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This thesis deals with the general issue of geographic information system GRASS distributed under the licence GNU GPL. It introduces the system itself and its possibilities as well as describes the terminology used in the Geography scientific sector. It also can be use as a simple handbook for teaching GIS.

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IUGONET研究集会第179回生存圏シンポジウム 『メタ情報のデータベースを利用した分野横断型地球科学研究の進展』

Version control systems are an asset to software development, enabling developers to keep snapshots of the code as they work. Stored in the version control system is the entire history of the software project, rich in information about who is contributing to the project, when contributions are made, and to what part of the project they are being made. Presented in the right way, this information can be made invaluable in helping software developers continue the development of the project, and maintainers to understand how the changes to the current version can be applied to older versions of projects. Maintainers are unable to effectively use the information stored within a software repository to assist with the maintanance older versions of that software in highly-collaborative projects. The Linux kernel repository is an example of such a project. This thesis focuses on improving visualizations of the Linux kernel repository, developing new visualizations that help answer questions about how commits are integrated into the project. Older versions of the kernel are used in a variety of systems where it is impractical to update to the current version of the kernel. Some of these applications include the controllers for spacecrafts, the core of mobile phones, the operating system driving internet routers, and as Internet-Of-Things (IOT) device firmware. As vulnerabilities are discovered in the kernel, they are patched in the current version. To ensure that older versions are also protected against the vulnerabilities, the patches applied to the current version of the kernel must be applied back to the older version. To do this, maintainers must be able to understand how the patch that fixed the vulnerability was integrated into the kernel so that they may apply it to the old version as well. This thesis makes four contributions: (1) a new tree-based model, the \mt{}, that abstracts the commits in the repository, (2) three visualizations that use this model, (3) a tool called \tool{} that uses these visualizations, (4) a user study that evaluates whether the tool is effective in helping users answer questions related to how commits are integrated about the Linux repository. The first contribution includes the new tree-based model, the algorithm that constructs the trees from the repository, and the evaluation of the results of the algorithm. the second contribution demonstrates some of the potential visualizations of the repository that are made possible by the model, and how these visualizations can be used depending on the structure of the tree. The third contribution is an application that applies the visualizations to the Linux kernel repository. The tool was able to help the participants of the study with understanding how commits were integrated into the Linux kernel repository. Additionally, the participants were able to summarize information about merges, including who made the most contributions, which file were altered the most, more quickly and accurately than with Gitk and the command line tools. / Graduate

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Context - In the fast-paced world of software development, understanding and tracking contributions within project teams is crucial for efficient project management and collaboration. Git, a popular Version Control System, facilitates collaboration but lacks comprehensive tools for analyzing individual contributions in detail. Objective - This thesis proposes an approach to classify and analyze Git commit messages and the associated file paths of the changed files in the commits, using Natural Language Processing (NLP) techniques, aiming to improve project transparency and contributor recognition. Method - By employing Bidirectional Encoder Representations from Transformers (BERT) models, an NLP technique, this study categorizes data from multiple collected Git repositories. A tool named DevAnalyzer is developed to automate the classification and analysis process, enhancing the understanding of contribution patterns. Results - The Git commit message model demonstrated high accuracy with an average of 98.9%, and the file path model showed robust performance with an average accuracy of 99.8%. Thereby, both models provided detailed insights into the types and locations of contributions within projects. Conclusions - The findings validate the effectiveness of using BERT models for classifying and categorizing both Git commit messages and file paths with the DevAnalyzer. This approach provides a more comprehensive understanding of contributions, benefiting project management and team collaboration.

DevOps is a cultural idea rather than a firm way to do software development, with the aim of reducing software lead times by bringing operations and development closer via principles that mainly deal with automation. This paper provides a potential DevOps solution for Wexnet, an internet service provider company. A requirements list is created by interviewing which is then used to evaluate existing web-based git solutions. Two viable candidates were selected, GitHub and GitLab which were compared against each other. GitLab was chosen because of its comparably low resource usage and lower overall setup complexity.