Change Impact Analysis based on Formalization of Trace Relations for Requirements

Evolving customer needs is one of the driving factors in software development. There is a need to analyze the impact of requirement changes in order to determine possible conflicts and design alternatives influenced by these changes. The analysis of the impact of requirement changes on related requirements can be based on requirements traceability. In this paper, we propose a requirements metamodel with well defined types of requirements relations. This metamodel represents the common concepts extracted from some prevalent requirements engineering approaches. The requirements relations in the metamodel are used to trace related requirements for change impact analysis. We formalize the relations. Based on this formalization, we define change impact rules for requirements. As a case study, we apply these rules to changes in the requirements specification for Course Management System

Hawk solutions to the TTC 2018 Social Media Case

The TTC 2018 Social Media Case required answering queries about social networks, where people write posts, comment on them, and friend or unfriend each other. NoSQL databases have been popular in the analysis of large social networks, and the Hawk heterogeneous model indexer can turn the models in the case to Neo4j NoSQL databases. This paper presents three solutions that were developed on top of each other, reducing on each step the amount of work required to update the results of the query

A model-driven traceability framework for software product lines

International audienceSoftware product line (SPL) engineering is a recent approach to software development where a set of software products are derived for a well defined target application domain, from a common set of core assets using analogous means of production (for instance, through Model Driven Engineering). Therefore, such family of products are built from reuse, instead of developed individually from scratch. SPL promise to lower the costs of development, increase the quality of software, give clients more flexibility and reduce time to market. These benefits come with a set of new problems and turn some older problems possibly more complex. One of these problems is traceability management. In the Europe an AMPLE project we are creating a common traceability framework across the various activities of the SPL development. We identified four orthogonal traceability dimensions in SPL development, one of which is an extension of what is often considered as "traceability of variability". This constitutes one of the two contributions of this paper. The second contribution is the specification of a metamodel for a repository of traceability links in the context of SPL and the implementation of a respective traceability framework. This framework enables fundamental traceability management operations, such as trace import and export, modification, query and visualization. The power of our framework is highlighted with an example scenari

Formal Model Merging Applied to Class Diagram Integration

AbstractThe integration of software artifacts is present in many scenarios of the Software Engineering field: object-oriented modeling, relational databases, XML schemas, ontologies, aspect-oriented programming, etc. In Model Management, software artifacts are viewed as models that can be manipulated by means of generic operators, which are specified independently of the context in which they are used. One of these operators is Merge, which enables the automated integration of models. Solutions for merging models that are achieved by applying this operator are more abstract and reusable than the ad-hoc solutions that are pervasive in many contexts of the Software Engineering field. In this paper, we present our automated approach for generic model merging from a practical standpoint, providing support for conflict resolution and traceability between software artifacts by using the QVT Relations language. We focus on the definition of our operator Merge, applying it to Class Diagrams integration

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings