Model-Driven Engineering and Software Development

The Unified Modeling Language (UML) is the most commonly used software description language. Today, textual notations for UML aim for a compact representation that is suitable for developers. Many textual notations exist but their applicability in engineering teams varies because a standardized textual notation is missing. Evaluating notations in order to find a suitable one is cumbersome and guidelines found in surveys do not report on applicability. This survey identifies textual notations for UML that can be used instead of or in combination with graphical notations, e.g. by collaborating teams or in different contexts. Additionally, it rates the notation’s applicability with respect to UML coverage, user editing experience, and applicability focused on engineering teams. Our results facilitate the otherwise unclear selection of a notation tailored for specific scenarios and enables trade-off decisions. We identified and characterized 21 known notations and 12 notations that were not covered in previous surveys. We used 20 categories to characterize the notations. Our findings show that a single notation does not cover more than 3 UML diagram types (mean 2.6), supports all surveyed state of the art editing features (only one notation supports all), and fits into existing tool chains.

Model-driven engineering (MDE) enables to generate software tools by systematically modeling and transforming this models. However, the usability of these tools is far from efficient. Common MDE activities, such as creating a domain-specific language, are non-trivial and often require repetitive tasks. This results in unnecessary increases of development time. The goal of this paper is to increase the productivity of modelers in their every day activities by automating the tasks they perform in current MDE tools. We propose an MDE-based solution where the user defines a reusable workflow that can be parametrized at run-time and executed. Our solution works for frameworks that support two level metamodeling as well as deep metamodeling. We implemented our solution in the MDE tool AToMPM. We also performed an empirical evaluation of our approach and showed that we reduce both mechanical and thinking efforts of the user. The ideas and concepts of this paper were introduced at the MODELSWARD conference [1] and are extended in this paper.

The configuration of a complex, generic, real-time application into a specifically customized signalling embedded application has an important impact on time to market, deployment costs and safety guarantees for a railway signalling manufacturer. In this paper we focus on the aspect of real-time schedulability analysis, that takes an important portion of the time dedicated to configuration in this kind of systems. We propose an approach based on rigorous modelling of the scheduling algorithms, aimed at substituting possibly unreliable and costly empirical tuning. In order to comply with the needs of our industrial partners, we have resorted to the use of variants of Petri Nets with associated available tools: Timed Petri Nets (TPN) and Coloured Petri Nets (CPN), supported by open source tools, respectively TINA and CPN Tools 4.0 have been exploited for the modelling of the pre-runtime and the runtime scheduling algorithms implemented in the industrial platform. The comparison of models produced with the two tools has concluded that the Coloured Petri Nets are more suited to the adopted schedulability analysis approach, for both scheduling algorithms.

State-of-the-art technologies have made it possible to provide a learner with immediate computer-assisted feedback by delivering a feedback targeting cognitive aspects of learning, (e.g. reflecting on a result, explaining a concept, i.e. improving understanding). Fast advancement of technology has recently generated increased interest for previously non-feasible approaches for providing feedback based on learning behavioral observations by exploiting different traces of learning processes stored in information systems. Such learner behavior data makes it possible to observe different aspects of learning processes in which feedback needs of learners (e.g. difficulties, engagement issues, inefficient learning processes, etc.) based on individual learning trajectories can be traced. By identifying problems earlier in a learning process it is possible to deliver individualized feedback helping learners to take control of their own learning, i.e. to become self-regulated learners, and teachers to understand individual feedback needs and/or adapt their teaching strategies. In this work we (i) propose cognitive computer-assisted feedback mechanisms using a combination of MDE based simulation augmented with automated feedback, and (ii) discuss perspectives for behavioral feedback, i.e. feedforward, that can be based on learning process analytics in the context of learning conceptual modeling. Aggregated results of our previous studies assessing the effectiveness of the proposed cognitive feedback method with respect to improved understanding on different dimensions of knowledge, as well as feasibility of behavioral feedforward automation based on learners behavior patterns, are presented. Despite our focus on conceptual modeling and specific diagrams, the principles of the approach presented in this work can be used to support educational feedback automation for a broader spectrum of diagram types beyond the scope of conceptual modeling.

