Browsing by Autor "Philippe Moret"

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ADVANCED AND RAPID DEVELOPMENT OF DYNAMIC ANALYSIS TOOLS FOR JAVA
(2012) Alex Villazón; Danilo Ansaloni; Philippe Moret
Low-level bytecode instrumentation techniques are widely used in many software-engineering tools for the Java Virtual Machine (JVM), that perform some form of dynamic program analysis, such as profilers or debuggers. While program manipulation at the bytecode level is very flexible, because the possible bytecode transformations are not restricted, tool development based on this technique is tedious and error-prone. As a promising alternative, the specification of bytecode instrumentation at a higher level using aspect-oriented programming (AOP) can reduce tool development time and cost. Unfortunately, prevailing AOP frameworks lack some features that are essential for certain dynamic analyses. In this article, we focus on three common shortcomings in AOP frameworks with respect to the development of aspect-based tools - (1) the lack of mechanisms for passing data between woven advices in local variables, (2) the support for user-defined static analyses at weaving time, and (3) the absence of pointcuts at the level of individual basic blocks of code. We propose @J, an annotation-based AOP language and weaver that integrates support for these three features. The benefits of the proposed features are illustrated with concrete examples.
ADVANCED AND RAPID DEVELOPMENT OF DYNAMIC ANALYSIS TOOLS FOR JAVA
(2010) Alex Villazón; Danilo Ansaloni; Philippe Moret
Low-level bytecode instrumentation techniques are widely used in many software-engineering tools for the Java Virtual Machine (JVM), that perform some form of dynamic program analysis, such as profilers or debuggers. While program manipulation at the bytecode level is very flexible, because the possible bytecode transformations are not restricted, tool development based on this technique is tedious and error-prone. As a promising alternative, the specification of bytecode instrumentation at a higher level using aspect-oriented programming (AOP) can reduce tool development time and cost. Unfortunately, prevailing AOP frameworks lack some features that are essential for certain dynamic analyses. In this article, we focus on three common shortcomings in AOP frameworks with respect to the development of aspect-based tools - (1) the lack of mechanisms for passing data between woven advices in local variables, (2) the support for user-defined static analyses at weaving time, and (3) the absence of pointcuts at the level of individual basic blocks of code. We propose @J, an annotation-based AOP language and weaver that integrates support for these three features. The benefits of the proposed features are illustrated with concrete examples.
Exploiting Dynamic Information in IDEs Improves Speed and Correctness of Software Maintenance Tasks
(IEEE Computer Society, 2012) David Röthlisberger; Marcel Harry; Walter Binder; Philippe Moret; Danilo Ansaloni; Alex Villazón; Oscar Nierstrasz
Modern IDEs such as Eclipse offer static views of the source code, but such views ignore information about the runtime 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 runtime architecture. In this paper, we present an approach to gather and integrate dynamic information in the Eclipse IDE with the goal of better supporting typical software maintenance activities. By means of a controlled experiment with 30 professional developers, we show that for typical software maintenance tasks, integrating dynamic information into the Eclipse IDE yields a significant 17.5 percent decrease of time spent while significantly increasing the correctness of the solutions by 33.5 percent. We also provide a comprehensive performance evaluation of our approach.
Flexible and efficient profiling with aspect‐oriented programming
(Wiley, 2011) Walter Binder; Danilo Ansaloni; Alex Villazón; Philippe Moret
Abstract Many profilers for virtual execution environments, such as the Java virtual machine (JVM), are implemented with low‐level bytecode instrumentation techniques, which is tedious, error‐prone, and complicates maintenance and extension of the tools. In order to reduce the development time and cost, we promote building profilers for the JVM using high‐level aspect‐oriented programming (AOP). We show that the use of aspects yields concise profilers that are easy to develop, extend, and maintain, because low‐level instrumentation details are hidden from the tool developer. In order to build efficient profilers, we introduce inter‐advice communication, an extension to common AOP languages that enables efficient data passing between advices that are woven into the same method using local variables. We illustrate our approach with two case studies. First, we show that an existing, instrumentation‐based tool for listener latency profiling can be easily recast as an aspect. Second, we present an aspect for comprehensive calling context profiling. In order to reduce profiling overhead, our aspect parallelizes application execution and profile creation, resulting in a speedup of 110% on a machine with more than two cores, compared with a primitive, non‐parallel approach. Copyright © 2011 John Wiley & Sons, Ltd.
Visualizing and exploring profiles with calling context ring charts
(Wiley, 2010) Philippe Moret; Walter Binder; Alex Villazón; Danilo Ansaloni; Abbas Heydarnoori
Abstract Calling context profiling is an important technique for analyzing the performance of object‐oriented software with complex inter‐procedural control flow. The Calling Context Tree (CCT) is a common data structure that stores dynamic metrics, such as CPU time, separately for each calling context. As CCTs may comprise millions of nodes, there is a need for a condensed visualization that eases the localization of performance bottlenecks. In this article, we discuss Calling Context Ring Charts ( CCRCs ), a compact visualization for CCTs, where callee methods are represented in ring segments surrounding the caller's ring segment. In order to reveal hot methods, their callers, and callees, the ring segments can be sized according to a chosen dynamic metric. We describe two case studies where CCRCs help us to detect and fix performance problems in applications. A performance evaluation also confirms that our implementation can efficiently handle large CCTs. Copyright © 2010 John Wiley & Sons, Ltd.