Creating websites today is not easy as it seems, therefore it is important to know the essential principle when developing new product for users. Knowing the essential principles is not enough, you will also need to know about what users think and feel is important on a website such as Stack Overflow. It is a question-and-answer website where it offers users the ability to post questions and receive answers from other users that uses the same website. This study will identify what is important for young adult developers on the website Stack Overflow and what they think, and feel is required in terms of usability on the website. In this study there will be a theoretical framework and it includes different aspects of usability: learnability, comprehensibility, navigation, flexibility, and discoverability. This theoretical framework has been created to be able to identify what is important for young adult developers on the website Stack Overflow. By using this theoretical framework, we can setup the data collection method which is interview and think-aloud-test. As for analysis of the data, content analysis has been used to analyze the results and the study reached its conclusion. The conclusion is that on a website like Stack Overflow, navigation, flexibility, and comprehensibility are the important aspects for young adult developers.

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Researchers use datasets of Question-Solution pairs to train machine learning models, such as source code generation models. A Question-Solution pair contains two parts: a programming question and its corresponding Solution Snippet. A Solution Snippet is a source code that solves a programming question. These datasets of Question-Solution pairs can be extracted from a number of different platforms. In this research, I study how Question-Solution pairs are extracted from Stack Overflow (SO). There are two limitations of datasets of Question-Solution pairs extracted from SO: (1) according to the authors of these datasets, some Question-Solution pairs contain Solution Snippets that do not solve the question correctly, and (2) these datasets do not contain the information on how Solution Snippets need to be reused, and such information would enhance the reusability of Solution Snippets. These limitations of datasets of pairs could adversely affect the quality of the code being generated by machine learning models. In this research, I conducted a qualitative study to categorize various presentations of Solution Snippets in SO’s answers as well as how Solution Snippets can be adapted for reuse. By doing so, I identified eight categories of how Solution Snippets are presented in SO’s answers and five categories of how Solution Snippets could be adapted. Based on these results, I concluded several potential reasons why it is not easy to create datasets of Question-Solution pairs. The first categorization informs that finding the correct location of the Solution Snippet is challenging when there are several code blocks within the answer to the question. Subsequently, the researcher must identify which code within that code block is the Solution Snippet. The second categorization informs that most Solution Snippets appear challenging to be adapted for reuse, and how Solution Snippets are potentially adapted is not explicitly stated in them. These insights shed light on creating better quality datasets from questions and answers posted on Stack Overflow. / Graduate