Standard

Automatic Assessments of Code Explanations : Predicting Answering Times on Stack Overflow. / Ercan, Selman; Stokkink, Quinten; Bacchelli, Alberto.

Proceedings of the 12th Working Conference on Mining Software Repositories, MSR 2015. ed. / M. Di Penta. Piscataway.NJ : IEEE Society, 2015. p. 442-445.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Ercan, S, Stokkink, Q & Bacchelli, A 2015, Automatic Assessments of Code Explanations: Predicting Answering Times on Stack Overflow. in M Di Penta (ed.), Proceedings of the 12th Working Conference on Mining Software Repositories, MSR 2015. IEEE Society, Piscataway.NJ, pp. 442-445, MSR 2015, Florence, Italy, 16/05/15. https://doi.org/10.1109/MSR.2015.59

APA

Ercan, S., Stokkink, Q., & Bacchelli, A. (2015). Automatic Assessments of Code Explanations: Predicting Answering Times on Stack Overflow. In M. Di Penta (Ed.), Proceedings of the 12th Working Conference on Mining Software Repositories, MSR 2015 (pp. 442-445). Piscataway.NJ: IEEE Society. https://doi.org/10.1109/MSR.2015.59

Vancouver

Ercan S, Stokkink Q, Bacchelli A. Automatic Assessments of Code Explanations: Predicting Answering Times on Stack Overflow. In Di Penta M, editor, Proceedings of the 12th Working Conference on Mining Software Repositories, MSR 2015. Piscataway.NJ: IEEE Society. 2015. p. 442-445 https://doi.org/10.1109/MSR.2015.59

Author

Ercan, Selman ; Stokkink, Quinten ; Bacchelli, Alberto. / Automatic Assessments of Code Explanations : Predicting Answering Times on Stack Overflow. Proceedings of the 12th Working Conference on Mining Software Repositories, MSR 2015. editor / M. Di Penta. Piscataway.NJ : IEEE Society, 2015. pp. 442-445

BibTeX

@inproceedings{ededf90eec4a4be5a0ab84c0ea45298e,
title = "Automatic Assessments of Code Explanations: Predicting Answering Times on Stack Overflow",
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.",
keywords = "stack overflow, answering time",
author = "Selman Ercan and Quinten Stokkink and Alberto Bacchelli",
note = "harvest",
year = "2015",
doi = "10.1109/MSR.2015.59",
language = "English",
isbn = "978-0-7695-5594-2",
pages = "442--445",
editor = "{Di Penta}, M.",
booktitle = "Proceedings of the 12th Working Conference on Mining Software Repositories, MSR 2015",
publisher = "IEEE Society",

}

RIS

TY - GEN

T1 - Automatic Assessments of Code Explanations

T2 - Predicting Answering Times on Stack Overflow

AU - Ercan, Selman

AU - Stokkink, Quinten

AU - Bacchelli, Alberto

N1 - harvest

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - stack overflow

KW - answering time

U2 - 10.1109/MSR.2015.59

DO - 10.1109/MSR.2015.59

M3 - Conference contribution

SN - 978-0-7695-5594-2

SP - 442

EP - 445

BT - Proceedings of the 12th Working Conference on Mining Software Repositories, MSR 2015

A2 - Di Penta, M.

PB - IEEE Society

CY - Piscataway.NJ

ER -

ID: 1648941