Learn More
This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread during its lifetime, so that synchronization operations on that object can be removed. We introduce a new program abstraction for(More)
—The problem of predicting links or interactions between objects in a network, is an important task in network analysis. Along this line, link prediction between co-authors in a co-author network is a frequently studied problem. In most of these studies, authors are considered in a homogeneous network, i.e., only one type of objects (author type) and one(More)
Social tagging on online portals has become a trend now. It has emerged as one of the best ways of associating metadata with web objects. With the increase in the kinds of web objects becoming available, collaborative tagging of such objects is also developing along new dimensions. This popularity has led to a vast literature on social tagging. In this(More)
Software systems obey the 80/20 rule: aggressively optimizing a vital few execution paths yields large speedups. However, finding the vital few paths can be difficult, especially for large systems like web applications. This paper describes a novel approach to finding bottlenecks in such systems, given (possibly very large) profiles of system executions. In(More)
As the complexity of distributed computing systems increases, systems management tasks require significantly higher levels of automation; examples include diagnosis and prediction based on real-time streams of computer events, setting alarms, and performing continuous monitoring. The core of <i>autonomic computing</i>, a recently proposed initiative towards(More)
With the phenomenal success of networking sites (<i>e.g.</i>, Facebook, Twitter and LinkedIn), social networks have drawn substantial attention. On online social networking sites, link recommendation is a critical task that not only helps improve user experience but also plays an essential role in network growth. In this paper we propose several link(More)
Temporal datasets, in which data evolves continuously, exist in a wide variety of applications, and identifying anomalous or outlying objects from temporal datasets is an important and challenging task. Different from traditional outlier detection, which detects objects that have quite different behavior compared with the other objects, temporal outlier(More)