159 research outputs found
Testing real-time systems using TINA
The paper presents a technique for model-based black-box conformance testing of real-time systems using the Time Petri Net Analyzer TINA. Such test suites are derived from a prioritized time Petri net composed of two concurrent sub-nets specifying respectively the expected behaviour of the system under test and its environment.We describe how the toolbox TINA has been extended to support automatic generation of time-optimal test suites. The result is optimal in the sense that the set of test cases in the test suite have the shortest possible accumulated time to be executed. Input/output conformance serves as the notion of implementation correctness, essentially timed trace inclusion taking environment assumptions into account. Test cases selection is based either on using manually formulated test purposes or automatically from various coverage criteria specifying structural criteria of the model to be fulfilled by the test suite. We discuss how test purposes and coverage criterion are specified in the linear temporal logic SE-LTL, derive test sequences, and assign verdicts
Model driven product line engineering : core asset and process implications
Reuse is at the heart of major improvements in productivity and quality in Software Engineering. Both Model Driven Engineering (MDE) and Software Product Line Engineering (SPLE) are software development paradigms that promote reuse. Specifically, they promote systematic reuse and a departure from craftsmanship towards an industrialization of the software development process. MDE and SPLE have established their benefits separately. Their combination, here called Model Driven Product Line Engineering (MDPLE), gathers together the advantages of both.
Nevertheless, this blending requires MDE to be recasted in SPLE terms. This has implications on both the core assets and the software development process. The challenges are twofold: (i) models become central core assets from which products are obtained and (ii) the software development process needs to cater for the changes that SPLE and MDE introduce. This dissertation proposes a solution to the first challenge following a feature oriented approach, with an emphasis on reuse and early detection of inconsistencies. The second part is dedicated to assembly processes, a clear example of the complexity MDPLE introduces in software development processes. This work advocates for a new discipline inside the general software development process, i.e., the Assembly Plan Management, which raises the abstraction level and increases reuse in such processes. Different case studies illustrate the presented ideas.This work was hosted by the University of the Basque Country (Faculty
of Computer Sciences). The author enjoyed a doctoral grant from the
Basque Goverment under the “Researchers Training Program” during the
years 2005 to 2009. The work was was co-supported by the Spanish Ministry
of Education, and the European Social Fund under contracts WAPO
(TIN2005-05610) and MODELINE (TIN2008-06507-C02-01)
Grand Challenges of Traceability: The Next Ten Years
In 2007, the software and systems traceability community met at the first
Natural Bridge symposium on the Grand Challenges of Traceability to establish
and address research goals for achieving effective, trustworthy, and ubiquitous
traceability. Ten years later, in 2017, the community came together to evaluate
a decade of progress towards achieving these goals. These proceedings document
some of that progress. They include a series of short position papers,
representing current work in the community organized across four process axes
of traceability practice. The sessions covered topics from Trace Strategizing,
Trace Link Creation and Evolution, Trace Link Usage, real-world applications of
Traceability, and Traceability Datasets and benchmarks. Two breakout groups
focused on the importance of creating and sharing traceability datasets within
the research community, and discussed challenges related to the adoption of
tracing techniques in industrial practice. Members of the research community
are engaged in many active, ongoing, and impactful research projects. Our hope
is that ten years from now we will be able to look back at a productive decade
of research and claim that we have achieved the overarching Grand Challenge of
Traceability, which seeks for traceability to be always present, built into the
engineering process, and for it to have "effectively disappeared without a
trace". We hope that others will see the potential that traceability has for
empowering software and systems engineers to develop higher-quality products at
increasing levels of complexity and scale, and that they will join the active
community of Software and Systems traceability researchers as we move forward
into the next decade of research
Grand Challenges of Traceability: The Next Ten Years
In 2007, the software and systems traceability community met at the first
Natural Bridge symposium on the Grand Challenges of Traceability to establish
and address research goals for achieving effective, trustworthy, and ubiquitous
traceability. Ten years later, in 2017, the community came together to evaluate
a decade of progress towards achieving these goals. These proceedings document
some of that progress. They include a series of short position papers,
representing current work in the community organized across four process axes
of traceability practice. The sessions covered topics from Trace Strategizing,
Trace Link Creation and Evolution, Trace Link Usage, real-world applications of
Traceability, and Traceability Datasets and benchmarks. Two breakout groups
focused on the importance of creating and sharing traceability datasets within
the research community, and discussed challenges related to the adoption of
tracing techniques in industrial practice. Members of the research community
are engaged in many active, ongoing, and impactful research projects. Our hope
is that ten years from now we will be able to look back at a productive decade
of research and claim that we have achieved the overarching Grand Challenge of
Traceability, which seeks for traceability to be always present, built into the
engineering process, and for it to have "effectively disappeared without a
trace". We hope that others will see the potential that traceability has for
empowering software and systems engineers to develop higher-quality products at
increasing levels of complexity and scale, and that they will join the active
community of Software and Systems traceability researchers as we move forward
into the next decade of research
Configuration Analysis for Large Scale Feature Models: Towards Speculative-Based Solutions
Los sistemas de alta variabilidad son sistemas de software en los que la gestión de la
variabilidad es una actividad central. Algunos ejemplos actuales de sistemas de alta
variabilidad son el sistema web de gesión de contenidos Drupal, el núcleo de Linux,
y las distribuciones Debian de Linux.
