SEMar 31, 2019

Exploring the Generality of a Java-based Loop Action Model for the Quorum Programming Language

arXiv:1904.00478v1
Originality Synthesis-oriented
AI Analysis

This work addresses the challenge of leveraging intermediate abstraction levels in code for developers, though it is incremental as it adapts an existing method to a new domain.

The paper tackled the problem of automatically identifying high-level actions performed by loops in source code, which are often undocumented, by applying a Java-based action identification model to the Quorum programming language, with results suggesting the approach could generalize to other languages.

Many algorithmic steps require more than one statement to implement, but not big enough to be a method (e.g., add element, find the maximum, determine a value, etc.). These steps are generally implemented by loops. Internal comments for the loops often describe these intermediary steps, however, unfortunately a very small percentage of code is well documented to help new users/coders. As a result, information at levels of abstraction between the individual statement and the whole method is not leveraged by current source code analyses, as that information is not easily available beyond any internal comments describing the code blocks. Hence, this project explores the generality of an approach to automatically determine the high level actions of loop constructs. The approach is to mine loop characteristics of a given loop structure over the repository of the Quorum language source code, map it to an (already developed for Java) action identification model, and thus identify the action performed by the specified loop. The results are promising enough to conclude that this approach could be applied to other programming languages too.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes