Efficient Reflection String Analysis via Graph Coloring

Static analyses for reflection and other dynamic language features have recently increased in number and advanced in sophistication. Most such analyses rely on a whole-program model of the flow of strings, through the stack and heap. We show that this global modeling of strings remains a major bottleneck of static analyses and propose a compact encoding, in order to battle unnecessary complexity. In our encoding, strings are maximally merged if they can never serve to differentiate class members in reflection operations. We formulate the problem as an instance of graph coloring and propose a fast polynomial-time algorithm that exploits the unique features of the setting (esp. large cliques, leading to hundreds of colors for realistic programs). The encoding is applied to two different frameworks for string-guided Java reflection analysis from past literature and leads to significant optimization (e.g., a ~2x reduction in the number of string-flow inferences), for a whole-program points-to analysis that uses strings

Defensive Points-To Analysis: Effective Soundness via Laziness

We present a defensive may-point-to analysis approach, which offers soundness even in the presence of arbitrary opaque code: all non-empty points-to sets computed are guaranteed to be over-approximations of the sets of values arising at run time. A key design tenet of the analysis is laziness: the analysis computes points-to relationships only for variables or objects that are guaranteed to never escape into opaque code. This means that the analysis misses some valid inferences, yet it also never wastes work to compute sets of values that are not "complete", i.e., that may be missing elements due to opaque code. Laziness enables great efficiency, allowing a highly precise points-to analysis (such as a 5-call-site-sensitive, flow-sensitive analysis). Despite its conservative nature, our analysis yields sound, actionable results for a large subset of the program code, achieving (under worst-case assumptions) 34-74% of the program coverage of an unsound state-of-the-art analysis for real-world programs

Program Tailoring: Slicing by Sequential Criteria

Protocol and typestate analyses often report some sequences of statements ending at a program point P that needs to be scrutinized, since P may be erroneous or imprecisely analyzed. Program slicing focuses only on the behavior at P by computing a slice of the program affecting the values at P. In this paper, we propose to restrict our attention to the subset of that behavior at P affected by one or several statement sequences, called a sequential criterion (SC). By leveraging the ordering information in a SC, e.g., the temporal order in a few valid/invalid API method invocation sequences, we introduce a new technique, program tailoring, to compute a tailored program that comprises the statements in all possible execution paths passing through at least one sequence in SC in the given order. With a prototyping implementation, Tailor, we show why tailoring is practically useful by conducting two case studies on seven large real-world Java applications. For program debugging and understanding, Tailor can complement program slicing by removing SC-irrelevant statements. For program analysis, Tailor can enable a pointer analysis, which is unscalable to a program, to perform a more focused and therefore potentially scalable analysis to its specific parts containing hard language features such as reflection

Connected Information Management

Society is currently inundated with more information than ever, making efficient management a necessity. Alas, most of current information management suffers from several levels of disconnectedness: Applications partition data into segregated islands, small notes don’t fit into traditional application categories, navigating the data is different for each kind of data; data is either available at a certain computer or only online, but rarely both. Connected information management (CoIM) is an approach to information management that avoids these ways of disconnectedness. The core idea of CoIM is to keep all information in a central repository, with generic means for organization such as tagging. The heterogeneity of data is taken into account by offering specialized editors. The central repository eliminates the islands of application-specific data and is formally grounded by a CoIM model. The foundation for structured data is an RDF repository. The RDF editing meta-model (REMM) enables form-based editing of this data, similar to database applications such as MS access. Further kinds of data are supported by extending RDF, as follows. Wiki text is stored as RDF and can both contain structured text and be combined with structured data. Files are also supported by the CoIM model and are kept externally. Notes can be quickly captured and annotated with meta-data. Generic means for organization and navigation apply to all kinds of data. Ubiquitous availability of data is ensured via two CoIM implementations, the web application HYENA/Web and the desktop application HYENA/Eclipse. All data can be synchronized between these applications. The applications were used to validate the CoIM ideas

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Intelligent Agents and Their Potential for Future Design and Synthesis Environment

This document contains the proceedings of the Workshop on Intelligent Agents and Their Potential for Future Design and Synthesis Environment, held at NASA Langley Research Center, Hampton, VA, September 16-17, 1998. The workshop was jointly sponsored by the University of Virginia's Center for Advanced Computational Technology and NASA. Workshop attendees came from NASA, industry and universities. The objectives of the workshop were to assess the status of intelligent agents technology and to identify the potential of software agents for use in future design and synthesis environment. The presentations covered the current status of agent technology and several applications of intelligent software agents. Certain materials and products are identified in this publication in order to specify adequately the materials and products that were investigated in the research effort. In no case does such identification imply recommendation or endorsement of products by NASA, nor does it imply that the materials and products are the only ones or the best ones available for this purpose. In many cases equivalent materials and products are available and would probably produce equivalent results

Proceedings of the Resolve Workshop 2006

The aim of the RESOLVE Workshop 2006 was to bring together researchers and educators interested in: Refining formal approaches to software engineering, especially component-based systems, and introducing them into the classroom. The workshop served as a forum for participants to present and discuss recent advances, trends, and concerns in these areas, as well as formulate a common understanding of emerging research issues and possible solution paths