Developer targeted analytics: supporting software development decisions with runtime information

Abstract

Runtime information of deployed software has been used by business and operations units to make informed decisions under the term ``analytics". However, decisions made by software engineers in the course of evolving software have, for the most part, been based on personal belief and gut-feeling. This could be attributed to software development being, for the longest time, viewed as an activity that is detached from the notion of operating software in a production environment. In recent years, this view has been challenged with the emergence of the DevOps movement, which aim is to promote cross-functional capabilities of development and operations activities within teams. This shift in process and mindset requires analytics tools that specifically target software developers. In this research, I investigate approaches to support developers in their decision-making by incorporating runtime information in source code and provide live feedback in IDEs by predicting the impact of code changes.

BibTeX

@inproceedings{Cito:ASE16,
  author    = {J{\"{u}}rgen Cito},
  title     = {Developer targeted analytics: supporting software development decisions with runtime information},
  booktitle = {ASE},
  pages     = {892--895},
  publisher = {{ACM}},
  year      = {2016},
}

Developer targeted analytics: supporting software development decisions with runtime information

Abstract

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