ANALYSIS AND RECOMMENDATIONS FOR DEVELOPER LEARNING RESOURCES by

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.i agement throughout the journey that led to this thesis.My supervisor, Martin, has always been ready to review my work quickly and to provide insightful advice, even for the 100th revision of a paper when separated by multiple timezones, a sabbatical, and countless attention-seeking tasks.He never stopped at "good enough" and always raised the bar which led to research work that I am particularly proud of.Thank you Martin.It has been a great pleasure to work with my friend and mentor at IBM Research, Harold.I learned a lot from our research discussions, from his kindness too, and I thank him for his advice in the toughest moments.Conducting a qualitative study and interviewing real people on the phone for the first time can be scary if you are used to quantitative studies and totally afraid to pick up the phone in general.I thank Rachel for helping me improve my interviewing techniques and analysis skills, and for giving me confidence in the qualitative work I was doing.I am thankful to the contributors of open source projects, senior software engineers, and technical writers who accepted to squeeze an interview with me in their busy schedule.I never expected to be part of a family barbecue (over the phone), to speak with a groom a day after his wedding or to hear so many war stories from technical writers.What I learned from these interviews will be useful for the rest of my career.iii My colleagues, Annie, David, Ekwa, and Tristan, were always available to bounce ideas with me and review my papers

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