Questions Developers Ask
URL
Change Log
| When | What |
|---|---|
| September 10th, 2015 | Donated by Thomas Fritz |
Reference
Studies who have been using the data (in any form) are required to include the following reference:
@inproceedings{Fritz:2010:UIF:1806799.1806828,
author = {Fritz, Thomas and Murphy, Gail C.},
title = {Using Information Fragments to Answer the Questions Developers Ask},
booktitle = {Proceedings of the 32Nd ACM/IEEE International Conference on Software Engineering - Volume 1},
series = {ICSE '10},
year = {2010},
isbn = {978-1-60558-719-6},
location = {Cape Town, South Africa},
pages = {175--184},
numpages = {10},
url = {http://doi.acm.org/10.1145/1806799.1806828},
doi = {10.1145/1806799.1806828},
acmid = {1806828},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {human-centric software engineering, information fragments, programming tools},
}
About the Data
Overview of Data
The data here is the 78 Questions that developers want to ask, but for which support is lacking, it also includes the domain of the desired answers. These were obtained by the authors through interviews with eleven different professional developers
Paper Abstract
Each day, a software developer needs to answer a variety of questions that require the integration of different kinds of project information. Currently, answering these questions, such as “What have my co-workers been doing?”, is tedious, and sometimes impossible, because the only support available requires the developer to manually link and traverse the information step-by-step. Through interviews with eleven professional developers, we identified 78 questions developers want to ask, but for which support is lacking. We introduce an information fragment model (and prototype tool) that automates the composition of different kinds of information and that allows developers to easily choose how to display the composed information. In a study, 18 professional developers used the prototype tool to answer eight of the 78 questions. All developers were able to easily use the prototype to successfully answer 94% of questions in a mean time of 2.3 minutes per question.