Pointer swizzling improves the performance of OODBMSs by reducing the number of table lookups. However, the object replacement incurs the unswizzling overhead. In this paper, we propose a new pointer swizzling strategy, the dynamic indirect pointer swizzling (DIPS). DIPS dynamically applies pointer swizzling techniques in order to reduce the overhead of unswizzling. DIPS uses the temporal local...

Pointer analysis is a fundamental static program analysis, with a rich literature and wide applications. The goal of pointer analysis is to compute an approximation of the set of program objects that a pointer variable or expression can refer to. We present an introduction and survey of pointer analysis techniques, with an emphasis on distilling the essence of common analysis algorithms. To thi...

The Simplified Self-Adapting Skip List, a practical new extension of the Skip List data structure, is designed for use with data that exhibit bias, that is, a nonuniform distribution of queries to set elements. The structure observes an initially unknown degree of bias in queries to a data set and adapts itself to a consistently nearly-optimal configuration, improving search efficiency and spee...

In this paper, we study the influence of both long and short skip connections on Fully Convolutional Networks (FCN) for biomedical image segmentation. In standard FCNs, only long skip connections are used to skip features from the contracting path to the expanding path in order to recover spatial information lost during downsampling. We extend FCNs by adding short skip connections, that are sim...

Pointer analysis is a fundamental static program analysis, with a rich literature and wide applications. The goal of pointer analysis is to compute an approximation of the set of program objects that a pointer variable or expression can refer to. We present an introduction and survey of pointer analysis techniques, with an emphasis on distilling the essence of common analysis algorithms. To thi...

The popular skip-gram model induces word embeddings by exploiting the signal from word-context coocurrence. We offer a new interpretation of skip-gram based on exponential family PCA—a form of matrix factorization. This makes it clear that we can extend the skip-gram method to tensor factorization, in order to train embeddings through richer higher-order coocurrences, e.g., triples that include...

Many optimizations need precise pointer analyses to be effective. Unfortunately, some Java features, such as dynamic class loading, reflection, and native methods, make pointer analyses difficult to develop. Hence, prior pointer analyses for Java either ignore these features or are overly conservative. This paper presents the first non-trivial pointer analysis that deals with all Java language ...