Stack Overflow is the most popular CQA for programmers on the web with 2.05M users, 5.1M questions and 9.4M answers. Stack Overflow has explicit, detailed guidelines on how to post questions and an ebullient moderation community. Despite these precise communications and safeguards, questions posted on Stack Overflow can be extremely off topic or very poor in quality. Such questions can be deleted from Stack Overflow at the discretion of experienced community members and moderators. We present the first study of deleted questions on Stack Overflow. We divide our study into two parts (i) Characterization of deleted questions over approx. 5 years (2008-2013) of data, (ii) Prediction of deletion at the time of question creation. Our characterization study reveals multiple insights on question deletion phenomena. We observe a significant increase in the number of deleted questions over time. We find that it takes substantial time to vote a question to be deleted but once voted, the community takes swift action. We also see that question authors delete their questions to salvage reputation points. We notice some instances of accidental deletion of good quality questions but such questions are voted back to be undeleted quickly. We discover a pyramidal structure of question quality on Stack Overflow and find that deleted questions lie at the bottom (lowest quality) of the pyramid. We also build a predictive model to detect the deletion of question at the creation time. We experiment with 47 features based on User Profile, Community Generated, Question Content and Syntactic style and report an accuracy of 66 . Our feature analysis reveals that all four categories of features are important for the prediction task. Our findings reveal important suggestions for content quality maintenance on community based question answering websites.
 Software frameworks provide sets of generic functionalities that can be later customized for a specific task. When developers invoke API methods in a framework, they often encounter obstacles in finding the correct usage of the API, let alone to employ best practices. Previous research addresses this line of questions by mining API usage patterns to induce API usage templates, by conducting and compiling interviews of developers, and by inferring correlations among APIs. In this paper, we analyze API-related posts regarding iOS and Android development from a Q&A Web site, stackoverflow.com. Assuming that API-related posts are primarily about API usage obstacles, we find several iOS and Android API classes that appear to be particularly likely to challenge developers, even after we factor out API usage hotspots, inferred by modelling API usage of open source iOS and Android applications. For each API with usage obstacles, we further apply a topic mining tool to posts that are tagged with the API, and we discover several repetitive scenarios in which API usage obstacles occur. We consider our work as a stepping stone towards understanding API usage challenges based on forum-based input from a multitude of developers, input that is prohibitively expensive to collect through interviews. Our method helps to motivate future research in API usage, and can allow designers of platforms - such as iOS and Android - to better understand the problems developers have in using their platforms, and to make corresponding improvements. Programmers learning how to use an API or a programming language often rely on code examples to support their learning activities. However, what makes for an effective ode example remains an open question. Finding the haracteristics of the effective examples is essential in improving the appropriateness of these learning aids. To help answer this question we have onducted a qualitative analysis of the questions and answers posted to a programming Q&A web site called StackOverflow. On StackOverflow answers can be voted on, indicating which answers were found helpful by users of the site. By analyzing these well-received answers we identified haracteristics of effective examples. We found that the explanations acompanying examples are as important as the examples themselves. Our findings have implications for the way the API documentation and example set should be developed and evolved as well as the design of the tools assisting the development of these materials. Community-based question answering services accumulate large volumes of knowledge through the voluntary services of people across the globe. Stack Overflow is an example of such a service that targets developers and software engineers. In general, questions in Stack Overflow are answered in a very short time. However, we found that the number of unanswered questions has increased significantly in the past two years. Understanding why questions remain unanswered can help information seekers improve the quality of their questions, increase their chances of getting answers, and better decide when to use Stack Overflow services. In this paper, we mine data on unanswered questions from Stack Overflow. We then conduct a qualitative study to categorize unanswered questions, which reveals characteristics that would be difficult to find otherwise. Finally, we conduct an experiment to determine whether we can predict how long a question will remain unanswered in Stack Overflow.