Auswahl der wissenschaftlichen Literatur zum Thema „Java bytecode“

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Zeitschriftenartikel zum Thema "Java bytecode"

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Gal, Andreas, Christian W. Probst und Michael Franz. „Integrated Java Bytecode Verification“. Electronic Notes in Theoretical Computer Science 131 (Mai 2005): 27–38. http://dx.doi.org/10.1016/j.entcs.2005.01.020.

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Kim, Ki-Tae, Je-Min Kim und Weon-Hee Yoo. „Implementation of Java Bytecode Framework“. Journal of the Korea Contents Association 10, Nr. 3 (28.03.2010): 122–31. http://dx.doi.org/10.5392/jkca.2010.10.3.122.

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Reynolds, Mark C. „Modeling the Java Bytecode Verifier“. Science of Computer Programming 78, Nr. 3 (März 2013): 327–42. http://dx.doi.org/10.1016/j.scico.2011.03.008.

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Bertelsen, Peter. „Dynamic semantics of Java bytecode“. Future Generation Computer Systems 16, Nr. 7 (Mai 2000): 841–50. http://dx.doi.org/10.1016/s0167-739x(99)00094-1.

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Cook, J. J. „Reverse Execution of Java Bytecode“. Computer Journal 45, Nr. 6 (01.06.2002): 608–19. http://dx.doi.org/10.1093/comjnl/45.6.608.

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Zhao, Jian-jun. „Static analysis of Java bytecode“. Wuhan University Journal of Natural Sciences 6, Nr. 1-2 (März 2001): 383–90. http://dx.doi.org/10.1007/bf03160273.

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Dobravec, Tomaž. „JAVA BYTECODE INSTRUCTION USAGE COUNTING WITH ALGATOR“. Acta Electrotechnica et Informatica 18, Nr. 4 (05.01.2018): 17–25. http://dx.doi.org/10.15546/aeei-2018-0028.

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Wang, Tao, und Abhik Roychoudhury. „Dynamic slicing on Java bytecode traces“. ACM Transactions on Programming Languages and Systems 30, Nr. 2 (März 2008): 1–49. http://dx.doi.org/10.1145/1330017.1330021.

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Chan, Jien-Tsai, und Wuu Yang. „Advanced obfuscation techniques for Java bytecode“. Journal of Systems and Software 71, Nr. 1-2 (April 2004): 1–10. http://dx.doi.org/10.1016/s0164-1212(02)00066-3.

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Ghosh, Sudipto, und John L. Kelly. „Bytecode fault injection for Java software“. Journal of Systems and Software 81, Nr. 11 (November 2008): 2034–43. http://dx.doi.org/10.1016/j.jss.2008.02.047.

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Dissertationen zum Thema "Java bytecode"

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Batchelder, Michael Robert. „Java bytecode obfuscation“. Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=18300.

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Programs written for machine execution will always be susceptible to information theft. This information can include trademarked algorithms, data embedded in the program, or even data the program accesses. As technology advances computer scientists are building more and more powerful tools for reverse-engineering such as decompilers.The Java programming language is particularly open to reverse-engineering attacks because of its well-defined, open, and portable binary format. We examine one area of better-securing the intellectual property of a Java program; obfuscation. Obfuscation of a program involves transforming the code of the program into a more complex, but semantically equivalent representation. This can include the addition of confusing control flow, the removal of certain information embedded in the program which is not explicitly required for execution, or the cloaking of data.Obfuscation is one of the only techniques available other than cryptological options. While many approaches to obfuscation are ultimately reversible, it nevertheless seriously hinders those attempting to steal information by increasing the computing time and power required by software to reverse-engineer the program and also severely increases the complexity of any source code that is recovered by the reverse-engineering.In this thesis we present a number of obfuscating transformations implemented within a new automatic tool we name the Java Bytecode Obfuscator (JBCO). We present empirical measures of the performance costs of these transformations in terms of execution speed and program size. Complexity measurements that gauge the effectiveness of the obfuscations are also given. Finally, we review the feasibility of each transformation by looking at source code generated from obfuscated bytecode by various decompilers.
Les programmes écrits pour l'exécution d'ordinateur seront toujours susceptibles au vol d'information. Cette information peut inclure des algorithmes de marque de commerce, des données incluses dans le programme, ou même des données concernant les accès de programme. Suivant les avancées technologiques, les informaticiens construisent des outils de plus en plus puissants pour l'ingénierie inverse telle que le décompilateur. Le langage de programmation de Java est particulièrement ouvert aux attaques de l'ingénierie inverse en raison de son format binaire bien défini, ouvert, et portatif. Nous recherches portent sur un domaine permettant de mieux sécuriser fixer la propriété intellectuelle des programmes en Java; obscurcissement. L'obscurcissement d'un programme implique de transformer le code du programme en une représentation plus complexe mais sémantiquement équivalente. Ceci peut inclure l'addition de l'écoulement embrouillant de commande, de la supression de certaines informations incluses dans les programmes dont l'exécution n'est pas spécifiquement exigée, ou de la dissimulation des données. Excepté les techniques cryptologique s, l'obscurcissement est l'une des seules techniques disponibles. Même si beaucoup de stratégies de l'obscurissment sont finalement réversibles, il gêne sérieusement ceux qui essayent de voler l'information en augmentant la durée de calcul et la puissance exigées par les logicels d'ingénierie inverse et augmente considérablement la complexité de n'importe quel code source récupere par cette technique. Dans cette thèse nous présentons un certain nombre de transformations d'obscurcissement mises en application dans un outil automatique que nous appelons le Java Bytecode Obfuscator (JBCO). Nous présentons des mesures empiriques des coûts d'exécution de ces transformations en termes de vitesse d'exécution et taille de programme. Des mesures de complexité qui mesurent l'efficacité des obscurc
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Klein, Gerwin. „Verified Java bytecode verification“. [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=967128749.

