Centralised architecture models are often adopted in the development of smart cities to take advantage of the technologies provided by dominant companies such as Google, Meta, and Amazon. This approach often comes with significant drawbacks, such as (i) application developers becoming dependent on the policies and rules imposed by large companies, which are subject to change, and (ii) users having their data collected and used haphazardly, and often without authorisation, which can undermine the trust that users place in the solution. Infrastructure for smart cities should, therefore, incorporate decentralised technologies that satisfy or reinforce important quality attributes such as trustworthiness, privacy, and security. The main objective of this article is to survey and discuss how the services of a smart city can be implemented using decentralised architectures; we explain the advantages and disadvantages of decentralised architectures and emerging technologies. We review the specialised literature and compile a set of emerging technologies that are essential to conceive a decentralised architectural solution for smart cities. The current state-of-the-art in decentralisation shows that this model can be implemented with current technologies and help to satisfy the quality attributes mentioned above, and potentially reinforce the degree of trustworthiness of the solution. We also propose a four-dimension guideline that functions as a conceptual driver for structuring actions for researchers, system architects, policymakers, and city authorities in the design, evaluation, and long-term maintenance of decentralised smart cities, thereby enhancing their capacity to address escalating urban challenges. We conclude that the set of technologies discussed in this article has the potential to be reused and replicated across smart cities. • Choice between C-architecture and D-architecture for smart cities. • Concerns about interoperability, privacy, vendor lock-in, and sustainability. • Decentralisation offers improved interoperability, privacy, and sustainability. • Approach to decentralised digital identity, permissions, and integration solutions.

Search-Based Software Engineering (SBSE) is widely used in different fields of Software Engineering, notoriously, in Enterprise Application Integrations (EAIs). EAI encompasses methodologies, techniques and tools that a software engineer can use to create integration solutions. SBSE is currently an active research topic of increasing interest. The number and diversity of publications produced yearly are large to the extent that it is hard to identify the active research groups, their locations, techniques used and research topics that have not received enough attention. To answer these questions categorically, we have conducted systematic mapping study of the literature. In this paper, we report our methodology and findings. In our study, we used systematic search strategies that resulted in the retrieval of 560 articles, of which we first selected 25. Second, on the basis of the authors’ experience, we included eight additional articles. Finally, we used a snowballing sample technique to include another 12 articles. The results demonstrate that during the last two decades (1999–2020) EAI has benefited from the use of Search-Based Software Engineering techniques.

Abstract Guaraná domain‐specific language is aimed to design enterprise application integration models. Although the language has been broadly used in the industry and academy, the design of its graphical notation was based in the common sense and social opinion of its developers rather than theoretical principles and empirical evidence. Thus, Guaraná becomes as an option for studying, modifying, and improving its concrete syntax. In this article we conducted an experiment with 85 participants in order to evaluate the semantic transparency of the concrete syntax of Guaraná. The study concludes that the language is not found to be semantically immediate because most of the language constructs used in the graphical notation of Guaraná are not semantically immediate, that is, a novice reader is not able to infer their meaning from their appearance alone.

Summary Increasingly enterprises rely on software applications to support their business processes. Since such processes are continually evolving to keep up with market dynamism, companies strive to increase their efficiency, for example, by optimising the integration of applications supporting these processes. Integration platforms are specialised software tools that allow creating integration processes so that applications can share data and functionality. However, this integration involves several challenges, especially when large volumes of heterogeneous data should be integrated and shared. The performance of an integration process, in terms of message processing, is directly related to the run‐time system of the integration platform. This article investigates the impact of the volume of messages and the number of threads used by a run‐time system on makespan and performance of an integration process. The greater is the number of messages per second received by the integration process, the high is the volume of messages. The study was based on a run‐time system with task‐based execution model and follows a strict protocol to conduct and report our empirical study. We observed an increment of makespan when increasing the volume of messages to integration processes and different behaviours when increasing the number of threads used in their executions. Makespan reduces as the number of threads increases, but only when the volume of inbound messages is not very high. We confirmed that there is a performance gain by increasing the number of threads to execute an integration process, but observed that the continuous increment of threads leads to degradation of the performance in this model.

