Refining active learning to increase behavioral coverage

Onderzoeksoutput: Bijdrage aan congresAbstract

Samenvatting

Modern high-tech industry is dealing with the maintenance of complex software systems today which consist of a large number of interconnected software components. Many of these components become legacy over years due to lack of documentation and unavailability of original developers. Several techniques are available in literature to retrieve the behavioral models from the existing software. Among those, the dynamic analysis techniques analyze the actual execution of the software, either via execution traces (passive learning), or by interaction with the software components (active learning). These techniques cannot guarantee alone to learn the complete and correct software behavior due to the limitations of each technique. We present an approach to aid active learning technique with software logs (execution traces) and passive learning result to increase the behavioral coverage of learned models.
Originele taal-2Engels
Aantal pagina's1
StatusGepubliceerd - 3 okt 2018
EvenementACM Celebration of Women in Computing
womENcourage 2018
- Belgrade, Servië
Duur: 3 okt 20185 okt 2018
https://womencourage.acm.org/2018/

Congres

CongresACM Celebration of Women in Computing
womENcourage 2018
LandServië
StadBelgrade
Periode3/10/185/10/18
Internet adres

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Citeer dit

Aslam, K., Luo, Y., Schiffelers, R. R. H., & van den Brand, M. G. J. (2018). Refining active learning to increase behavioral coverage. Abstract van ACM Celebration of Women in Computing
womENcourage 2018, Belgrade, Servië.