The effectiveness of garbage collectors and leak detectors in identifying dead objects depends on the accuracy of their reachability traversal. Accuracy has two orthogonal dimensions: (i) whether the reachability traversal can distinguish between pointers and nonpointers (type accuracy), and (ii) whether the reachability traversal can identify memory locations that will be dereferenced in the future (liveness accuracy). This article presents an experimental study of the importance of type and liveness accuracy for reachability traversals. We show that liveness accuracy reduces the reachable heap size by up to 62% for our benchmark programs. However, the simpler liveness schemes (e.g., intraprocedural analysis of local variables) are largely ineffective for our benchmark runs: one must analyze global variables using interprocedural analysis to obtain significant benefits. Type accuracy has an insignificant impact on a garbage collector s ability to find unreachable objects in our benchmark runs. We report results for programs written in C, C , and Eiffel.

We describe the design, implementation, and use of a machinecertified framework for correct compilation and execution of programs in garbage-collected languages. Our framework extends Leroy’s Coq-certified Compcert compiler and Cminor intermediate language. We add: (i) a new intermediate language, GCminor, that includes primitives for allocating memory in a garbage-collected heap and for specifying GC roots; (ii) a precise, low-level specification for a Cminor library for garbage collection; and (iii) a proven semantics-preserving translation from GCminor to Cminor plus the GC library. GCminor neatly encapsulates the interface between mutator and collector code, while remaining simple and flexible enough to be used with a wide variety of source languages and collector styles. Front ends targeting GCminor can be implemented using any compiler technology and any desired degree of verification, including full semantics preservation, type preservation, or informal trust. As an example application of our framework, we describe a compiler for Haskell that translates the Glasgow Haskell Compiler’s Core intermediate language to GCminor. To support a simple but useful memory safety argument for this compiler, the front end uses a novel combination of type preservation and runtime checks, which is of independent interest.

Implementing a concurrent programming language such as Java by the means of a translator to an existing language is attractive as it provides portability over all platforms supported by the host language and reduces development time – as many low-level tasks can be delegated to the host compiler. The C and C++ programming languages are popular choices for many language implementations due to the availability of efficient compilers on a wide range of platforms. For garbage-collected languages, however, they are not a perfect match as no support is provided for accurately discovering pointers to heap-allocated data on thread stacks. We evaluate several previously published techniques, and propose a new mechanism, lazy pointer stacks, for performing accurate garbage collection in such uncooperative environments. We implemented the new technique in the Ovm Java virtual machine with our own Java-to-C/C++ compiler using GCC as a back-end compiler. Our extensive experimental results confirm that lazy pointer stacks outperform existing approaches: we provide a speed-up of 4.5 % over Henderson’s accurate collector with a 17 % increase in code size. Accurate collection is essential in the context of real-time systems, we thus validate our approach with the implementation of a real-time concurrent garbage collection algorithm. 1.

Real-time Java is quickly emerging as a platform for building safety-critical embedded systems. The real-time variants of Java, including [8, 15], are attractive alternatives to Ada and C since they provide a cleaner, simpler, and safer programming model. Unfortunately, current real-time Java implementations have trouble scaling down to very hard real-time embedded settings, where memory is scarce and processing power is limited. In this paper, we describe the architecture of the Fiji VM, which enables vanilla Java applications to run in very hard environments, including booting on bare hardware with only very rudimentary operating system support. We also show that our minimalistic approach delivers comparable performance to that of server-class production Java Virtual Machine implementations. 1.

committee and by majority vote has been found to be satisfactory.

While managed languages such as C # and Java have become quite popular in enterprise computing, they are still considered unsuitable for hard real-time systems. In particular, the presence of garbage collection has been a sore point for their acceptance for low-level system programming tasks. Realtime extensions to these languages have the dubious distinction of, at the same time, eschewing the benefits of highlevel programming and failing to offer competitive performance. The goal of our research is to explore the limitations of high-level managed languages for real-time systems programming. To this end we target a real-world embedded platform, the LEON3 architecture running the RTEMS real-time operating system, and demonstrate the feasibility of writing garbage collected code in critical parts of embedded systems. We show that Java with a concurrent, real-time garbage collector, can have throughput close to that of C programs and comes within 10 % in the worst observed case on realistic benchmark. We provide a detailed breakdown of the costs of Java features and their execution times and compare to real-time and throughput-optimized commercial Java virtual machines.

Applying region-based memory management (RBMM) to logic programming languages poses a special challenge: backtracking can require regions removed during forward execution to be “resurrected”, and any memory allocated during a computation that has been backtracked over must be recovered promptly, without waiting for the regions involved to come to the end of their life. In this paper, we describe how we implemented runtime support for RBMM in the logic programming language Mercury, whose specialized implementation of the language constructs involved in backtracking required equally specialized support. Our benchmark Mercury programs run about 25 % faster on average with RBMM than with the usual Boehm garbage collector, and for some programs, RBMM achieves optimal memory consumption. D.3.4 [Processors]: Compil-

Region-based memory management is a technique to do compiletime memory management based on the idea of dividing the heap memory into different regions such that, at runtime, memory can be reclaimed automatically by destroying regions in their entirety. This report contains a static region analysis for the logic programming language Mercury. We define region points-to graphs, which represent the locations of terms and the sharing among them, to model the partitioning of the memory used by a program into separate regions. The static analysis starts with a region points-to analysis that determines the different regions in the program. We then compute the liveness of the regions by a region liveness analysis. Finally, a program transformation adds sufficient region annotations to the program for region support. In this report we also give the correctness proofs for the analysis, so that the safety of memory accesses can be guaranteed. The implementation of the runtime support for region-based memory management in the Mercury compiler will be described in a second report.