API (application programming interface) documentation is critical for developers to learn APIs. However, it is unclear whether API documentation indeed improves the API learnability for developers. In this paper, we focus on two types of API documentation, i.e., official API tutorials and API crowd documentation. First, we analyze API coverage and check API consistencies in API documentation based on the API traceability. Then, we conduct a survey and extract several characteristics to analyze which API documentation can help developers learn APIs. Our findings show that: 1) API crowd documentation can be regarded as a supplement to the official API tutorials to some extent; 2) the concerns for frequently-used APIs between different types of API documentation show a huge mismatch, which may prevent developers from deeply understanding the usages of APIs through only one type of API documentation; 3) official API tutorials can help developers seek API information on a long page and API crowd documentation could provide long codes for a particular programming task. These findings may help developers select the suitable API documentation and find the useful information they need.

In common design pattern collections, e.g., design pattern books, design patterns are documented with templates that consist of multiple attributes, such as intent, structure, and sample code. To adapt to modern developers, the depictions of design patterns, especially some specific attributes, should advance with the current programming technologies, for example, “known uses”, which exemplifies the use scenarios of design patterns in practice, and “related patterns”, which describes the relatedness between a design pattern and the others within a context. However, it is not easy to update the contents of these attributes manually due to the diversity of the programming technologies. To address this problem, in this work, we conducted a case study to mine design pattern use scenarios and related design pattern pairs from Stack Overflow posts to enrich the two attributes. We first extracted the question posts relevant to each design pattern by identifying the design pattern tags. Then, the topics of the posts were discovered by applying topic modeling techniques. Finally, by analyzing the topics specified for each design pattern, we detected 195 design pattern use scenarios and 70 related design pattern pairs, involving 61 design patterns totally. These findings are associated with a variety of popular software frameworks and programming techniques. They could complement the existing design pattern collections and help developers better acknowledge the usage and relatedness of design patterns in today’s programming practice.