3,631 research outputs found
Darwinian Data Structure Selection
Data structure selection and tuning is laborious but can vastly improve an
application's performance and memory footprint. Some data structures share a
common interface and enjoy multiple implementations. We call them Darwinian
Data Structures (DDS), since we can subject their implementations to survival
of the fittest. We introduce ARTEMIS a multi-objective, cloud-based
search-based optimisation framework that automatically finds optimal, tuned DDS
modulo a test suite, then changes an application to use that DDS. ARTEMIS
achieves substantial performance improvements for \emph{every} project in
Java projects from DaCapo benchmark, popular projects and uniformly
sampled projects from GitHub. For execution time, CPU usage, and memory
consumption, ARTEMIS finds at least one solution that improves \emph{all}
measures for () of the projects. The median improvement across
the best solutions is , , for runtime, memory and CPU
usage.
These aggregate results understate ARTEMIS's potential impact. Some of the
benchmarks it improves are libraries or utility functions. Two examples are
gson, a ubiquitous Java serialization framework, and xalan, Apache's XML
transformation tool. ARTEMIS improves gson by \%, and for
memory, runtime, and CPU; ARTEMIS improves xalan's memory consumption by
\%. \emph{Every} client of these projects will benefit from these
performance improvements.Comment: 11 page
Automated Verification of Practical Garbage Collectors
Garbage collectors are notoriously hard to verify, due to their low-level
interaction with the underlying system and the general difficulty in reasoning
about reachability in graphs. Several papers have presented verified
collectors, but either the proofs were hand-written or the collectors were too
simplistic to use on practical applications. In this work, we present two
mechanically verified garbage collectors, both practical enough to use for
real-world C# benchmarks. The collectors and their associated allocators
consist of x86 assembly language instructions and macro instructions, annotated
with preconditions, postconditions, invariants, and assertions. We used the
Boogie verification generator and the Z3 automated theorem prover to verify
this assembly language code mechanically. We provide measurements comparing the
performance of the verified collector with that of the standard Bartok
collectors on off-the-shelf C# benchmarks, demonstrating their competitiveness
Preventing Atomicity Violations with Contracts
Software developers are expected to protect concurrent accesses to shared
regions of memory with some mutual exclusion primitive that ensures atomicity
properties to a sequence of program statements. This approach prevents data
races but may fail to provide all necessary correctness properties.The
composition of correlated atomic operations without further synchronization may
cause atomicity violations. Atomic violations may be avoided by grouping the
correlated atomic regions in a single larger atomic scope. Concurrent programs
are particularly prone to atomicity violations when they use services provided
by third party packages or modules, since the programmer may fail to identify
which services are correlated. In this paper we propose to use contracts for
concurrency, where the developer of a module writes a set of contract terms
that specify which methods are correlated and must be executed in the same
atomic scope. These contracts are then used to verify the correctness of the
main program with respect to the usage of the module(s). If a contract is well
defined and complete, and the main program respects it, then the program is
safe from atomicity violations with respect to that module. We also propose a
static analysis based methodology to verify contracts for concurrency that we
applied to some real-world software packages. The bug we found in Tomcat 6.0
was immediately acknowledged and corrected by its development team
Proving termination of evaluation for System F with control operators
We present new proofs of termination of evaluation in reduction semantics
(i.e., a small-step operational semantics with explicit representation of
evaluation contexts) for System F with control operators. We introduce a
modified version of Girard's proof method based on reducibility candidates,
where the reducibility predicates are defined on values and on evaluation
contexts as prescribed by the reduction semantics format. We address both
abortive control operators (callcc) and delimited-control operators (shift and
reset) for which we introduce novel polymorphic type systems, and we consider
both the call-by-value and call-by-name evaluation strategies.Comment: In Proceedings COS 2013, arXiv:1309.092
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