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Shah, Rahul Arvind. „Vulnerability assessment of Java bytecode“. Auburn, Ala., 2005. http://repo.lib.auburn.edu/Send%2012-16-07/SHAH_RAHUL_44.pdf.

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Ochani, Vidit. „Java bytecode to Pilar translator“. Kansas State University, 2013. http://hdl.handle.net/2097/16987.

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Master of Science
Department of Computing and Information Sciences
Robby
Software technology is the pivot around which all modern industries revolve. It is not surprising that industries of diverse nature such as finance, business, engineering, medicine, defense, etc. have assimilated sophisticated software in every step of functioning. Subsequently, with larger reach of application, software technology has evolved intricately; thereby thwarting the desirable testing of software. Companies are investing millions of dollars in manual and automated testing, however, software bugs continue to persist. It is well known that even a trivial bug can ultimately cost the company millions of dollars. Therefore, we need smarter tools to help eliminate bugs. Sireum is a research project to develop a software analysis platform that incorporates various tools and techniques. Symbolic execution, model checking, deductive reasoning and control flow graph are few examples of the aforementioned techniques. The Sireum platform is based on previous projects like the Indus static analysis framework, the Bogor model checking framework and the Bandera Java model checker. It uses the Pilar language as intermediate representation. Any language which can be translated to Pilar can be analyzed by Sireum. There exists translator for Spark - a verifiable subset of Ada for building high-integrity systems. In this report, we are presenting one such translator for Java Bytecode - A frontend which can generate Pilar from Java intermediate representation. The translator emulates the working of the Java Virtual Machine(JVM), by simulating a stack-based virtual machine. It will help us analyse JVM based softwares, such as, mobile applications for Android. We also evaluate and report statistics on the efficiency and speed of translation.
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Doyon, Stéphane. „On the security of Java, the Java bytecode verifier“. Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0004/MQ41890.pdf.

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Vallee-Rai, Raja. „Soot : a java bytecode optimization framework“. Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=30836.

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Java provides many attractive features such as platform independence, execution safety, garbage collection and object orientation. These features facilitate application development but are expensive to support; applications written in Java are often much slower than their counterparts written in C or C++. To use these features without having to pay a great performance penalty, sophisticated optimizations and runtime systems are required.
We present SOOT, a framework for optimizing Java bytecode. The framework is implemented in Java and supports three intermediate representations for representing Java bytecode: BAF, a streamlined representation of bytecode which is simple to manipulate; JIMPLE, a typed 3-address intermediate representation suitable for optimization; and GRIMP an aggregated version of JIMPLE suitable for decompilation. SOOT also contains a set of transformations between these intermediate representations, and an application programming interface (API) is provided to write optimizations and analyses on Java bytecode in these forms.
In order to demonstrate the usefulness of the framework, we have implemented intraprocedural and whole program optimizations. To show that whole program bytecode optimization can give performance improvements, we provide experimental results for 10 large benchmarks, including 8 SPECjvm98 benchmarks running on JDK 1.2. These results show a speedup of up to 38%.
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Pinto, Camara Tarcisio. „Otimização bytecode Java na plataforma J2ME“. Universidade Federal de Pernambuco, 2004. https://repositorio.ufpe.br/handle/123456789/2567.

