Bytecode instrumentation is a valuable technique for transparently enhancing virtual execution environments for purposes such as monitoring or profiling. Current approaches to bytecode instrumentation either exclude some methods from instrumentation, severely restrict the ways certain methods may be instrumented, or require the use of native code. In this paper we compare different approaches to bytecode instrumentation in Java and come up with a novel instrumentation framework that goes beyond the aforementioned limitations. We evaluate our approach with an instrumentation for profiling which generates calling context trees of various platform-independent dynamic metrics.

Service matchmaking and composition has recently drawn increasing attention in the research community. Most existing algorithms construct chains of services based on exact matches of input/output types. However, this does not work when the available services only cover a part of the range of the input type. We present an algorithm that also allows partial matches and composes them using switches that decide on the required service at runtime based on the actual data type. We report experiments on randomly generated composition problems that show that using partial matches can decrease the failure rate of the integration algorithm using only complete matches by up to 7 times with no increase in the number of directory accesses required. This shows that composition with partial matches is an essential and useful element of web service composition. 1

Service-level agreements (SLAs) establish a contract between service providers and clients concerning Quality of Service (QoS) parameters. Without proper penalties, service providers have strong incentives to deviate from the advertised QoS, causing losses to the clients. Reliable QoS monitoring (and proper penalties computed on the basis of delivered QoS) are therefore essential for the trustworthiness of a service-oriented environment. In this paper, we present a novel QoS monitoring mechanism based on quality ratings from the clients. A reputation mechanism collects the ratings and computes the actual quality delivered to the clients. The mechanism provides incentives for the clients to report honestly, and pays special attention to minimizing cost and overhead.

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SUMMARYVirtual execution environments, such as the Java Virtual Machine, promote platform-independent software development. However, when it comes to analyzing algorithm complexity and performance bottlenecks, available tools focus on platform-specific metrics, such as e.g. the CPU time consumption on a particular system. Other drawbacks of many prevailing profiling tools are high overhead, significant measurement perturbation, as well as reduced portability of profiling tools, which are often implemented in platformdependent native code. This article presents a novel profiling approach, which is entirely based on program transformation techniques, in order to build a profiling data structure that provides calling-contextsensitive program execution statistics. We explore the use of platform-independent profiling metrics, in order to make the instrumentation entirely portable and to generate reproducible profiles. We implemented these ideas within a Java-based profiling tool called JP. A significant novelty is that this tool achieves complete bytecode coverage, by statically instrumenting the core runtime libraries, and dynamically instrumenting the rest of the code. JP provides a small and flexible API to write customized profiling agents in pure Java, which are periodically activated to process the collected profiling information. Performance measurements point out that, despite the presence of dynamic instrumentation, JP causes significantly less overhead than a prevailing tool for the profiling of Java code.

Modern IDEs such as Eclipse offer static views of the source code, but such views ignore information about the run-time behavior of software systems. Since typical object-oriented systems make heavy use of polymorphism and dynamic binding, static views will miss key information about the run-time architecture. In this paper we show by means of a controlled experiment with 30 professional developers that for typical software maintenance tasks integrating dynamic information into the Eclipse IDE yields a significant 17.5% decrease of time spent while significantly increasing the correctness of the solutions by 33.5%. Furthermore, we describe several enhancements to the Eclipse IDE that integrate static and dynamic information, with the goal of better supporting typical software maintenance activities. We elaborate on a case study which further highlights the usefulness of dynamic information for performance optimizations. We also report on several important efficiency improvements to our dynamic information collection framework, and we present benchmarks evaluating the overhead of our approach.

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