这是谁?使用IDE事件数据识别开发人员

2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR) Pub Date : 2018-05-28 DOI:10.1145/3196398.3196461

J. Wilkie, Ziad Al Halabi, Alperen Karaoglu, Jiafeng Liao, George Ndungu, Chaiyong Ragkhitwetsagul, M. Paixão, J. Krinke

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引用次数: 2

摘要

本文介绍了一种基于IDE事件数据识别开发人员的技术。我们利用了KaVE数据集，该数据集记录了来自85个开发人员的IDE活动和1100万个事件。我们发现，在原始事件计数上使用具有线性核的SVM在识别开发人员方面优于k-NN，准确率为0.52。此外，在设置了训练分类器的最优事件数和会话数后，我们分别达到了0.69和0.71的更高准确率。研究结果表明，我们可以根据IDE事件数据来识别开发人员。该技术可以进一步扩展，以便对类似的开发人员进行分组，以获得IDE特性建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Who's This? Developer Identification Using IDE Event Data

This paper presents a technique to identify a developer based on their IDE event data. We exploited the KaVE data set which recorded IDE activities from 85 developers with 11M events. We found that using an SVM with a linear kernel on raw event count outperformed k-NN in identifying developers with an accuracy of 0.52. Moreover, after setting the optimal number of events and sessions to train the classifier, we achieved a higher accuracy of 0.69 and 0.71 respectively. The findings shows that we can identify developers based on their IDE event data. The technique can be expanded further to group similar developers for IDE feature recommendations.

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来源期刊

2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR)

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