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Authors: Nikolai Moesus 1 ; Matthias Scholze 1 ; Sebastian Schlesinger 2 and Paula Herber 2

Affiliations: 1 QMETHODS – Business & IT Consulting GmbH, Berlin and Germany ; 2 Software and Embedded Systems Engineering, Technische Universität Berlin and Germany

Keyword(s): Software Refactoring, Performance, Static Analysis, Profiling.

Abstract: Performance is a critical property of a program. While there exist refactorings that have the potential to significantly increase the performance of a program, it is hard to decide which refactorings effectively yield improvements. In this paper, we present a novel approach for the automated detection and selection of refactorings that are promising candidates to improve performance. Our key idea is to provide a heuristics that utilizes software properties determined by both static code analyses and dynamic software analyses to compile a list of concrete refactorings sorted by their assessed potential to improve performance. The expected performance improvement of a concrete refactoring depends on two factors: the execution frequency of the respective piece of code, and the effectiveness of the refactoring itself. To assess the latter, namely the general effectiveness of a given set of refactorings, we have implemented a set of micro benchmarks and measured the effect of each refacto ring on computation time and memory consumption. We demonstrate the practical applicability of our overall approach with experimental results. (More)

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Paper citation in several formats:
Moesus, N.; Scholze, M.; Schlesinger, S. and Herber, P. (2018). Automated Selection of Software Refactorings that Improve Performance. In Proceedings of the 13th International Conference on Software Technologies - ICSOFT; ISBN 978-989-758-320-9; ISSN 2184-2833, SciTePress, pages 33-44. DOI: 10.5220/0006837900670078

@conference{icsoft18,
author={Nikolai Moesus. and Matthias Scholze. and Sebastian Schlesinger. and Paula Herber.},
title={Automated Selection of Software Refactorings that Improve Performance},
booktitle={Proceedings of the 13th International Conference on Software Technologies - ICSOFT},
year={2018},
pages={33-44},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006837900670078},
isbn={978-989-758-320-9},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Software Technologies - ICSOFT
TI - Automated Selection of Software Refactorings that Improve Performance
SN - 978-989-758-320-9
IS - 2184-2833
AU - Moesus, N.
AU - Scholze, M.
AU - Schlesinger, S.
AU - Herber, P.
PY - 2018
SP - 33
EP - 44
DO - 10.5220/0006837900670078
PB - SciTePress

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