Measuring source code conciseness across programming languages using compression

TL;DR

This paper introduces an information-theoretic model to objectively measure and compare the conciseness of different programming languages, validated through large-scale analysis and surveys.

Contribution

It presents a novel, evidence-based approach for quantifying programming language conciseness using compression, applicable to diverse software applications.

Findings

Strong correlation with alternative analytical methods

High correlation with developer survey results

Useful for improving multi-language software metrics

Abstract

It is well-known, and often a topic of heated debates, that programs in some programming languages are more concise than in others. This is a relevant factor when comparing or aggregating volume-impacted metrics on source code written in a combination of programming languages. In this paper, we present a model for measuring the conciseness of programming languages in a consistent, objective and evidence-based way. We present the approach, explain how it is founded on information theoretical principles, present detailed analysis steps and show the quantitative results of applying this model to a large benchmark of diverse commercial software applications. We demonstrate that our metric for language conciseness is strongly correlated with both an alternative analytical approach, and with a large scale developer survey, and show how its results can be applied to improve software metrics for multi-language applications.