Natural language elements (e.g., API comments, todo comments) form a substantial part of software repositories. While developers routinely use many natural language elements (e.g., todo comments) for communication, the semantic content of these elements is often neglected by software engineering techniques and tools. Additionally, as software evolves and development teams re-organize, these natural language elements are frequently forgotten, or just become outdated, imprecise and irrelevant. We envision several techniques, which combine natural language processing and program analysis, to help developers maintain their todo comments. Specifically, we propose techniques to synthesize code from comments, make comments executable, answer questions in comments, improve comment quality, and detect dangling comments.

It is a massive trial-and-error process. From time to time, you will hear about a new fantastic piece of computer science. For example, right now deep learning is the hot new thing. Some years ago, people were very excited about MapReduce. As an ecosystem changes, some tools become less likely to be useful while others gain dominance in common use cases.

It is a massive trial-and-error process. From time to time, you will hear about a new fantastic piece of computer science. For example, right now deep learning is the hot new thing. Some years ago, people were very excited about MapReduce. As an ecosystem changes, some tools become less likely to be useful while others gain dominance in common use cases.