Back
Raglianti_2022_IEEE-ACM_ICPC
Conference paper (in proceedings)

Using Discord conversations as program comprehension aid

  • Raglianti, Marco ORCID REVEAL, Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Nagy, Csaba ORCID REVEAL, Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Minelli, Roberto ORCID REVEAL, Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Lanza, Michele ORCID REVEAL, Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
Show more…
  • 2022
Published in:
  • 2022 IEEE/ACM 30th International Conference on Program Comprehension (ICPC). - 2022, p. 597-601
Conversations
Discord
Visualization
English Modern communication platforms used in software development host daily conversations among developers and users about a wide range of topics pertaining to software systems, such as language features, APIs, code artifacts like classes and methods, design patterns, usage examples, code reviews, bug reporting and fixing. Discord servers are one of these virtual community hubs that have seen a steep rise in popularity, as coordination and aggregation means for communities of developers. Although Discord supports filter-based search functionalities, the sheer volume, velocity, and small granularity of single messages make it hard to find useful results, let alone complete discussions revolving around particular themes. One reason is that the concept of a discussion, which we call a conversation, does not exist as an explicit concept. We argue that extracting and analyzing such conversations can be used fruitfully to aid program comprehension. We present an approach that reconstructs the conversations that take place on a software community Discord server, focusing on software-related conversations: Our approach binds the conversations to the discussed artifacts. Leveraging our approach, we built a tool that enables the interactive exploration of the conversations’ contents. We illustrate its usefulness through a number of examples that highlight how the insights obtained serve as an additional form of software documentation and program comprehension aid.
Collections
Language
  • English
Classification
Computer science and technology
License
Rights reserved
Open access status
green
Identifiers
Persistent URL
https://n2t.net/ark:/12658/srd1325426
Statistics
Document views: 28 File downloads:
  • Raglianti_2022_IEEE-ACM_ICPC.pdf: 37