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Made available in DSpace on 2014-06-12T15:59:18Z (GMT). No. of bitstreams: 2 arquivo5023_1.pdf: 1253051 bytes, checksum: 0bb4a72739c259711e027e24c5f3659f (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2004
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Aplicações para os dispositivos móveis, como telefones celulares e pagers, implementadas em J2ME (Java 2 Micro Edition) são desenvolvidas sob severas restrições de tamanho e desempenho do código. A indústria tem adotado ferramentas de otimização, como obfuscators e shrinkers, que aplicam otimizações de programa inteiro (Whole Program Optimizations) considerando que o código gerado não será estendido ou usado por outras aplicações. Infelizmente, os desenvolvedores freqüentemente não conhecem suficientemente nestas ferramentas e continuam sacrificando a qualidade do código na tentativa de otimizar suas aplicações. Este trabalho apresenta um estudo original identificando a efetividade das otimizações mais comuns nos obfuscators. Este estudo mostra também que a otimização de Method Inlining, conhecida pelos benefícios de desempenho, tem sido negligenciada por estas ferramentas por normalmente esperarse que ela tenha efeito negativo sobre o tamanho de código. Assim, este trabalho contribui com uma implementação de method inlining entre classes e fundada no princípio de otimização de programa inteiro, capaz de melhorar tanto o tamanho do código como o desempenho da aplicação, ao remover cerca de 50% dos métodos alcançáveis. Finalmente, na tentativa de ajudar os desenvolvedores a tirar o melhor proveito destas ferramentas, o estudo inclui também um guia de boas práticas de programação considerando as otimizações implementadas pelos obfuscators
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Modesto, Francisco. „Development of a Java Bytecode Front-End“. Thesis, Växjö University, School of Mathematics and Systems Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-6210.

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The VizzAnalyzer is a powerful software analysis tool. It is able to extract information from various software representations like source code  but also other specifications like UML. The extracted information is input to static analysis of these software projects. One programming language the VizzAnalyzer can extract information from is Java source code.

Analyzing the source code is sufficient for most of the analysis. But, sometimes it is necessary to analyze compiled classes either because the program is only available in byte-code, or the scope of analysis includes libraries that exist usually in binary form. Thus, being able to extract information from Java byte-code is paramount for the extension of some analyses, e.g., studying the dependecy structure of a project and the libraries it uses.

Currently, the VizzAnalyzer does not feature information extraction from Java byte-code. To allow, e.g., the analysis of the project dependency structure, we extend the VizzAnalyzer tool with a bytecode front-end that will allow the extraction of information from Java bytecode.

This thesis describes the design and implementation of the bytecode front-end. After we implemented and integrated the new front-end with the VizzAnalyzer, we are now able to perform new analyses that work on data extracted from both, source- and bytecode.

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Zabel, Martin. „Effiziente Mehrkernarchitektur für eingebettete Java-Bytecode-Prozessoren“. Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-84156.

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Die Java-Plattform bietet viele Vorteile für die schnelle Entwicklung komplexer Software. Für die Ausführung des Java-Bytecodes auf eingebetteten Systemen eignen sich insbesondere Java-(Bytecode)-Prozessoren, die den Java-Bytecode als nativen Befehlssatz unterstützen. Die vorliegende Arbeit untersucht detailliert die Gestaltung einer Mehrkernarchitektur für Java-Prozessoren zur effizienten Nutzung der auf Thread-Ebene ohnehin vorhandenen Parallelität eines Java-Programms. Für die Funktionalitäts- und Leistungsbewertung eines Prototyps wird eine eigene Trace-Architektur eingesetzt. Es wird eine hohe Leistungssteigerung bei nur geringem zusätzlichem Hardwareaufwand erzielt sowie eine höhere Leistung als bekannte alternative Ansätze erreicht.
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Zabel, Martin, und Rainer G. Spallek. „SHAP — Scalable Multi-Core Java Bytecode Processor“. Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-97619.

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Abstract This paper introduces a new embedded Java multi-core architecture which shows a significantly better performance for a large number of cores than the related projects JopCMP and jamuth IP multi-core. The cores gain fast access to the shared heap by a fullduplex bus with pipelined transactions. Each core is equipped with local on-chip memory for the Java operand stack and the method cache to further reduce the memory bandwidth requirements. As opposed to the related projects, synchronization is supported on a per object-basis instead of a single lock. Load balancing is implemented in Java and requires no additional hardware. The multi-port memory manager includes an exact and fully concurrent garbage collector for automatic memory management. The design can be synthesized for a variable number of parallel cores and shows a linear increase in chip-space. Three different benchmarks demonstrate the very good scalability of our architecture. Due to limited chip-space on our evaluation platform, the core count could not be increased further than 8. But, we expect a smooth performance decrease.
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Bücher zum Thema "Java bytecode"

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Lew, Dion. BCIR: A framework for the representation and manipulation of the Java bytecode. 2001, 2001.

