StackOverflow (SO) is a widely used question-and-answer (QandA) website for software developers and computer scientists. GitHub is a code hosting platform for collaboration and version control. Popular software libraries are open-source and published in repositories on GitHub. Preliminary observation shows developers cite SO questions in their GitHub repository. This observation inspired us to explore the relationship between SO posts and GitHub repositories; to help software developers better understand the characterization of SO answers that are reused by GitHub projects. For this study, we conducted an empirical study to investigate the SO answers reused by Java code from public GitHub projects. We used a hybrid approach to ensure precise results: code clone detection, keyword-based search, and manual inspection. This approach helped us identify the leveraged answers from developers. Based on the identified answers, we further investigated the topics of the discussion threads; answer characteristics (e.g., scores, ages, code lengths, and text lengths) and developers' reuse practices. We observed both reused and unused answers. Compared with unused answers, We found that the reused answers mostly have higher scores, longer code, and longer plain text explanations. Most reused answers were related to implementing specific coding tasks. In one of our observations, 9% (40/430) of scenarios, developers entirely copied code from one or multiple answers of an SO discussion thread. Furthermore, we observed that in the other 91% (390/430) of scenarios, developers only partially reused code or created brand new code from scratch. We investigated 130 SO discussion threads referred to by Java developers in 356 GitHub projects. We then arranged those into five different categories. Our findings can help the SO community have a better distribution of programming knowledge and skills, as well as inspire future research related to SO and GitHub. / Master of Science / StackOverflow (SO) is a widely used question-and-answer (QandA) website for software developers and computer scientists. GitHub is a code hosting platform for collaboration and version control. Popular software libraries are open-source and published in repositories on GitHub. Preliminary observation shows developers cite SO questions in their GitHub repository. This observation inspired us to explore the relationship between SO posts and GitHub repositories; to help software developers better understand the characterization of SO answers that are reused by GitHub projects. Our objectives are to guide SO answerers to help developers better; help tool builders understand how SO answers shape software products. Thus, we conducted an empirical study to investigate the SO answers reused by Java code from public GitHub projects. We used a hybrid approach to refine our dataset and to ensure precise results. Our hybrid approach includes three steps. The first step is code clone detection. We compared two code snippets with a code clone detection tool to find the similarity. The second step is a keyword-based search. We created multiple keywords to search within GitHub code to find the referenced answers missed by step one. Lastly, we manually inspected the outputs of both step one and two to ensure zero false positives in our data. This approach helped us identify the leveraged answers from developers. Based on the identified answers, we further investigated the topics of the discussion threads, answer characteristics, and developers' reuse practices. We observed both reused and unused answers. Compared with unused answers, We found that the reused answers mostly have higher scores, longer code, and longer plain text explanations. Most reused answers were related to implementing specific coding tasks. In one of our observations, 9% of scenarios, developers entirely copied code from one or multiple answers of an SO discussion thread. Furthermore, we observed that in the other 91% of scenarios, developers only partially reused code or created brand new code from scratch. Our findings can help the SO community have a better distribution of programming knowledge and skills, as well as inspire future research related to SO and GitHub.

This project is the design and implementation of a web-based message board for software developers. The purpose of “Social Network for Software Developers” is to connect inexperienced software developers with experienced software developers.

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abstract: Online discussion forums have become an integral part of education and are large repositories of valuable information. They facilitate exploratory learning by allowing users to review and respond to the work of others and approach learning in diverse ways. This research investigates the different comment semantic features and the effect they have on the quality of a post in a large-scale discussion forum. We survey the relevant literature and employ the key content quality identification features. We then construct comment semantics features and build several regression models to explore the value of comment semantics dynamics. The results reconfirm the usefulness of several essential quality predictors, including time, reputation, length, and editorship. We also found that comment semantics are valuable to shape the answer quality. Specifically, the diversity of comments significantly contributes to the answer quality. In addition, when searching for good quality answers, it is important to look for global semantics dynamics (diversity), rather than observe local differences (disputable content). Finally, the presence of comments shepherd the community to revise the posts by attracting attentions to the posts and eventually facilitate the editing process. / Dissertation/Thesis / Masters Thesis Computer Science 2016

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-11-01T21:17:48Z No. of bitstreams: 1 TeresaDoCarmoBarretoFernandes_DISSERT.pdf: 5261298 bytes, checksum: 1a7e32ec8483e6e7e31101df7f8675f9 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-11-07T21:08:03Z (GMT) No. of bitstreams: 1 TeresaDoCarmoBarretoFernandes_DISSERT.pdf: 5261298 bytes, checksum: 1a7e32ec8483e6e7e31101df7f8675f9 (MD5) / Made available in DSpace on 2017-11-07T21:08:03Z (GMT). No. of bitstreams: 1 TeresaDoCarmoBarretoFernandes_DISSERT.pdf: 5261298 bytes, checksum: 1a7e32ec8483e6e7e31101df7f8675f9 (MD5) Previous issue date: 2017-06-30 / Exce??es n?o capturadas (do ingl?s: uncaught) n?o s?o cen?rios excepcionais nas aplica??es Java atuais. Eles s?o, na verdade, uma das principais causas de falha das aplica??es Java - que podem originar-se de erros de programa??o (e.g., acesso a refer?ncias nulas); falhas no hardware ou em APIs utilizadas. Essas exce??es uncaught resultam em stack traces que s?o frequentemente usados pelos desenvolvedores como fonte de informa??es para a depura??o. Atualmente, essa informa??o ? frequentemente usada pelos desenvolvedores em mecanismos de busca ou sites de perguntas e respostas (do ingl?s: Question and Answer - Q&A) para tentar compreender melhor a causa do crash e assim poder resolv?lo. Este estudo fez a minera??o de stack traces inclu?das nas perguntas e respostas do StackOverflow (SOF). O objetivo deste estudo foi: (i) identificar caracter?sticas das stack traces mineradas do SOF e (ii) investigar como tais informa??es podem ser usadas para evitar exce??es uncaught durante o desenvolvimento de software. Neste estudo, 121.253 stack traces foram extra?das e analisadas em combina??o com inspe??es de postagens do SOF. Tamb?m ? proposta a ferramenta ExMinerSOF, que alerta o desenvolvedor sobre as exce??es que podem ser potencialmente sinalizadas por um m?todo de API. Essas informa??es s?o descobertas aplicando uma estrat?gia de minera??o apresentada neste trabalho. Ao faz?-lo, a ferramenta permite que o desenvolvedor evite falhas com base em falhas relatadas por outros desenvolvedores. / Uncaught exceptions are not an exceptional sce- nario in current Java applications. They are actually one of the main causes of applications crashes, which can originate from programming errors on the application itself (null pointer dereferences); faults in underlying hardware or re-used APIs. Such uncaught exceptions result in exception stack traces that are often used by developers as a source of information for debugging. Currently, this information is ofttimes used by developers on search engines or Question and Answer sites while the developer tries to: better understand the cause of the crash and solve it. This study mined the exception stack traces embedded on StackOverflow (SOF) questions and answers. The goal of this work was to two-fold: to identify characteristics of stack traces mined from SOF and to investigate how such information can be used to prevent uncaught exceptions during software development. Overall 121.253 exception stack traces were extracted and analyzed in combination with Q&A inspections. Hence, this study proposes ExMinerSOF tool, which alerts the developer about the exceptions that can be potentially signaled by an API method but are not part of the API documentation - and was discovered by applying a mining strategy in SOF repository. Doing so, the tool enable the developer to prevent faults based on failures reported by the crowd.