Conferencia
Abstract:
In recent years, research efforts have been directed towards the use of Machine Learning (ML) techniques to support and automate activities such as program repair, specification mining and risk assessment. The focus has largely been on techniques for classification, clustering and regression. Although beneficial, these do not produce a declarative, interpretable representation of the learned information. Hence, they cannot readily be used to inform, revise and elaborate software models. On the other hand, recent advances in ML have witnessed the emergence of new logic-based learning approaches that differ from traditional ML in that their output is represented in a declarative, rule-based manner, making them well-suited for many software engineering tasks. In this technical briefing, we will introduce the audience to the latest advances in logic-based learning, give an overview of how logic-based learning systems can successfully provide automated support to a variety of software engineering tasks, demonstrate the application to two real case studies from the domain of requirements engineering and software design and highlight future challenges and directions. © 2016 Authors.
Registro:
| Documento: | Conferencia |
| Título: | Logic-based learning in software engineering |
| Autor: | Alrajeh, D.; Russo, A.; Uchitel, S.; Kramer, J. |
| Filiación: | Imperial College London, United Kingdom Departamento de Computación, Universidad de Buenos Aires and CONICET, Argentina |
| Palabras clave: | Application programs; Computer circuits; Learning systems; Risk assessment; Software design; Software engineering; Technical presentations; Automated support; Future challenges; Interpretable representation; Learning approach; Research efforts; Rule based; Software model; Specification mining; Engineering education |
| Año: | 2016 |
| Página de inicio: | 892 |
| Página de fin: | 893 |
| DOI: | http://dx.doi.org/10.1145/2889160.2891050 |
| Título revista: | 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering, ICSE 2016 |
| Título revista abreviado: | Proc Int Conf Software Eng |
| ISSN: | 02705257 |
| CODEN: | PCSED |
| Registro: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_02705257_v_n_p892_Alrajeh |
Referencias:
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Citas:
---------- APA ----------
Alrajeh, D., Russo, A., Uchitel, S. & Kramer, J. (2016) . Logic-based learning in software engineering. 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering, ICSE 2016, 892-893.http://dx.doi.org/10.1145/2889160.2891050
---------- CHICAGO ----------
Alrajeh, D., Russo, A., Uchitel, S., Kramer, J. "Logic-based learning in software engineering" . 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering, ICSE 2016 (2016) : 892-893.http://dx.doi.org/10.1145/2889160.2891050
---------- MLA ----------
Alrajeh, D., Russo, A., Uchitel, S., Kramer, J. "Logic-based learning in software engineering" . 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering, ICSE 2016, 2016, pp. 892-893.http://dx.doi.org/10.1145/2889160.2891050
---------- VANCOUVER ----------
Alrajeh, D., Russo, A., Uchitel, S., Kramer, J. Logic-based learning in software engineering. Proc Int Conf Software Eng. 2016:892-893.http://dx.doi.org/10.1145/2889160.2891050