Testing interactive multimodal applications is particularly important and requires a lot of effort. Automating this activity can result to significant development cost reduction and quality improvement. In this paper, we propose an approach for automating the test generation of such multimodal applications. This approach is based on the definition of a test modeling language, TTT. The objective of the TTT language is to provide a means for expressing abstract test scenarios for interactive multimodal applications, including non-deterministic choices and action occurrence probabilities that can be used to automate the test generation. Then, we built the TTTEST tool that supports to generate tests for multimodal events and to check the validity of CARE properties of this kind of applications. The approach is illustrated on a case study.

Cloud computing brings new business opportunities and services on infrastructure, platform and software level. It provides a new way for testing software applications known as Testing-as-a-Service (TaaS). TaaS eliminates the need of installing and maintaining testing environments on customer’s side and reduces the testing cost on pay-per-use basis. Availability of on-demand testing services allows testers to provide raw cloud resources at run time, when and where needed. This paper addresses TaaS benefits by proposing a TaaS-enabled framework offering cloud-based testing services. The framework, called Testing as a Service Software Architecture (TASSA), supports testing of web service compositions described with Business Process Execution Language for Web Services (WS-BPEL). It consists of two main components: (1) TaaS functionality for fault injection and dependencies isolation of the application under test and (2) Graphical User Interface (GUI) for test case design and execution. TASSA framework could be installed on a local computer or used for building a cloud test lab on a virtual machine. Its feasibility is proved through a case study on a sample business process from wine industry.

Ontologies are an essential component of semantic knowledge bases and applications, and nowadays they are used in a plethora of domains. Despite the maturity of ontology languages, support tools and engineering techniques, the testing and validation of ontologies is a field which still lacks consolidated approaches and tools. This paper attempts at partly bridging that gap, taking a first step towards the extension of some traditional software testing techniques to ontologies expressed in a widely-used format. Mutation testing and coverage testing, revisited in the light of the peculiar features of the ontology language and structure, can can assist in designing better test suites to validate them, and overall help in the engineering and refinement of ontologies and software based on them.

This paper presents the Italian scenario of cash register software certification. The basic concepts of certification are introduced together with involved actors, requirements and possible objects to be certified. Subsequently, the specific kind of fiscal device running fiscal software, that is the cash register, is outlined, and its certification process is described. The current technological adjustments of the cash register software according to the Italian legislation modifications are introduced and discussed.

The work presented in this paper addresses the general problem of verifying if models structurally compliant to a given meta-model also satisfy the constraints specified on it, whether integrity or tool-specific ones. For accomplishing such constraints satisfaction verification, a completely model-driven strategy is proposed, whose core idea is to perform the checking by applying an M2M transformation to the model to verify, hence yielding a model which represents the verification result. This output model encapsulates every detected constraint violation, allowing their later manifestation, automatic fixing or any other kind of processing. Besides providing a meta-model for formalizing those diagnostic models gathering constraint violations, the presented methodology enables the systematic and straightforward development of verification tools, each one targeting a given couple of domain meta-model and constraints set. Therefore, it supports the actual objective of this work: A strategy for the development of a generic tool for the verification, suitable for any constraints set or meta-model. The functional foundation for designing such a generic tool is that it will be based on a generator (meta-tool) for the on-the-fly creation of the required specific tool (M2M checking transformation), thanks to the Higher Order Transformation (HOT) technique.

Internet of Things (IoT) and sensor networks are improving the cooperation between organizations, becoming more efficient and productive for the industrial systems. However, high iteration between human, machines, and heterogeneous IoT technologies increases the security threats. The IoT security is an essential requirement to fully adoption of applications, which requires correct management of information and confidentiality. The system and devices’ variability requires dynamically adaptive systems to provide services depending on the context of the environment. In this paper, we propose a model driven adaptive approach to offer security services for an ontology-based security framework. Model-Driven Engineering (MDE) approach allows creating secure capabilities more efficient with the generation of security services based on security requirements in the knowledge base (IoTSec ontology). An industrial scenario of C2NET project was analyzed to identify the transformation of a system design of security solution in a platform specific model.

