"Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis", In ASE 2017
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README.md

An Empirical Study of Transfer Learning for Performance Analysis

This repository contains the supplementary materials (data, scripts, results, etc) of our empirical study on the similarities of performance measurements across environments, this research shed some lights on transfer learning for performance modeling and analysis of highly configurable software systems. The results are presented in our paper "Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis" (ASE 2017) by Pooyan Jamshidi, Norbert Siegmund, Miguel Velez, Christian Kaestner, Akshay Patel, and Yuvraj Agarwal.

Citing the paper

If you find this research useful in your research or if you use the dataset in your research, please consider citing:

@InProceedings{JSVKPA:ASE17,
    title     = {Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis},
    author    = {Jamshidi, Pooyan and Siegmund, Norbert and Velez, Miguel and K\"{a}stner, Christian and Patel, Akshay and Agarwal, Yuvraj},
    booktitle = {Proc. Int'l Conf. Automated Software Engineering (ASE)},
    year      = {2017},
    publisher = {ACM}
} 

Complementary materials

Contact

If you have a question or feedback, please send us an email:

Pooyan Jamshidi, Carnegie Mellon University, pooyan.jamshidi@gmail.com

Licence

The data is published under the MIT License.