On the Lexical Distinguishability of Source Code

TL;DR

This paper investigates the core words in source code that are essential for distinguishing functions, providing quantitative evidence for keyword-based programming and new insights into programming models.

Contribution

It introduces a method to identify minimal distinguishing subsets of code, called Minsets, demonstrating that functions have core 'wheat' words crucial for understanding.

Findings

Functions contain a small set of key words that distinguish them

Quantitative evidence supports keyword-based programming approaches

Large corpus analysis confirms the presence of minimal distinguishing code subsets

Abstract

Natural language is robust against noise. The meaning of many sentences survives the loss of words, sometimes many of them. Some words in a sentence, however, cannot be lost without changing the meaning of the sentence. We call these words "wheat" and the rest "chaff". The word "not" in the sentence "I do not like rain" is wheat and "do" is chaff. For human understanding of the purpose and behavior of source code, we hypothesize that the same holds. To quantify the extent to which we can separate code into "wheat" and "chaff", we study a large (100M LOC), diverse corpus of real-world projects in Java. Since methods represent natural, likely distinct units of code, we use the ~9M Java methods in the corpus to approximate a universe of "sentences." We extract their wheat by computing the function's minimal distinguishing subset (Minset). Our results confirm that functions contain work offers the first quantitative evidence for recent promising work on keyword-based programming and insight into how to develop a powerful, alternative programming model.