Conference paper (in proceedings)

Topology of the documentation landscape

  • Raglianti, Marco ORCID REVEAL, Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • 2021
Published in:
  • Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings (ICSE '22). - 2021, p. 297–299
English Every software system (ideally) comes with one or more forms of documentation. Beside source code comments, other structured and unstructured sources (e.g., design documents, API references, wikis, usage examples, tutorials) constitute critical assets.Cloud-based repositories for collaborative development (e.g., GitHub, Bitbucket, GitLab) provide many functionalities to create, persist, and version documentation artifacts. On the other hand, the last decade has seen the rise of rich instant messaging clients used as global software community platforms (e.g., Slack, Discord). Although completely detached from a specific versioning system or development workflow, they allow developers to discuss implementation issues, report bugs, and, in general, interact with one another. We refer to this evolving heterogeneous collection of information sources and documentation artifacts as the documentation landscape. It is important to have tools to extract information from these sources and integrate them in a topological visualization, to ease comprehension of a software system. How can we automatically generate this topology? How can we link elements in the topology back to the source code they refer to? The goal of this PhD research is to automatically mine the documentation landscape of a system by disclosing pieces of information to aid, for example, in program maintenance tasks. We present our classification of possible documentation sources. The long term vision is to provide a domain model of the documentation landscape to build, visualize, and explore its instances for real software systems and evaluate the usefulness of the metaphor we propose.
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  • English
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Computer science and technology
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https://n2t.net/ark:/12658/srd1325424
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