La configuración en sistemas de alta variabilidad es la selección de opciones
de configuración según sus restricciones de configuración y los requerimientos de
usuario. Los modelos de características son un estándar “de facto” para modelar las
funcionalidades comunes y variables de sistemas de alta variabilidad. No obstante,
el elevado número de componentes y configuraciones que un modelo de características
puede contener hacen que el análisis manual de estos modelos sea una tarea muy
costosa y propensa a errores. Así nace el análisis automatizado de modelos de características
con mecanismos y herramientas asistidas por computadora para extraer
información de estos modelos. Las soluciones tradicionales de análisis automatizado
de modelos de características siguen un enfoque de computación secuencial para
utilizar una unidad central de procesamiento y memoria. Estas soluciones son adecuadas
para trabajar con sistemas de baja escala. Sin embargo, dichas soluciones demandan
altos costos de computación para trabajar con sistemas de gran escala y alta
variabilidad. Aunque existan recusos informáticos para mejorar el rendimiento de
soluciones de computación, todas las soluciones con un enfoque de computación secuencial
necesitan ser adaptadas para el uso eficiente de estos recursos y optimizar su
rendimiento computacional. Ejemplos de estos recursos son la tecnología de múltiples
núcleos para computación paralela y la tecnología de red para computación distribuida.
Esta tesis explora la adaptación y escalabilidad de soluciones para el analisis automatizado
de modelos de características de gran escala. En primer lugar, nosotros
presentamos el uso de programación especulativa para la paralelización de soluciones.
Además, nosotros apreciamos un problema de configuración desde otra perspectiva,
para su solución mediante la adaptación y aplicación de una solución no
tradicional. Más tarde, nosotros validamos la escalabilidad y mejoras de rendimiento
computacional de estas soluciones para el análisis automatizado de modelos de características
de gran escala.
Concretamente, las principales contribuciones de esta tesis son:
• Programación especulativa para la detección de un conflicto mínimo y
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preferente. Los algoritmos de detección de conflictos mínimos determinan
el conjunto mínimo de restricciones en conflicto que son responsables de comportamiento
defectuoso en el modelo en análisis. Nosotros proponemos una
solución para, mediante programación especulativa, ejecutar en paralelo y reducir
el tiempo de ejecución de operaciones de alto costo computacional que
determinan el flujo de acción en la detección de conflicto mínimo y preferente
en modelos de características de gran escala.
• Programación especulativa para un diagnóstico mínimo y preferente. Los
algoritmos de diagnóstico mínimo determinan un conjunto mínimo de restricciones
que, por una adecuada adaptación de su estado, permiten conseguir un
modelo consistente o libre de conflictos. Este trabajo presenta una solución
para el diagnóstico mínimo y preferente en modelos de características de gran
escala mediante la ejecución especulativa y paralela de operaciones de alto
costo computacional que determinan el flujo de acción, y entonces disminuir
el tiempo de ejecución de la solución.
• Completar de forma mínima y preferente una configuración de modelo
por diagnóstico. Las soluciones para completar una configuración parcial
determinan un conjunto no necesariamente mínimo ni preferente de opciones
para obtener una completa configuración. Esta tesis soluciona el completar
de forma mínima y preferente una configuración de modelo mediante técnicas
previamente usadas en contexto de diagnóstico de modelos de características.
Esta tesis evalua que todas nuestras soluciones preservan los valores de salida esperados,
y también presentan mejoras de rendimiento en el análisis automatizado de
modelos de características con modelos de gran escala en las operaciones descrita
A Falsification View of Success Typing
Dynamic languages are praised for their flexibility and expressiveness, but
static analysis often yields many false positives and verification is
cumbersome for lack of structure. Hence, unit testing is the prevalent
incomplete method for validating programs in such languages.
Falsification is an alternative approach that uncovers definite errors in
programs. A falsifier computes a set of inputs that definitely crash a program.
Success typing is a type-based approach to document programs in dynamic
languages. We demonstrate that success typing is, in fact, an instance of
falsification by mapping success (input) types into suitable logic formulae.
Output types are represented by recursive types. We prove the correctness of
our mapping (which establishes that success typing is falsification) and we
report some experiences with a prototype implementation.Comment: extended versio
Languages of games and play: A systematic mapping study
Digital games are a powerful means for creating enticing, beautiful, educational, and often highly addictive interactive experiences that impact the lives of billions of players worldwide. We explore what informs the design and construction of good games to learn how to speed-up game development. In particular, we study to what extent languages, notations, patterns, and tools, can offer experts theoretical foundations, systematic techniques, and practical solutions they need to raise their productivity and improve the quality of games and play. Despite the growing number of publications on this topic there is currently no overview describing the state-of-the-art that relates research areas, goals, and applications. As a result, efforts and successes are often one-off, lessons learned go overlooked, language reuse remains minimal, and opportunities for collaboration and synergy are lost. We present a systematic map that identifies relevant publications and gives an overview of research areas and publication venues. In addition, we categorize research perspectives along common objectives, techniques, and approaches, illustrated by summaries of selected languages. Finally, we distill challenges and opportunities for future research and development
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