Learning Program Models from Generated Inputs
Recent advances in Machine Learning (ML) show that Neural Machine Translation (NMT) models can mock the program behavior when trained on input-output pairs. Such models can mock the functionality of existing programs and serve as quick-to-deploy reverse engineering tools. Still, the problem of autom...
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| Vydáno v: | Proceedings (IEEE/ACM International Conference on Software Engineering Companion. Online) s. 245 - 247 |
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| Hlavní autor: | |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.05.2023
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| Témata: | |
| ISSN: | 2574-1934 |
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| Abstract | Recent advances in Machine Learning (ML) show that Neural Machine Translation (NMT) models can mock the program behavior when trained on input-output pairs. Such models can mock the functionality of existing programs and serve as quick-to-deploy reverse engineering tools. Still, the problem of automatically learning such predictive and reversible models from programs needs to be solved. This work introduces a generic approach for automated and reversible program behavior modeling. It achieves 94% of overall accuracy in the conversion of Markdown-to-HTML and HTML-to-Markdown markups. |
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| AbstractList | Recent advances in Machine Learning (ML) show that Neural Machine Translation (NMT) models can mock the program behavior when trained on input-output pairs. Such models can mock the functionality of existing programs and serve as quick-to-deploy reverse engineering tools. Still, the problem of automatically learning such predictive and reversible models from programs needs to be solved. This work introduces a generic approach for automated and reversible program behavior modeling. It achieves 94% of overall accuracy in the conversion of Markdown-to-HTML and HTML-to-Markdown markups. |
| Author | Mammadov, Tural |
| Author_xml | – sequence: 1 givenname: Tural surname: Mammadov fullname: Mammadov, Tural email: tural.mammadov@cispa.de organization: Saarland University,CISPA Helmholtz Center for Information Security,Saarbrücken,Germany |
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| Snippet | Recent advances in Machine Learning (ML) show that Neural Machine Translation (NMT) models can mock the program behavior when trained on input-output pairs.... |
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| SubjectTerms | Behavioral sciences deep learning Machine learning Machine translation Predictive models Reverse engineering security testing Software Software engineering software testing |
| Title | Learning Program Models from Generated Inputs |
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