Clustering and Dynamic Invariant Detection

dc.rights.license	CC-BY-NC-ND
dc.contributor.advisor	Prasetya, Wishnu
dc.contributor.advisor	Feelders, Ad
dc.contributor.author	Pol, A.
dc.date.accessioned	2015-08-19T17:00:36Z
dc.date.available	2015-08-19T17:00:36Z
dc.date.issued	2015
dc.identifier.uri	https://studenttheses.uu.nl/handle/20.500.12932/21109
dc.description.abstract	Dynamic invariant detection is the process of distilling invariants from information about a program run. Clustering is the practice of grouping information into groups of similar elements. As properties of variables at program points are dependent upon conditionals upon said variables, clustering a program trace may have merit. The effects of different ways of clustering inputs to Daikon are examined, and an algorithm for automatically detecting program failures without any programmer interference will be shown.
dc.description.sponsorship	Utrecht University
dc.format.extent	428187
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.title	Clustering and Dynamic Invariant Detection
dc.type.content	Master Thesis
dc.rights.accessrights	Open Access
dc.subject.keywords	clustering;daikon;mujava;invariant;detection;java;
dc.subject.courseuu	Computing Science