Three of the most widely studied software dependency types are the structural, logical and semantic dependencies. Logical dependencies capture the degree of co-change between software artifacts. Semantic dependencies capture the degree to which artifacts, comments and names are related. Structural dependencies capture the dependencies in the source code of artifacts. Prior studies show that a combination of dependency analysis (e.g., semantic and logical analysis) improves accuracy when predicting which artifacts are likely to be impacted by ripple effects of software changes (though not to a large extent) compared to individual approaches. In addition, some dependencies could be hidden dependencies when an analysis of one dependency type (e.g., logical) does not reveal artifacts only linked by another dependency type (semantic). While previous studies have focused on combining dependency information with minimal benefits, this Thesis explores the consistency of these measurements, and whether hidden dependencies arise between artifacts, and in any of the axes studied. In this Thesis, 79 Java projects are empirically studied to investigate (i) the direct influence and the degree of overlap between dependency types on three axes (logical - structural (LSt); logical - semantic (LSe); structural - semantic (StSe)) (structural, logical and semantic), and (ii) the presence of hidden coupling on the axes. The results show that a high proportion of hidden dependencies can be detected on the LSt and StSe axes. Notwithstanding, the LSe axis shows a much smaller proportion of hidden dependencies. Practicable refactoring methods to mitigate hidden dependencies are proposed in the Thesis and discussed with examples.

Este trabalho de tese apresenta o Modelo Presença Plus (PPlus) para identificação de pistas textuais denotadoras de presença social em interações discursivas feitas por alunos em fóruns e chats educacionais. O grau de presença social (PS) é um indicativo de como os sujeitos interagem entre si e com o ambiente de aprendizagem; sendo considerado, na literatura, significativo para o desenvolvimento de relacionamentos e fortalecimento de sentimento de pertencimento no grupo. O trabalho se baseia na vertente Pragmática da Linguística, campo que enfatiza a importância de se considerar o contexto de produção dos eventos comunicativos e a dinâmica dialógica entre os interlocutores. Considerando que o mapeamento das interações dos discentes para detectar e avaliar seu grau de presença pode se constituir uma tarefa complexa e morosa para tutores de cursos a distância, desenvolveu-se um software para realizar o processamento automático das mensagens eletrônicas visando torná-lo uma funcionalidade a ser adicionada a ambientes virtuais de ensino e aprendizagem (AVEAs). Apesar de alguns impasses referentes, particularmente, aos aspectos sintáticos dos textos, os resultados obtidos no processamento, por lexicometria, das postagens foram satisfatoriamente semelhantes aos levantados na análise manual. O modelo PPlus e a escala de graus de PS foram também testados em um segundo ambiente disponibilizado na plataforma Moodle, tendo apresentado resultados equivalentes. A sondagem com professores e tutores de cursos a distância forneceu dados que corroboram a proposta de uma ferramenta a ser inserida em AVEAs de modo a facilitar o acompanhamento de estados afetivos, grau de envolvimento e interação entre os participantes no e com o ambiente. / This thesis presents Presence Plus (PPLus), a model for identifying indicators of social presence in text-based interactions made by students in educational forums and chats. The degree of social presence (SP) can be an indicator of how individuals interact among themselves and with the learning environment, and is considered by the literature to be relevant for the development of relationships and the strengthening of the sense of belonging in the group. This study is based on Pragmatics, an area of Linguistics that emphasizes the importance of the context in communicative events and the dialogic dynamics among speakers. Considering that mapping students’ interactions, as well as detecting and evaluating their degree of SP, may be a complex and time-consuming task in distance learning tutoring, a software was developed to do the automatic processing of posts, aiming at making it a possible functionality in virtual learning environments (VLEs). Despite the few conflicting results, mostly related to textual syntactic relations, data from processing tests using lexicometrics were satisfactorily similar to those obtained by manual analysis. The PPlus model and the SP scale were also tested in a different course in the Moodle platform. Results from this experiment presented equally positive data. Feedback from the questionnaire answered by teachers and tutors working in distance learning courses support the proposal of a tool that may facilitate their assessment of affective states, involvement and text-based interaction dents within the environment.

