A Metric for Software Readability - ArrestedComputing

A Metric forSoftwareReadabilityRay Buse ∙ Westley WeimerISSTA 2008

Readability“The quality that enables the observer to correctlyperceive the message”Metrics for Natural Language• Flesch-Kincaid Grade Level• Gunning-Fog Index• SMOG Index• Automated Readability Index2

Readability and SoftwareCode maintenance = 70% of lifecycle cost.And most of maintenance effort is spent readingcode!But do we have any way to gain some level ofassurance in code readability?5

HypothesisEmploying a simple set of local features, we canderive, from a set of human judgments, an accuratemodel of readability for code.• To what extent do humans agree on codereadability?• We know readability is important, but can we createa predictive model of it?• What could such a model teach us?6

Outline• Acquiring Human Readability Judgments• Extracting a Model• Model Performance• Correlation with External Notions of SoftwareQuality• Readability and the Software Lifecycle7

8Snippet Sniper Demo

Scoring Data11

Score Distribution12

Setup13

FeaturesWe choose “local” code features• Line length• Length of identifier names• Comment density• Blank lines• Presence of numbers• [and 20 others]14

Model Performance15

External Notions of Quality16

Software Lifecycle17

Software Lifecycle 218

ConclusionsWe can automatically judge readability about aswell as the “average” human canThis notion of readability shows significantcorrelation with:• Version Changes• The output of a bug finder• Self-reported program maturityWe may also learn more about software readabilityby looking at the predictive power of our model’sfeatures19

Questions?Questions?20