ESEM 2022 Best Paper Award for Kolabri's Michael DornerNovember 9, 2022 by Maximilian Capraro
Congratulations to our very own Michael Dorner for winning the Best Paper Award at the prestigious 16th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement.
Michael received the award a study carried out with his colleagues at BTH Karlskrona quantifying how information can be distributed through large organizations using code review feedback. We are already looking forward to use the insights of Michael’s research to support our clients practicing even more purposeful workflows for software development collaboration and InnerSource.
Please find more details about the study and the research paper below.
Background: Modern code review is expected to facilitate knowledge sharing: All relevant information, the collective expertise, and meta-information around the code change and its context become evident, transparent, and explicit in the corresponding code review discussion. The discussion participants can leverage this information in the following code reviews; the information diffuses through the communication network that emerges from code review. Traditional time-aggregated graphs fall short in rendering information diffusion as those models ignore the temporal order of the information exchange: Information can only be passed on if it is available in the first place.
Aim: This manuscript presents a novel model based on time-varying hypergraphs for rendering information diffusion that overcomes the inherent limitations of traditional, time-aggregated graph-based models.
Method: In an in-silico experiment, we simulate an information diffusion within the internal code review at Microsoft and show the empirical impact of time on a key characteristic of information diffusion: the number of reachable participants.
Results: Time-aggregation significantly overestimates the paths of information diffusion available in communication networks and, thus, is neither precise nor accurate for modelling and measuring the spread of information within communication networks that emerge from code review.
Conclusion: Our model overcomes the inherent limitations of traditional, static or time-aggregated, graph-based communication models and sheds the first light on information diffusion through code review. We believe that our model can serve as a foundation for understanding, measuring, managing, and improving knowledge sharing in code review in particular and information diffusion in software engineering in general.
Michael Dorner, Darja Smite, Daniel Mendez, Krysztof Wnuk, Jacek Czerwonka (2022). Only Time Will Tell: Modeling Information Diffusion in Code Review with Time-Varying Hypergraphs. 16th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement.