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Companion repository to the paper "Learning Input-aware Performance Models of Configurable Systems: An Empirical Evaluation"

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Learning Input-aware Performance Models of Configurable Systems: An Empirical Evaluation

This is the companion repository of our submission "Learning Input-aware Performance Models of Configurable Systems: An Empirical Evaluation", appeared in Journal of Systems & Software Preprint.

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Measurements and details about the performances can be consulted in the data folder.

Source code can be consulted in the src directory.

The results directory contains the results shown in the submission, as well as complementary results.

In a nutshell

In this paper, we present an empirical evaluation of different learning techniques when predicting the performance properties of software systems according to their configuration and to their input data.

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Companion repository to the paper "Learning Input-aware Performance Models of Configurable Systems: An Empirical Evaluation"

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