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Buchteile zum Thema "Java bytecode"

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Stärk, Robert F., Joachim Schmid und Egon Börger. „Bytecode type assignments“. In Java and the Java Virtual Machine, 223–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59495-3_16.

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Czarnik, Patryk, Jacek Chrząszcz und Aleksy Schubert. „A Java Bytecode Formalisation“. In Lecture Notes in Computer Science, 135–54. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03592-1_8.

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Fischer, Robert. „Lambdas in Java Bytecode“. In Java Closures and Lambda, 139–52. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4302-5999-2_8.

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Albert, Elvira, Puri Arenas, Michael Codish, Samir Genaim, Germán Puebla und Damiano Zanardini. „Termination Analysis of Java Bytecode“. In Lecture Notes in Computer Science, 2–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-68863-1_2.

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Brockschmidt, Marc, Carsten Otto, Christian von Essen und Jürgen Giesl. „Termination Graphs for Java Bytecode“. In Verification, Induction, Termination Analysis, 17–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17172-7_2.

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Laneve, Cosimo, und Abel Garcia. „Deadlock Detection of Java Bytecode“. In Logic-Based Program Synthesis and Transformation, 37–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94460-9_3.

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Leroy, Xavier. „Java Bytecode Verification: An Overview“. In Computer Aided Verification, 265–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44585-4_26.

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Albert, E., P. Arenas, S. Genaim, G. Puebla und D. Zanardini. „Cost Analysis of Java Bytecode“. In Programming Languages and Systems, 157–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71316-6_12.

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Tanter, Éric, Marc Ségura-Devillechaise, Jacques Noyé und José Piquer. „Altering Java Semantics via Bytecode Manipulation“. In Generative Programming and Component Engineering, 283–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45821-2_18.

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Genaim, Samir, und Fausto Spoto. „Information Flow Analysis for Java Bytecode“. In Lecture Notes in Computer Science, 346–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-30579-8_23.

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Konferenzberichte zum Thema "Java bytecode"

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Barbuti, Roberto, und Stefano Cataudella. „Java bytecode verification on Java cards“. In the 2004 ACM symposium. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/967900.967991.

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Binder, Walter, Jarle Hulaas und Philippe Moret. „Advanced Java bytecode instrumentation“. In the 5th international symposium. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1294325.1294344.

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Burdy, Lilian, und Mariela Pavlova. „Java bytecode specification and verification“. In the 2006 ACM symposium. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1141277.1141708.

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Lance, Don, Roland H. Untch und Nancy J. Wahl. „Bytecode-based Java program analysis“. In the 37th annual Southeast regional conference (CD-ROM). New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/306363.306382.

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Ribeiro, José Carlos Bregieiro, Francisco Fernández de Vega und Mário Zenha-Rela. „Using Dynamic Analysis Of Java Bytecode For Evolutionary Object-Oriented Unit Testing“. In Workshop de Testes e Tolerância a Falhas. Sociedade Brasileira de Computação - SBC, 2007. http://dx.doi.org/10.5753/wtf.2007.23245.

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The focus of this paper is on presenting a methodology for generating and optimizing test data by employing evolutionary search techniques, with basis on the information provided by the analysis and interpretation of Java bytecode and on the dynamic execution of the instrumented test object. The main reason to work at the bytecode level is that even when the source code is unavailable, structural testing requirements can still be derived and used to assess the quality of a given test set and to guide the evolutionary search towards reaching specific test goals. Java bytecode retains enough high-level information about the original source code for an underlying model for program representation to be built. The observations required to select or generate test data are obtained by employing dynamic analysis techniques – i.e. by instrumenting, tracing and analysing Java bytecode.
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„JSIMIL - A Java Bytecode Clone Detector“. In 5th International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0003013403330336.

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Zambon, Andrea. „Aucsmith-Like Obfuscation of Java Bytecode“. In 2012 12th IEEE Working Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2012. http://dx.doi.org/10.1109/scam.2012.14.

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Octeau, Damien, Somesh Jha und Patrick McDaniel. „Retargeting Android applications to Java bytecode“. In the ACM SIGSOFT 20th International Symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2393596.2393600.

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Santone, Antonella, und Gigliola Vaglini. „Local model checking of Java bytecode“. In the 14th international conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/568760.568827.

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Albert, Elvira, Samir Genaim und Miguel Gomez-Zamalloa. „Heap space analysis for java bytecode“. In the 6th international symposium. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1296907.1296922.

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