4th International Conference on Principles and Practices ... - MADOC

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Figure 3: Screenshot of Kcachegrind tool visualizing percentage of total program runtime spent in each concept Figure 4: Simple webpage visualizing phased behaviour of concept execution trace 35
Figure 5: Investigation of garbage collection activity for different heap sizes We use the _201_compress benchmark from SPEC JVM98 again. Figure 6 shows the start of benchmark execution using the default (adaptive) compilation settings (top) and specifying that the optimizing compiler should be used by default (bottom, -X:aos:initial compiler=opt). In the top execution, the baseline compiler is invoked frequently for a small amount of time each invocation. On the other hand, in the bottom execution, the optimizing compiler is invoked more frequently. It takes a long time on some methods (since it employs expensive analysis techniques). However note that even with the optimizing compiler as default, it is still the case that there are some baseline compiled methods. This is not necessarily intuitive, but it is clear to see from the visualization! Figure 7 shows the same execution profiles, only further on in execution time. The top visualization (default compilation settings) shows that many methods are now (re)compiled using the optimizing compiler. As methods get hot at different times, optimizing compiler execution is scattered across runtime. In the bottom visualization, once all the methods have been compiled with the optimizing compiler, there is generally no need for recompilation. Note that both Figures 6 and 7 demonstrate that the optimizing compiler causes more garbage collection! The compilation system uses the same heap as user applications, and there is intensive memory usage for some optimizing compiler analyses. There are plenty of other investigations to be performed with the Jikes RVM compilation system. In addition, we hope to identify other interesting concepts in Jikes RVM. 5. RELATED WORK Hauswirth et al [13] introduce the discipline of vertical profiling which involves monitoring events at all levels of abstraction (from hardware counters through virtual machine state to user-defined application-specific debugging statistics). Their system is built around Jikes RVM. It is able to correlate events at different abstraction levels in dynamic execution traces. They present some interesting case studies to explain performance anomalies in standard benchmarks. Our work focuses on user-defined high-level concepts, and how source code and dynamic execution traces are partitioned by concepts. Their work relies more on event-based counters at all levels of abstraction in dynamic execution traces. GCspy [18] is an elegant visualization tool also incorporated with Jikes RVM. It is an extremely flexible tool for visualizing heaps and garbage collection behaviour. Our work examines processor utilization by source code concepts, rather than heap utilization by source code mutators. Sefika et al [20] introduce architecture-oriented visualization. They recognise that classes and methods are the base units of instrumentation and visualization, but they state that higher-level aggregates (which we term concepts!) are more likely to be useful. They instrument methods in the memory management system of an experimental operating system. The methods are grouped into architectural units (concepts) and instrumentation is enabled or disabled for each concept. This allows efficient partial instrumentation on a per-concept basis, with a corresponding reduction in the dynamic trace data size. Our instrumentation is better in that it can operate at a finer granularity than methodlevel. However our instrumentation cannot be selectively disabled, other than by re-assigning concepts to reduce the number of concept boundaries. Sevitsky et al [21] describe a tool for analysing performance of Java programs using execution slices. An execution slice is a set of program elements that a user specifies to belong 36
Page 1 and 2: Edited by: Ralf Gitzel, Markus Alek
Page 3 and 4: Message from the Chairs Dear confer
Page 5 and 6: Sam Midkiff, Purdue University (USA
Page 7 and 8: Session F: Novel Uses of Java______
Page 10 and 11: The Project Maxwell Assembler Syste
Page 12 and 13: tomated assembler and disassembler
Page 14 and 15: memory address offset mnemonic argu
Page 16 and 17: 5.2 Instruction Templates The assem
Page 18 and 19: ange for a very short restart/debug
Page 20 and 21: Tatoo: an innovative parser generat
Page 22 and 23: In the grammar file an error termin
Page 24 and 25: Figure 3: Push parsers and lexers L
Page 26 and 27: eturn visit((Expr)p1, param); } R v
Page 28: Session B Program and Performance A
Page 31 and 32: Table 1: Use of interfaces and deco
Page 33 and 34: Table 3: Comparison of the situatio
Page 35 and 36: will trigger the creation of many n
Page 37 and 38: Appendix A 10 9 8 7 6 5 4 3 2 1 0 1
Page 39 and 40: Throughout this paper, we make no a
Page 41: instrumented program and obtained t
Page 45 and 46: to the same category—again, this
Page 47 and 48: Investigating Throughput Degradatio
Page 49 and 50: Figure 1: Apache. Throughput degrad
Page 51 and 52: Minor GC Full GC Workload # of Avg.
