Producing robust memory manager implementations is a challenging task. Defects in garbage collection algorithms produce subtle effects that are revealed later in program execution as memory corruptions. This problem is exacerbated by the fact that garbage collection algorithms deal with low-level implementation details to be efficient. Finding, reproducing, and debugging such bugs is complex and time-consuming.In this article, we propose to fuzz heaps by generating large sequences of random heap events guided by virtual machine experts. Randomly generated events exercise the garbage collection algorithm with the objective of crashing the virtual machine and finding bugs. Once a bug is found, we use a test case reduction algorithm to find the smaller subset of events that reproduces the issue.We implemented our approach on top of the virtual machine simulator of the Pharo Virtual Machine, to test its sequential stop-the-world generational scavenger. Experts guided our fuzzing toward the ephemeron finalization mechanism, corner allocation cases, and the heap compaction algorithm. Our prototype found 6 bugs: 3 in Pharo’s ephemeron implementation which is not yet in production, 2 bugs in the default compactor which has been in production for 8 years, and 1 bug in the VM simulator used daily by VM developers. We show how such test cases were automatically reduced to trivial sequences that were easy to debug.

J2EE applications tend to be multi-tier and multi-language applications. They rely on the J2EE platform and containers that offer infrastructure and architectural services to ensure distributed, secure, safe, and scalable executions. These mechanisms hide many program dependencies, which helps development but hinders maintenance, evolution, and re-engineering of J2EE applications. In this paper, we study (i) the J2EE specifications to extract a declarative specification of the dependencies that are inherent in the services offered and that are not visible in the user code that uses them. Then, we introduce (ii) a codification of the dependencies into rules, and (iii) a tool that supports the specification of those dependencies and their detection in J2EE applications. We validate our approach and tool on a sample of 10 J2EE applications. We also compare our tool against JRipples, a state-of-the-art tool for change-impact analysis tasks. Results show that our tool adds, on average, 15% more call dependencies, which would have been missed otherwise. On change impact analysis tasks, our tool outperforms JRipples in all 10 applications, especially for the early iterations of change propagation exploration.

Program dependency artifacts such as call graphs help support a number of software engineering tasks such as software mining, program understanding, debugging, feature location, software maintenance and evolution. Java Enterprise Edition (JEE) applications represent a significant part of the recent legacy applications, and we are interested in modernizing them. This modernization involves, among other things, analyzing dependencies between their various components/tiers. JEE applications tend to be multilanguage, rely on JEE container services, and make extensive use of late binding techniques-all of which makes finding such dependencies difficult. In this paper, we describe some of these difficulties and how we addressed them to build a dependency call graph. We developed our tool called DeJEE (Dependencies in JEE) as an Eclipse plug-in. We applied DeJEE on two open-source JEE applications: Java PetStore and JSP Blog. The results show that DeJEE is able to identify different types of JEE dependencies.

Achieving submillisecond response times in a managed language environment such as Java or C# requires overcoming significant challenges. In this article, we propose Reflexes, a programming model and runtime system infrastructure that lets developers seamlessly mix highly responsive tasks and timing-oblivious Java applications. Thus enabling gradual addition of real-time features, to a non-real-time application without having to resort to recoding the real-time parts in a different language such as C or Ada. Experiments with the Reflex prototype implementation show that it is possible to run a real-time task with a period of 45 μs with an accuracy of 99.996% (only 0.001% worse than the corresponding C implementation) in the presence of garbage collection and heavy load ordinary Java threads.

Object-oriented languages involve a threefold tradeoff between runtime efficiency, expressiveness (multiple inheritance), and modularity, i.e. open-world assumption (OWA). Runtime efficiency is conditioned by both the implementation technique and compilation scheme. The former specifies the data structures that support method invocation, attribute access and subtype testing. The latter consists of the production line of an executable from the source code. Many implementation techniques have been proposed and several compilation schemes can be considered from fully global compilation under the closed-world assumption (CWA) to separate compilation with dynamic loading under the OWA, with midway solutions. This article reviews a significant subset of possible combinations and presents a systematic, empirical comparison of their respective efficiencies with all other things being equal. The testbed consists of the Prm compiler that has been designed for this purpose. The considered techniques include C++ subobjects, coloring, perfect hashing, binary tree dispatch and caching. A variety of processors were considered. Qualitatively, these first results confirm the intuitive or theoretical abstract assessments of the tested approaches. As expected, efficiency increases as CWA strengthens. From a quantitative standpoint, the results are the first to precisely compare the efficiency of techniques that are closely associated with specific languages like C++ and Eiffel. They also confirm that perfect hashing should be considered for implementing Java and .Net interfaces.

The stream programming paradigm aims to expose coarsegrained parallelism in applications that must process continuous sequences of events.The appeal of stream programming comes from its conceptual simplicity.A program is a collection of independent filters which communicate by the means of uni-directional data channels.This model lends itself naturally to concurrent and efficient implementations on modern multiprocessors.As the output behavior of filters is determined by the state of their input channels, stream programs have fewer opportunities for the errors (such as data races and deadlocks) that plague shared memory concurrent programming.This paper introduces STREAMFLEX, an extension to Java which marries streams with objects and thus enables to combine, in the same Java virtual machine, stream processing code with traditional object-oriented components.STREAMFLEX targets high-throughput low-latency applications with stringent quality-of-service requirements.To achieve these goals, it must, at the same time, extend and restrict Java.To allow for program optimization and provide latency guarantees, the STREAMFLEX compiler restricts Java by imposing a stricter typing discipline on filters.On the other hand, STREAMFLEX extends the Java virtual machine with real-time capabilities, transactional memory and type-safe region-based allocation.The result is a rich and expressive language that can be implemented efficiently.

Compilers used in industry are mainly based on a separate compilation framework. However, the knowledge of the whole program improves efficiency of object-oriented language compilers, therefore more efficient implementation techniques are based on a global compilation framework.In this paper, we propose a compromise by including three global compilation techniques (type analysis, coloring and binary tree dispatching) in a separate compilation framework. Files are independently compiled into standard binary files with unresolved symbols. The program is build by linking object files: files are gathered and analyzed, some link code is generated then symbols are resolved.