Access Type

Open Access Thesis

Date of Award

January 2016

Degree Type

Thesis

Degree Name

M.S.

Department

Computer Science

First Advisor

Marwan Abi-Antoun

Abstract

Developers need to understand the runtime structure of object-oriented code, and abstract object graphs can help. To extract abstract object graphs that convey design intent in the form of object hierarchy, additional information is needed to express this hierarchy in the code using ownership types, but adding ownership type qualifiers after the fact involves manual overhead, and requires developers to switch between adding qualifiers in the code and looking at abstract object graphs to understand the object structures that the qualifiers describe. We describe an approach where developers express their design intent by refining an object graph directly, while an inference analysis infers valid qualifiers in the code. A separate extraction analysis then uses these qualifiers and extracts an updated object graph. We implement and test the approach on several small test cases and confirm its feasibility.

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