Este trabalho de tese apresenta o Modelo Presença Plus (PPlus) para identificação de pistas textuais denotadoras de presença social em interações discursivas feitas por alunos em fóruns e chats educacionais. O grau de presença social (PS) é um indicativo de como os sujeitos interagem entre si e com o ambiente de aprendizagem; sendo considerado, na literatura, significativo para o desenvolvimento de relacionamentos e fortalecimento de sentimento de pertencimento no grupo. O trabalho se baseia na vertente Pragmática da Linguística, campo que enfatiza a importância de se considerar o contexto de produção dos eventos comunicativos e a dinâmica dialógica entre os interlocutores. Considerando que o mapeamento das interações dos discentes para detectar e avaliar seu grau de presença pode se constituir uma tarefa complexa e morosa para tutores de cursos a distância, desenvolveu-se um software para realizar o processamento automático das mensagens eletrônicas visando torná-lo uma funcionalidade a ser adicionada a ambientes virtuais de ensino e aprendizagem (AVEAs). Apesar de alguns impasses referentes, particularmente, aos aspectos sintáticos dos textos, os resultados obtidos no processamento, por lexicometria, das postagens foram satisfatoriamente semelhantes aos levantados na análise manual. O modelo PPlus e a escala de graus de PS foram também testados em um segundo ambiente disponibilizado na plataforma Moodle, tendo apresentado resultados equivalentes. A sondagem com professores e tutores de cursos a distância forneceu dados que corroboram a proposta de uma ferramenta a ser inserida em AVEAs de modo a facilitar o acompanhamento de estados afetivos, grau de envolvimento e interação entre os participantes no e com o ambiente. / This thesis presents Presence Plus (PPLus), a model for identifying indicators of social presence in text-based interactions made by students in educational forums and chats. The degree of social presence (SP) can be an indicator of how individuals interact among themselves and with the learning environment, and is considered by the literature to be relevant for the development of relationships and the strengthening of the sense of belonging in the group. This study is based on Pragmatics, an area of Linguistics that emphasizes the importance of the context in communicative events and the dialogic dynamics among speakers. Considering that mapping students’ interactions, as well as detecting and evaluating their degree of SP, may be a complex and time-consuming task in distance learning tutoring, a software was developed to do the automatic processing of posts, aiming at making it a possible functionality in virtual learning environments (VLEs). Despite the few conflicting results, mostly related to textual syntactic relations, data from processing tests using lexicometrics were satisfactorily similar to those obtained by manual analysis. The PPlus model and the SP scale were also tested in a different course in the Moodle platform. Results from this experiment presented equally positive data. Feedback from the questionnaire answered by teachers and tutors working in distance learning courses support the proposal of a tool that may facilitate their assessment of affective states, involvement and text-based interaction dents within the environment.

Este trabalho de tese apresenta o Modelo Presença Plus (PPlus) para identificação de pistas textuais denotadoras de presença social em interações discursivas feitas por alunos em fóruns e chats educacionais. O grau de presença social (PS) é um indicativo de como os sujeitos interagem entre si e com o ambiente de aprendizagem; sendo considerado, na literatura, significativo para o desenvolvimento de relacionamentos e fortalecimento de sentimento de pertencimento no grupo. O trabalho se baseia na vertente Pragmática da Linguística, campo que enfatiza a importância de se considerar o contexto de produção dos eventos comunicativos e a dinâmica dialógica entre os interlocutores. Considerando que o mapeamento das interações dos discentes para detectar e avaliar seu grau de presença pode se constituir uma tarefa complexa e morosa para tutores de cursos a distância, desenvolveu-se um software para realizar o processamento automático das mensagens eletrônicas visando torná-lo uma funcionalidade a ser adicionada a ambientes virtuais de ensino e aprendizagem (AVEAs). Apesar de alguns impasses referentes, particularmente, aos aspectos sintáticos dos textos, os resultados obtidos no processamento, por lexicometria, das postagens foram satisfatoriamente semelhantes aos levantados na análise manual. O modelo PPlus e a escala de graus de PS foram também testados em um segundo ambiente disponibilizado na plataforma Moodle, tendo apresentado resultados equivalentes. A sondagem com professores e tutores de cursos a distância forneceu dados que corroboram a proposta de uma ferramenta a ser inserida em AVEAs de modo a facilitar o acompanhamento de estados afetivos, grau de envolvimento e interação entre os participantes no e com o ambiente. / This thesis presents Presence Plus (PPLus), a model for identifying indicators of social presence in text-based interactions made by students in educational forums and chats. The degree of social presence (SP) can be an indicator of how individuals interact among themselves and with the learning environment, and is considered by the literature to be relevant for the development of relationships and the strengthening of the sense of belonging in the group. This study is based on Pragmatics, an area of Linguistics that emphasizes the importance of the context in communicative events and the dialogic dynamics among speakers. Considering that mapping students’ interactions, as well as detecting and evaluating their degree of SP, may be a complex and time-consuming task in distance learning tutoring, a software was developed to do the automatic processing of posts, aiming at making it a possible functionality in virtual learning environments (VLEs). Despite the few conflicting results, mostly related to textual syntactic relations, data from processing tests using lexicometrics were satisfactorily similar to those obtained by manual analysis. The PPlus model and the SP scale were also tested in a different course in the Moodle platform. Results from this experiment presented equally positive data. Feedback from the questionnaire answered by teachers and tutors working in distance learning courses support the proposal of a tool that may facilitate their assessment of affective states, involvement and text-based interaction dents within the environment.

Various vulnerabilities in software products can often represent a significant security threat if they are discovered by malicious attackers. It is therefore important to identify these vulnerabilities and report their presence to responsible persons before they are exploited by malicious subjects. The number of security reports about discovered vulnerabilities in various software products has grown rapidly over the last decade. It is becoming more and more difficult to process all of the incoming reports manually. This work discusses various methods that can be used to automate several important processes in collecting and sorting the reports. The reports are analyzed in various ways, including techniques of text mining, and the results of the analysis are applied in form of practical implementation.