Analysis and Recommendations for Developer Learning Resources

Developer documentation helps developers learn frameworks and libraries, yet developing and maintaining accurate documentation require considerable effort and resources. Contributors who work on developer documentation need to at least take into account the project’s code and the support needs of users. Although related, the documentation, the code, and the support needs evolve and are not always synchronized: for example, new features in the code are not always documented and questions repeatedly asked by users on support channels such as mailing lists may not be addressed by the documentation. Our thesis is that by studying how the relationships between documentation, code, and users’ support needs are created and maintained, we can identify documentation improvements and automatically recommend some of these improvements to contributors. In this dissertation, we (1) studied the perspective of documentation contributors by interviewing open source contributors and users, (2) developed a technique that automatically generates the model of documentation, code, and users’ support needs, (3) devised a technique that recovers fine-grained traceability links between the learning resources and the code, (4) investigated strategies to infer high-level documentation structures based on the traceability links, and (5) devised a recommendation system that uses the traceability links and the high-level documentation structures to suggest adaptive changes to the documentation when the underlying code evolves.