6,261 research outputs found
Debugging Native Extensions of Dynamic Languages
Many dynamic programming languages such as Ruby and Python enable developers
to use so called native extensions, code implemented in typically statically
compiled languages like C and C++. However, debuggers for these dynamic
languages usually lack support for also debugging these native extensions.
GraalVM can execute programs implemented in various dynamic programming
languages and, by using the LLVM-IR interpreter Sulong, also their native
extensions. We added support for source-level debugging to Sulong based on
GraalVM's debugging framework by associating run-time debug information from
the LLVM-IR level to the original program code. As a result, developers can now
use GraalVM to debug source code written in multiple LLVM-based programming
languages as well as programs implemented in various dynamic languages that
invoke it in a common debugger front-end.Comment: 7 pages, 7 figures, accepted at 15th International Conference on
Managed Languages & Runtimes (ManLang'18
Developing a Generic Debugger for Advanced-Dispatching Languages
Programming-language research has introduced a considerable number of advanced-dispatching mechanisms in order to improve modularity. Advanced-dispatching mechanisms allow changing the behavior of a function without modifying their call sites and thus make the local behavior of code less comprehensible. Debuggers are tools, thus needed, which can help a developer to comprehend program behavior but current debuggers do not provide inspection of advanced-\ud
dispatching-related language constructs. In this paper, we present a debugger which extends a traditional Java debugger with the ability of debugging an advanced-dispatching language constructs and a user interface for inspecting this
Dynamic and Transparent Analysis of Commodity Production Systems
We propose a framework that provides a programming interface to perform
complex dynamic system-level analyses of deployed production systems. By
leveraging hardware support for virtualization available nowadays on all
commodity machines, our framework is completely transparent to the system under
analysis and it guarantees isolation of the analysis tools running on its top.
Thus, the internals of the kernel of the running system needs not to be
modified and the whole platform runs unaware of the framework. Moreover, errors
in the analysis tools do not affect the running system and the framework. This
is accomplished by installing a minimalistic virtual machine monitor and
migrating the system, as it runs, into a virtual machine. In order to
demonstrate the potentials of our framework we developed an interactive kernel
debugger, nicknamed HyperDbg. HyperDbg can be used to debug any critical kernel
component, and even to single step the execution of exception and interrupt
handlers.Comment: 10 pages, To appear in the 25th IEEE/ACM International Conference on
Automated Software Engineering, Antwerp, Belgium, 20-24 September 201
A Simulator for LLVM Bitcode
In this paper, we introduce an interactive simulator for programs in the form
of LLVM bitcode. The main features of the simulator include precise control
over thread scheduling, automatic checkpoints and reverse stepping, support for
source-level information about functions and variables in C and C++ programs
and structured heap visualisation. Additionally, the simulator is compatible
with DiVM (DIVINE VM) hypercalls, which makes it possible to load, simulate and
analyse counterexamples from an existing model checker
Program development using abstract interpretation (and the ciao system preprocessor)
The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation
as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system librarles), to genérate and simplify run-time tests, and to perform high-level program transformations such as múltiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, non-failure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas
VXA: A Virtual Architecture for Durable Compressed Archives
Data compression algorithms change frequently, and obsolete decoders do not
always run on new hardware and operating systems, threatening the long-term
usability of content archived using those algorithms. Re-encoding content into
new formats is cumbersome, and highly undesirable when lossy compression is
involved. Processor architectures, in contrast, have remained comparatively
stable over recent decades. VXA, an archival storage system designed around
this observation, archives executable decoders along with the encoded content
it stores. VXA decoders run in a specialized virtual machine that implements an
OS-independent execution environment based on the standard x86 architecture.
The VXA virtual machine strictly limits access to host system services, making
decoders safe to run even if an archive contains malicious code. VXA's adoption
of a "native" processor architecture instead of type-safe language technology
allows reuse of existing "hand-optimized" decoders in C and assembly language,
and permits decoders access to performance-enhancing architecture features such
as vector processing instructions. The performance cost of VXA's virtualization
is typically less than 15% compared with the same decoders running natively.
The storage cost of archived decoders, typically 30-130KB each, can be
amortized across many archived files sharing the same compression method.Comment: 14 pages, 7 figures, 2 table
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