32,164 research outputs found
A Domain-Specific Language and Editor for Parallel Particle Methods
Domain-specific languages (DSLs) are of increasing importance in scientific
high-performance computing to reduce development costs, raise the level of
abstraction and, thus, ease scientific programming. However, designing and
implementing DSLs is not an easy task, as it requires knowledge of the
application domain and experience in language engineering and compilers.
Consequently, many DSLs follow a weak approach using macros or text generators,
which lack many of the features that make a DSL a comfortable for programmers.
Some of these features---e.g., syntax highlighting, type inference, error
reporting, and code completion---are easily provided by language workbenches,
which combine language engineering techniques and tools in a common ecosystem.
In this paper, we present the Parallel Particle-Mesh Environment (PPME), a DSL
and development environment for numerical simulations based on particle methods
and hybrid particle-mesh methods. PPME uses the meta programming system (MPS),
a projectional language workbench. PPME is the successor of the Parallel
Particle-Mesh Language (PPML), a Fortran-based DSL that used conventional
implementation strategies. We analyze and compare both languages and
demonstrate how the programmer's experience can be improved using static
analyses and projectional editing. Furthermore, we present an explicit domain
model for particle abstractions and the first formal type system for particle
methods.Comment: Submitted to ACM Transactions on Mathematical Software on Dec. 25,
201
A heuristic-based approach to code-smell detection
Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache
JWalk: a tool for lazy, systematic testing of java classes by design introspection and user interaction
Popular software testing tools, such as JUnit, allow frequent retesting of modified code; yet the manually created test scripts are often seriously incomplete. A unit-testing tool called JWalk has therefore been developed to address the need for systematic unit testing within the context of agile methods. The tool operates directly on the compiled code for Java classes and uses a new lazy method for inducing the changing design of a class on the fly. This is achieved partly through introspection, using Java’s reflection capability, and partly through interaction with the user, constructing and saving test oracles on the fly. Predictive rules reduce the number of oracle values that must be confirmed by the tester. Without human intervention, JWalk performs bounded exhaustive exploration of the class’s method protocols and may be directed to explore the space of algebraic constructions, or the intended design state-space of the tested class. With some human interaction, JWalk performs up to the equivalent of fully automated state-based testing, from a specification that was acquired incrementally
Automatic Test Generation for Space
The European Space Agency (ESA) uses an engine to perform tests in the Ground
Segment infrastructure, specially the Operational Simulator. This engine uses
many different tools to ensure the development of regression testing
infrastructure and these tests perform black-box testing to the C++ simulator
implementation. VST (VisionSpace Technologies) is one of the companies that
provides these services to ESA and they need a tool to infer automatically
tests from the existing C++ code, instead of writing manually scripts to
perform tests. With this motivation in mind, this paper explores automatic
testing approaches and tools in order to propose a system that satisfies VST
needs
Learning Concise Models from Long Execution Traces
Abstract models of system-level behaviour have applications in design
exploration, analysis, testing and verification. We describe a new algorithm
for automatically extracting useful models, as automata, from execution traces
of a HW/SW system driven by software exercising a use-case of interest. Our
algorithm leverages modern program synthesis techniques to generate predicates
on automaton edges, succinctly describing system behaviour. It employs trace
segmentation to tackle complexity for long traces. We learn concise models
capturing transaction-level, system-wide behaviour--experimentally
demonstrating the approach using traces from a variety of sources, including
the x86 QEMU virtual platform and the Real-Time Linux kernel
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