Abstract This article addresses major information systems integration problems, approaches, technologies, and tools within the context of Model‐Driven Software Engineering. The Guaraná integration platform is introduced as an innovative platform amongst state‐of‐the‐art technologies available for enterprises to design and implement integration solutions. In this article, we present its domain‐specific modeling language and its industrial cloud‐based web development platform, which supports the design and implementation of integration solutions. A real‐world case study is described and analyzed; then, we delve into its design and implementation, to finally disclose ten measures that empirically help estimating the amount of effort involved in the development of integration solutions.

Summary Integration frameworks are specialized software tools built and adapted to facilitate the design and implementation of integration solutions. An integration solution allows for the reuse of applications from the software ecosystem of companies to support their business processes. There are several open‐source integration frameworks available on the market designed to operate in a business context to manipulate structured data; however, increasingly, they are required to deal with unstructured and large volumes of data, thus requiring effort to adapt these frameworks to work with unstructured and large volume of data. Choosing the framework, which is the easiest to be adapted, is not a trivial task. In this article, we review the newest stable versions of four open‐source integration frameworks by analyzing how they have evolved regarding their adaptive maintainability over five years. We rank them according to their maintainability degree and compare past and current versions of each framework. To encourage and enable researchers and developers to replicate our experiments, with the aim of verifying our findings, and to experiment with new versions of the integration frameworks analyzed, we detail the experimental protocol used while also having made all the required software involved available on the Web.

Summary Enterprises turn to their software applications to support their business processes. Over time, it is common for a company to end up with a wide range of applications, which are usually developed in‐house by its information technology department or purchased from third‐party specialized software companies. The result is a heterogeneous software ecosystem with applications developed in different technologies and frequently using different data models, which brings challenges when two or more applications have to collaborate to support a business process. Integration platforms are specialized software tools that help design, implement, run, and monitor integration solutions that orchestrate a set of applications. The run‐time system is the component of integration platforms responsible for running integration solutions, which makes its performance a critically important issue. In this paper, we report our experience in evaluating and comparing four well‐known open‐source integration platforms in the context of a research project where performance was a central requirement to choose an integration platform. The evaluation was conducted using a decision‐making methodology to build a ranking of candidate platforms by means of subjective and objective criteria. The subjective evaluation takes into account expert preferences and compares integration platforms using the analytic hierarchy process, which has been used in many applications related with decision‐making. The objective evaluation is build on top of properties distributed on three dimensions, namely, message processing, hotspot detection, and fairness execution, which compose the research methodology we used. The evaluated platforms were ranked to identify the one with the best performance.

Summary Companies are taking advantage of cloud computing to upgrade their business processes. Cloud computing requires interaction with many kinds of applications, so it is necessary to improve the performance of software tools that allow keeping information on all these applications consistent and synchronised. Integration platforms are specialised software tools that provide support to design, implement, run, and monitor integration solutions, which aim to orchestrate a set of applications so as to promote compatibility among their data or to develop new functionality on top of the current ones. The run‐time system is the part of the integration platform responsible for running the integration solutions, which makes its performance the uttermost important issue. The contribution of this article is two‐fold: a framework and an evaluation of integration platforms. The former is a framework composed of ten properties grouped into two dimensions to evaluate the run‐time systems focusing on performance. Using this framework as reference, the second contribution is an evaluation of nine open‐source integration platforms, which represent the state‐of‐the‐art, provide support to the integration patterns, and follow the pipes‐and‐filters architectural style. In addition, as a result of this work, we suggest open research directions that can be explored to improve the performance of the run‐time systems and at the same time may be useful to adapt them to the context of cloud computing.

FMSPLE 2012 is the third edition of the FMSPLE workshop series, traditionally affiliated with SPLC, which aims to connect researchers and practitioners interested in raising the efficiency and the effectiveness of SPLE through the application of innovative analysis approaches and formal methods.

Orthogonal Variability Model (OVM) is a modelling language for representing variability in Software Product Line Engineering. The automated analysis of OVMs is defined as the computer-aided extraction of information from such models. In this paper, we present FaMa-OVM, which is a pioneer tool for the automated analysis of OVMs. FaMa-OVM is easy to extend or integrate in other tools. It has been developed as part of the FaMa ecosystem enabling the benefits coming from other tools of that ecosystem as FaMaFW and BeTTy.