Page 53 and 54: Figure 6: Comparing memory and pagi
Page 55 and 56: GenRC on the other hand, allows the
Page 58: Session C Mobile and Distributed Sy
Page 61 and 62: ing a continuous buffer for raw dat
Page 63 and 64: the data arrival speed is more impo
Page 65 and 66: public class StreamingClient { publ
Page 67 and 68: importance of β in our aggregation
Page 69 and 70: Enabling Java Mobile Computing on t
Page 71 and 72: A strongly mobile thread has the ab
Page 73 and 74: a context switch occur. The invoked
Page 75 and 76: above phases. Now, the new stack ha
Page 77 and 78: 5 frames 15 frames 25 frames Pure d
Page 79 and 80: Juxta-Cat: A JXTA-based platform fo
Page 81 and 82: Figure 1: JXTA Architecture. 3. JUX
Page 83 and 84: • Send a discovery query to the p
Page 85 and 86: The best candidate is then the one
Page 87 and 88: Local Hosts=2 Hosts=4 Hosts=8 Hosts
Page 90: Session D Resource and Object Manag
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Enterprise Edition (J2EE). It enabl
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As pictured in Figure 4, JDOSecure
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Methods of a PersistenceManager, th
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Datenmodell abstrahiert user role,
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An Extensible Mechanism for Long-Te
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missing object references in the de
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4.2 Mapping the name spaces of the
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(a) (b) ColorSliderPanel0 color
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8. REFERENCES [1] Abu-Ghazaleh, N.,
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permission by process. In other wor
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The processor then refers to the en
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1: // Protection domain 2: struct p
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Table 3: Frequency of JNI calls tha
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[13] Intel Corporation. IA-32 Intel
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01 try { 02 ... 03 } finally { 04 t
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2. FRAMEWORK The Framework for Unif
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ManagedInputStream ResourceGroup Ma
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18. throw ‡ 1. release 17. cleanu
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3. FUTURE WORK The ability to split
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124
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UML sequence diagrams are among the
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diagrams, and behavioral (dynamic)
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the official scripting language for
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Apache's XML Graphics Project. A cu
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Java Debug Interface (JDI). In Revi
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1.3 JML 1.3.1 Overview JML, the Jav
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The Usage of CANAPA is fairly strai
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*@non_null@*/ String str = attribut
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142
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parallel and distributed versions o
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RingElem CextendsRingElem GenPolyno
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RingElem +isZERO():bolean CextendsR
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class constructors with the actual
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plemented via a distributed hash ta
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which are common nowadays. The reus
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Derivative Contract Component Repos
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stepwise execution create Derivativ
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5.4.1 Structural Constraints Struct
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into the conceptual foundation of n
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different implementation and is mor
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the service from the root. It allow
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model: 1. Servlet [6] adapter compo
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y possibly different service, where
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or the fact that widgets extend ser
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174
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The idea of Java 5.0 type inference
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Source := (class | interface)∗ cl
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5. IMPLEMENTATION In order to prese
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Infinite Streams in Java Dominik Gr
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} private static LinkedStream fibon
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of the f stream in order to compute
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Interaction among Objects via Roles
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(a) (b) (c) (d) (e) Figure 1: The p
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class Printer { private int totalPr
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Experiences of using the Dagstuhl M
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Metric Definition Java .class files
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scription of the metric values. Non
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Figure 1: Results from the J-vestig
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an error is subsequently generated
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3. BASIC TERMINOLOGY As object-orie
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• subtyping • (implementation)
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Improving the Quality of Programmin
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Results of online checks (shortened
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212
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214
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Experiences With Hierarchy-Based Co
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Sub View Child DataField 0..n Ke
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Figure 8 - Actual State Charts elem
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associations, which may result in r
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M3PS: A Multi-Platform P2P System B
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In following, we will explain in de
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Figure 10. JDP in Windows XP. Figur
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Mapping Clouds of SOA- and Business
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the technical SOA events (from the
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component and the business process
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Figure 13. “Business Value of Dat
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Solaris of SUN. This platform provi
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status change of an application is
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coming up, is presently discussing
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ISBN: 3-939352-05-5 ISBN: 978-3-939
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