The exponential growth of scientific literature and increasing interdisciplinary nature of research have made the manual discovery of relevant collaborators a significant challenge. Scientific collaborator recommendation systems, which apply artificial intelligence (AI) and network science to analyze scholarly data and suggest potential research partners, have emerged as an important tool to address this need. This paper presents a systematic literature review (SLR) of 70 primary studies published between 2013 and 2026 to map the evolution, synthesize the methodologies, and identify persistent gaps in this domain. These papers have been selected from a search of 1452 papers. Our analysis reveals a clear methodological progression from simple collaborative filtering (CF) to sophisticated hybrid recommendation models integrating network representation learning (NRL). We provide a critical comparative framework evaluating techniques, datasets, scholar attributes, and evaluation practices. A key finding is a pronounced utility–evaluation gap, that is, even though algorithmic performance on historical data has advanced, there is a near-total absence of user-centered evaluation, with less than 10% of studies assessing real-world utility, serendipity, or long-term impact. The review further identifies persistent challenges including dynamic network modeling, data sparsity and cold-start scenarios, and integration of heterogeneous data sources. Based on the synthesis, we contribute novel, evidence-based practical guidelines for dataset selection, attribute engineering, and system design.

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.

Software Process Improvement (SPI) consists of a set of changes in a software development company, introducing new and improved methods, techniques, and tools. We call SPI Diagnostic, the process to know the organization current status. Typically, these SPI Diagnostic processes are manually performed, thus demanding consultant practitioner and a high effort from the organization under analysis. Based on this we propose the following question: “What solutions have been proposed to SPI Diagnostic?” We looked for other Systematic Literature Reviews with the same goal and the found studies do not answer our question. Hence, we performed a Systematic Literature Review (SLR) to investigate solutions to the SPI Diagnostic process. We executed an SLR, based on snowballing technique. This SLR characterizes 14 solutions aiming at systematizing the SPI Diagnostic process through a method, model, or framework. As a result, we advocate that Artificial Intelligence (AI) based solutions should be more explored in research to deal with SPI Diagnostic complexity and, therefore helping the SPI Diagnostic.

Background: Systematic Reviews (SR) are crucial for collecting evidence related with a particular field or area. Hence, there are different protocols for conducting SR in software engineering. There is also several tools designed to provide support for these protocols. Aims: We understand that there is still a lack of a web-tool, fully integrating the features considered important for SR. Implementing such a tool would be a great contribution to the field. Method: We analyzed several studies discussing features for tools supporting SR. We defined design decisions based on these features. Results: We created Thoth, a web-based tool for SR. In this study we present a first version, containing a set of features. Before moving forward with the implementation, we conducted a quasi-experiment for evaluating and comparing Thoth with a similar tool. Conclusion: Despite being in the right direction for achieving our goal, the results of the quasi-experiment provided us with important evidence for improving Thoth.

Summary Software product lines (SPLs) are a well‐known solution to systematically create reusable software products. Among the approaches to create an SPL, the extractive approach is usually used when the organization already has a set of similar systems. These systems are analyzed to extract, categorize, and group their common and variant features throughout the SPL reengineering process. As there are different scenario variables, such as available artifacts and team experience, the activities and techniques used to perform these tasks may change. This may increase the effort and decrease the quality of retrieved features when users with low experience in SPL reengineering perform such tasks. However, there is a lack of a process supporting these tasks considering different scenarios. Therefore, we specify the Prepare, Assemble, and Execute Process for SPL Reengineering (PAxSPL), a process that provides support to prepare, assemble, and execute feature retrieval throughout the analysis of documentation and team experience. To initially evaluate PAxSPL, we conducted and reported an exploratory case study in a real development environment. The results indicated that our proposal helps in the assembly of a feature retrieval process according to user needs. Results were important to identify points for improvement in PAxSPL. We also could use the information gathered to improve the guidelines and provide this information to be used as basis of comparison for future users.

Wireless Sensor Networks (WSNs) are rapidly becoming a necessary tool in many different application areas, such as environmental monitoring, security, safety, and so on. The heterogeneity of hardware is large, so there exists several different environments that support WSN programming. However, the great majority of such environments only target the sensors programming, forgetting about their real intent: the application. In this paper we propose an approach to satisfy the need of high level development methods in WSN applications, aiming to provide a clear link between the modelled WSN constraints and the programming entities. An important part of this proposal is the so-called Wireless Sensor Network (WiSeN) Profile, an UML profile devoted for WSN applications design in a Model-Drivel Development (MDD) paradigm.

The growth of applications developed with the support of model transformations makes reuse a required practice, specially when applied to transformation assets (e.g. transformation chains, algorithms, and configuration files). In order to promote reuse one must consider the different implementations, communalities, and variants among these assets. In this domain, a couple techniques have been used as solutions to adapt reusable assets for specific needs. However, so far, no work has discussed their combined use in real software projects. In this paper, we present a new tool named WCT, which can be used to adapt transformation assets. Moreover, through lessons learned in industry, we address some reuse techniques devoted to adapt these assets.

This paper tackles the problem of ever changing embedded systems non-functional requirements, specially the architectural ones. It proposes a solution based on features model and MDA standards, which is called features-oriented model-driven architecture (FOMDA). This proposal can be used to help application designer in defining the mappings and transformations of UML models to as many target platforms as wished. This is done by configuring model-to-model and model-to-code transformations over tiers, where every tier represents some target platform properties that the system must be mapped and transformed to. To validate the proposal a case study related to the development of an embedded real-time system is presented, detailing how to transform a generic high-level UML model to a model specific for a given target platform. Obtained results are optimistic and conclude that the FOMDA approach can make designers re-think their current development process to make it more decoupled from a specific target platform