Service oriented architecture is emerging as a powerful paradigm for organizations that need to integrate their applications within and across organizational boundaries. Organizations need to take decisions more quickly and need to change those decisions dynamicaly. Delivering an adequate level of performance is a critical and significant challenge that requires monitoring along the different layers of service oriented architecture. Current monitoring systems are designed to support specific layers but do not fulfil the requirements of all the layers of service oriented architecture. Ontologies on the semantic web standardize and formalize the concepts and store domain knowledge for effective decision making. In this paper, we propose performance monitoring framework for various layers of service oriented architecture. It integrates various ontologies to monitor the performance at the service oriented layers in order to ensure their sustainability. We design a Service Performance Ontology that captures all the information about the service domain. Along with that we design ontologies for ensuring performance at service level, binding level, composition level and server level. We conduct a performance evaluation over real web services using suitable estimators for response time, delay, loss and more.

Scrumban combines two Agile approaches (Scrum and Kanban) to create a management framework for improving software engineering practices. Scrumban is expected to override both Scrum and Kanban, as it inherits the best features of both. However, there is little understanding of the possible impact of Scrumban on software development in prior studies. This study first makes a comparison among Scrum, Kanban, and Scrumban and then investigates the impact of Scrumban on six major challenges of global software development. This study was conducted in a distributed project at two Software Factories in two universities in Finland and Italy. The results show that Scrumban could positively affect issues such as evenness of different sites, communication, and cultural issues as well as leveraging resources among sites. However, there are still few challenges that require alternative methodologies and tools other than Scrumban to be overcome.

A challenging aspect of model-to-code transformations is to ensure that the semantic behavior of the input model is preserved in the output code. When constructing concurrent systems, this is mainly difficult due to the non-deterministic potential interaction between threads. In this paper, we consider this issue for a framework that implements a transformation chain from models expressed in the state machine based domain specific language SLCO to Java. In particular, we provide a fine-grained generic mechanism to preserve atomicity of SLCO statements in the Java implementation. We give its generic specification based on separation logic and verify it using the verification tool VeriFast. The solution can be regarded as a reusable module to safely implement atomic operations in concurrent systems. Moreover, we also prove with VeriFast that our mechanism does not introduce deadlocks. The specification formally ensures that the locks are not reentrant which simplifies the formal treatment of the Java locks.

Process Oriented Training can be applied in two different approaches: (a) processes describing the methodology of training and learning as well as (b) processes describing the organizational context that need to be learned. This paper introduces the results of the EU project Learn PAd that developed prototypes of modelling tools enabling the latter - the usage of business processes to describe the organizational context. Flexibility of business processes have been introduced with case management and knowledge artefacts had been integrated to provide a homogeneous modelling environment. The requirements of such a modelling environment had been collected and implemented with the meta-modelling platform ADOxx^®. The meta-model approach has been used to implement the modelling language as well as the mechanisms and the algorithms. The architecture of the modeling tool is introduced and a use case feedback is provided.

To improve their service quality modern organization employees have to understand and put in action latest procedures and rules while coping with quickly changing contexts and decreasing resources. To this end a model-based architecture with interrelated enriched models is required in order to fosters an informative learning approach in the learning-by-doing paradigm. Such architecture enables organization employees to learn by accessing and studying enriched business process models and related material in a process-driven learning approach. Zachman Framework is used to organize all the models through the definition of the relations among them.

Assessing the acquired competencies during a learning activity as well as the possibility of simulating difficult situations or scenarios are important challenges in learning management. The current uses of (semi) formal models representing the knowledge domain open the possibility of advanced techniques of simulation and monitoring. In this paper, we propose an assessment environment for model-based learning management that integrates simulation and monitoring facilities. In particular, we describe its architecture and main functionalities and its application inside an ongoing EU project. The proposed framework allows for user-friendly learning simulation with a strong support for collaboration and social interactions. Moreover, it monitors the learners’ behavior during simulation execution and it is able to compute the learning scores useful for the learner knowledge assessment.

The support of workplace learning is increasingly relevant as the change in every form determines today’s working world in the industry and public administrations alike. Adapting quickly to a new job, a new task or a new team is a significant challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it is aligned with business goals. Our approach supports workplace learning by suggesting historical cases and providing recommendations of experts and learning resources. We utilize users’ workplace environment, we consider their learning preferences, provide them with useful prior lessons, and compare required and acquired competencies to issue the best-suited recommendations. Our research work follows a Design Science Research strategy and is part of the European funded project Learn PAd. The recommender system introduced here is evaluated in an iterative manner, first by comparing it to previously elicited user requirements and then through practical application in a test process conducted by the project application partner.