• Publications
  • Influence
Predicting Defects for Eclipse
TLDR
The resulting data set lists the number of pre- and post-release defects for every package and file in the eclipse releases 2.0, 2.1, and 3.0.
When do changes induce fixes?
TLDR
In a first investigation of the MOZILLA and ECLIPSE history, it turns out that fix-inducing changes show distinct patterns with respect to their size and the day of week they were applied.
Predicting defects using network analysis on dependency graphs
TLDR
This paper proposes to use network analysis on dependency graphs of the entire system to identify central program units that are more likely to face defects and finds that the recall for models building from network measures is by 10% points higher than for models built from complexity metrics.
Mining version histories to guide software changes
We apply data mining to version histories in order to guide programmers along related changes: "Programmers who changed these functions also changed. . . ". Given a set of existing changes, such
Mining version histories to guide software changes
We apply data mining to version histories in order to guide programmers along related changes: "Programmers who changed these functions also changed. . . ". Given a set of existing changes, such
Cross-project defect prediction: a large scale experiment on data vs. domain vs. process
TLDR
This paper studied cross-project defect prediction models on a large scale and identified factors that do influence the success of cross- project predictions, and derived decision trees that can provide early estimates for precision, recall, and accuracy before a prediction is attempted.
Mining version histories to guide software changes
TLDR
The ROSE prototype can correctly predict further locations to be changed and show up item coupling that is undetectable by program analysis, and can prevent errors due to incomplete changes.
Software Engineering for Machine Learning: A Case Study
TLDR
A study conducted on observing software teams at Microsoft as they develop AI-based applications finds that various Microsoft teams have united this workflow into preexisting, well-evolved, Agile-like software engineering processes, providing insights about several essential engineering challenges that organizations may face in creating large-scale AI solutions for the marketplace.
What Makes a Good Bug Report?
TLDR
The CUEZILLA prototype is a tool that measures the quality of new bug reports and recommends which elements should be added to improve the quality, and discusses several recommendations for better bug tracking systems which should focus on engaging bug reporters, better tool support, and improved handling of bug duplicates.
Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness
TLDR
A study with 30 participants who had adopted wearable activity-tracking devices of their own volition and had continued to use them for between 3 and 54 months paints a picture of the evolving benefits and practices surrounding these emerging technologies over long periods of use.
...
...