Stefanakos, Ioannis orcid.org/0000-0003-3741-252X, Calinescu, Radu orcid.org/0000-0002-2678-9260 and Gerasimou, Simos (Accepted: 2021) Probabilistic Program Performance Analysis. In: EUROMICRO Conference on Software Engineering and Advanced Applications (SEAA 2021). IEEE , pp. 148-157. (In Press)
Abstract
We introduce a tool-supported method for the formal analysis of timing, resource use, cost and other quality aspects of computer programs. The new method synthesises a Markov-chain model of the analysed code, computes this quantitative model’s transition probabilities using information from program logs, and employs probabilistic model checking to evaluate the performance properties of interest. Unlike existing solutions, our method can reuse the probabilistic model to accurately predict how the program performance would change if the code ran on a different hardware platform, used a new function library, or had a different usage profile. We show the effectiveness of our method by using it to analyse the performance of Java code from the Apache Commons Math library, the Android messaging app Telegram, and an implementation of the knapsack algorithm.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 16 Jul 2021 12:10 |
Last Modified: | 16 Oct 2024 11:14 |
Published Version: | https://doi.org/10.1109/SEAA53835.2021.00027 |
Status: | In Press |
Publisher: | IEEE |
Identification Number: | 10.1109/SEAA53835.2021.00027 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:176272 |