Automatic Assessments of Code Explanations

Predicting Answering Times on Stack Overflow

Conference paper (2015)

Authors

Selman Ercan Student
Q.A. Stokkink Student
A. Bacchelli Software Engineering - EEMCS
Research Group
Software Engineering (EEMCS) (TU Delft)
Stack overflow Answering time
More Info
expand_more

Published Date

2015

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Software Engineering

Abstract

Users of Question & Answer websites often include code fragments in their questions. However, large and unexplained code fragments make it harder for others to understand the question, thus possibly impacting the time required to obtain a correct answer. In this paper, we quantitatively study this relation: We look at questions containing code fragments and investigate the influence of explaining these fragments better on the time to answer. We devise an approach to quantify code explanations and apply it to ~300K posts. We find that it causes up to a 5σ (single-tail significant) increase in precision over baseline prediction times. This supports the use of our approach as an `edit suggestion': Questions with a low score could trigger a warning suggesting the user to better explain the included code.