WAP: Understanding the Brain at Software Debugging

2016 
We propose that understanding functional patterns of activity in mapped brain regions associated with code comprehension tasks and, more specifically, to the activity of finding bugs in traditional code inspections could reveal useful insights to improve software reliability and to improve the software development process in general. This includes helping to select the best professionals for the debugging effort, improving the conditions for code inspections, and identify new directions to follow for training code reviewers. This paper presents an interdisciplinary study to analyze the brain activity during code inspection tasks using functional magnetic resonance imaging (fMRI), which is a well-established tool in cognitive neuroscience research. We used several programs where realistic bugs representing the most frequent types of software faults found in the field were injected. The code inspectors involved in the research include programmers with different levels of expertise and experience in real code reviews. The goal is to understand brain activity patterns associated with code comprehension tasks and, more specifically, the brain activity when the code reviewer identifies a bug in the code ('eureka' moment), which can be a true positive or a false positive. Our results confirmed that brain areas associated with language processing and mathematics are highly active during code reviewing and shows that there are specific brain activity patterns that can be related to the decision-making moment of suspicion/bug detection. Importantly, the activity at the anterior insula region that we find to play a relevant role in the process of identifying software bugs is positively correlated to the precision of bug detection by the inspectors. This finding provides a new perspective on the role of this region on error awareness and monitoring and of its potential predictive value in predicting the quality of bug removing.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    13
    References
    28
    Citations
    NaN
    KQI
    []