Observations for Assertion-based Scenarios in the context of Model Validation

Certain approaches to Model-Based Testing focus on test case generation from assertions and invariants, e.g., written in the Object Constraint Language. In such a setting, assertions and invariants must be validated. Validation can be carried out via executing scenarios wherein system operations are applied to detect unsatisfied invariants or failed assertions. This paper aims to improve our understanding of how to write useful validation scenarios for assertions in OCL. To do so, we report on our experiences during the creation and execution of 237 scenarios for validating assertions for the Mondex Smart Card application. We also describe key factors that must be considered in transforming scenarios into test cases

A Comparison of State-Based Modelling Tools for Model Validation

In model-based testing, one of the biggest decisions taken before modelling is the modelling language and the model analysis tool to be used to model the system under investigation. UML, Alloy and Z are examples of popular state-based modelling languages. In the literature, there has been research about the similarities and the differences between modelling languages. However, we believe that, in addition to recognising the expressive power of modelling languages, it is crucial to detect the capabilities and the weaknesses of analysis tools that parse and analyse models written in these languages. In order to explore this area, we have chosen four model analysis tools: USE, Alloy Analyzer, ZLive and ProZ and observed how modelling and validation stages of MBT are handled by these tools for the same system. Through this experiment, we not only concretise the tasks that form the modelling and validation stages of MBT process, but also reveal how efficiently these tasks are carried out in different tools

Testing and test-driven development of conceptual schemas

The traditional focus for Information Systems (IS) quality assurance relies on the evaluation of its implementation. However, the quality of an IS can be largely determined in the first stages of its development. Several studies reveal that more than half the errors that occur during systems development are requirements errors. A requirements error is defined as a mismatch between requirements specification and stakeholders¿ needs and expectations. Conceptual modeling is an essential activity in requirements engineering aimed at developing the conceptual schema of an IS. The conceptual schema is the general knowledge that an IS needs to know in order to perform its functions. A conceptual schema specification has semantic quality when it is valid and complete. Validity means that the schema is correct (the knowledge it defines is true for the domain) and relevant (the knowledge it defines is necessary for the system). Completeness means that the conceptual schema includes all relevant knowledge. The validation of a conceptual schema pursues the detection of requirements errors in order to improve its semantic quality. Conceptual schema validation is still a critical challenge in requirements engineering. In this work we contribute to this challenge, taking into account that, since conceptual schemas of IS can be specified in executable artifacts, they can be tested. In this context, the main contributions of this Thesis are (1) an approach to test conceptual schemas of information systems, and (2) a novel method for the incremental development of conceptual schemas supported by continuous test-driven validation. As far as we know, this is the first work that proposes and implements an environment for automated testing of UML/OCL conceptual schemas, and the first work that explores the use of test-driven approaches in conceptual modeling. The testing of conceptual schemas may be an important and practical means for their validation. It allows checking correctness and completeness according to stakeholders¿ needs and expectations. Moreover, in conjunction with the automatic check of basic test adequacy criteria, we can also analyze the relevance of the elements defined in the schema. The testing environment we propose requires a specialized language for writing tests of conceptual schemas. We defined the Conceptual Schema Testing Language (CSTL), which may be used to specify automated tests of executable schemas specified in UML/OCL. We also describe a prototype implementation of a test processor that makes feasible the approach in practice. The conceptual schema testing approach supports test-last validation of conceptual schemas, but it also makes sense to test incomplete conceptual schemas while they are developed. This fact lays the groundwork of Test-Driven Conceptual Modeling (TDCM), which is our second main contribution. TDCM is a novel conceptual modeling method based on the main principles of Test-Driven Development (TDD), an extreme programming method in which a software system is developed in short iterations driven by tests. We have applied the method in several case studies, in the context of Design Research, which is the general research framework we adopted. Finally, we also describe an integration approach of TDCM into a broad set of software development methodologies, including the Unified Process development methodology, MDD-based approaches, storytest-driven agile methods and goal and scenario-oriented requirements engineering methods.Els enfocaments per assegurar la qualitat deis sistemes d'informació s'han basal tradicional m en! en l'avaluació de la seva implementació. No obstan! aix6, la qualitat d'un sis tema d'informació pot ser ampliament determinada en les primeres fases del seu desenvolupament. Diversos estudis indiquen que més de la meitat deis errors de software són errors de requisits . Un error de requisit es defineix com una desalineació entre l'especificació deis requisits i les necessitats i expectatives de les parts im plicades (stakeholders ). La modelització conceptual és una activitat essencial en l'enginyeria de requisits , l'objectiu de la qual és desenvolupar !'esquema conceptual d'un sistema d'informació. L'esquema conceptual és el coneixement general que un sistema d'informació requereix per tal de desenvolupar les seves funcions . Un esquema conceptual té qualitat semantica quan és va lid i complet. La valides a implica que !'esquema sigui correcte (el coneixement definit és cert peral domini) i rellevant (el coneixement definit és necessari peral sistema). La completes a significa que !'esquema conceptual inclou tot el coneixement rellevant. La validació de !'esquema conceptual té coma objectiu la detecció d'errors de requisits per tal de millorar la qualitat semantica. La validació d'esquemes conceptuals és un repte crític en l'enginyeria de requisits . Aquesta te si contribueix a aquest repte i es basa en el fet que els es quemes conceptuals de sistemes d'informació poden ser especificats en artefactes executables i, per tant, poden ser provats. Les principals contribucions de la te si són (1) un enfocament pera les pro ves d'esquemes conceptuals de sistemes d'informació, i (2) una metodología innovadora pel desenvolupament incremental d'esquemes conceptuals assistit per una validació continuada basada en proves . Les pro ves d'esquemes conceptuals poden ser una im portant i practica técnica pera la se va validació, jaque permeten provar la correctesa i la completesa d'acord ambles necessitats i expectatives de les parts interessades. En conjunció amb la comprovació d'un conjunt basic de criteris d'adequació de les proves, també podem analitzar la rellevancia deis elements definits a !'esquema. L'entorn de test proposat inclou un llenguatge especialitzat per escriure proves automatitzades d'esquemes conceptuals, anomenat Conceptual Schema Testing Language (CSTL). També hem descrit i implementa! a un prototip de processador de tes tos que fa possible l'aplicació de l'enfocament proposat a la practica. D'acord amb l'estat de l'art en validació d'esquemes conceptuals , aquest és el primer treball que proposa i implementa un entorn pel testing automatitzat d'esquemes conceptuals definits en UML!OCL. L'enfocament de proves d'esquemes conceptuals permet dura terme la validació d'esquemes existents , pero també té sentit provar es quemes conceptuals incomplets m entre estant sent desenvolupats. Aquest fet és la base de la metodología Test-Driven Conceptual Modeling (TDCM), que és la segona contribució principal. El TDCM és una metodología de modelització conceptual basada en principis basics del Test-Driven Development (TDD), un métode de programació en el qual un sistema software és desenvolupat en petites iteracions guiades per proves. També hem aplicat el métode en diversos casos d'estudi en el context de la metodología de recerca Design Science Research. Finalment, hem proposat enfocaments d'integració del TDCM en diverses metodologies de desenvolupament de software

Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

Metamodel-based model conformance and multiview consistency checking

Model-driven development, using languages such as UML and BON, often makes use of multiple diagrams (e.g., class and sequence diagrams) when modeling systems. These diagrams, presenting different views of a system of interest, may be inconsistent. A metamodel provides a unifying framework in which to ensure and check consistency, while at the same time providing the means to distinguish between valid and invalid models, that is, conformance. Two formal specifications of the metamodel for an object-oriented modeling language are presented, and it is shown how to use these specifications for model conformance and multiview consistency checking. Comparisons are made in terms of completeness and the level of automation each provide for checking multiview consistency and model conformance. The lessons learned from applying formal techniques to the problems of metamodeling, model conformance, and multiview consistency checking are summarized

SizeNet: Weakly Supervised Learning of Visual Size and Fit in Fashion Images

Finding clothes that fit is a hot topic in the e-commerce fashion industry. Most approaches addressing this problem are based on statistical methods relying on historical data of articles purchased and returned to the store. Such approaches suffer from the cold start problem for the thousands of articles appearing on the shopping platforms every day, for which no prior purchase history is available. We propose to employ visual data to infer size and fit characteristics of fashion articles. We introduce SizeNet, a weakly-supervised teacher-student training framework that leverages the power of statistical models combined with the rich visual information from article images to learn visual cues for size and fit characteristics, capable of tackling the challenging cold start problem. Detailed experiments are performed on thousands of textile garments, including dresses, trousers, knitwear, tops, etc. from hundreds of different brands.Comment: IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW) 2019 Focus on Fashion and Subjective Search - Understanding Subjective Attributes of Data (FFSS-USAD