“Using (Bio)Metrics to Predict Code Quality” is currently one of the most downloaded articles in software engineering

We are happy to announce that our paper “Using (Bio)Metrics to Predict Code Quality Online”, written by Sebastian Müller and Thomas Fritz, was one of the most downloaded software engineering articles in June and July 2016. With 1709 downloads in 6 weeks, it scored the second place of all ACM software engineering articles. According to ACM, this is the first time that any paper was downloaded more than 1000 times.

screen-shot-2016-10-05-at-14-18-11

Image source: ACM SIGSOFT Software Engineering Notes. Volume 41 Number 4.

The paper investigates the use of biometrics, such as heart rate variability (HRV) or electro-dermal activity (EDA) to determine the difficulty that developers experience while working on real world change tasks and automatically identify code quality concerns while a developer is making a change to the code. It can be accessed here.

2 thoughts on ““Using (Bio)Metrics to Predict Code Quality” is currently one of the most downloaded articles in software engineering

  1. How can “this is the first time that any paper was downloaded more than 1000 times.” be when there is a first paper that was downloaded more often than yours?

  2. The top downloaded paper and our paper are – at the same time – the first papers that were downloaded more than 1000 times.

    To quote from the ACM SIGSOFT Software Engineering Notes Volume 41 Number 4: “Note: It is interesting to see the number of times that the top two papers have been downloaded! This is the first time any papers have been downloaded over 1,000 times! Also, note 8 of the 10 are from the proceedings of ICSE 2016.”

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s