupyter and/or R for data analysis.  Ability to work indecently.
+Good programming and data analysis skills overall, and experience in using Jupyter and/or R for data analysis.  Ability to work independently.
 Interest in usable privacy, critical analysis of privacy policies and privacy related regulation.
@@ Line 207: / Line 207: @@
 Experience with web-development frameworks (e.g., React JS, Spring Boot) and good oral and written skills in English
+==== Large Language Models based Test Case Generation ====
+**Course:**  EECS4080
+**Supervisor:**  Song Wang
+**Supervisor's email address:** wangsong@yorku.ca
+**Project Description:**
+Recently, pre-trained large language models (LLMs) have emerged as a breakthrough technology in natural language processing and artificial intelligence, with the ability to handle large-scale datasets and exhibit remarkable performance across a wide range of tasks. Meanwhile, software testing is a crucial undertaking that serves as a cornerstone for ensuring the quality and reliability of software products. As the scope and complexity of software systems continue to grow, the need for more effective software testing techniques becomes increasingly urgent and making it an area ripe for innovative approaches such as the use of LLMs. Our recent collaboration with Meta also confirms the limitations of existing widely used testing techniques in test input generations, test oracle generation, and test scenario generation. This project takes a solid initial step towards exploring the next-generation software testing techniques powered by LLMs.
+**Required skills or prerequisites:**
+Be familiar with DL libraries such as Tensorflow and Pytorch;
+**Instructions:**
+Send your c.v. and transcript to supervisor