(Abstract and video links below)
ACM SIGSOFT Webinar May 4th, 2016
Distinguished lecture at ISR, UCI, April 2016.
UCI Video is available at: https://www.youtube.com/watch?v=Ujm4G7ayRQQ
Webinar link will be available shortly.
This talk is based on a short chapter to appear in a forthcoming book on "Perspectives on Data Science for Software Engineering", it can be preordered here:
Software analytics and the use of computational methods on "big" data in software engineering is transforming the ways software is developed, used, improved and deployed. Software engineering researchers and practitioners are witnessing an increasing trend in the availability of diverse trace and operational data and the methods to analyze it. This information is being used to paint a picture of how software is engineered and suggest ways it may be improved. But we have to remember that software engineering is inherently a socio-technical endeavour, with complex practices, activities and cultural aspects that cannot be externalized or captured by tools alone---in fact, they may be perturbed when trace data is surfaced and analyzed in a transparent manner.
In this talk, I will ask:
- Are researchers and practitioners adequately considering the unanticipated impacts that software analytics can have on software engineering processes and stakeholders?
- Are there important questions that are not being asked because the answers do not lie in the data that are readily available?
- Can we improve the application of software analytics using other methods that collect insights directly from participants in software engineering (e.g., through observations)?
I will explore these questions through specific examples. I hope to engage the audience in discussing how software analytics that depend on "big data" from tools, as well as methods that collect "thick" data from participants, can be mutually beneficial in improving software engineering research and practice.