Industry 4.0 refers to the digital transformation in the manufacturing domain through new technology. Currently, it expands well beyond manufacturing, affecting many areas of life and posing implications for all types of business. This paper focuses on the relationships between Industry 4.0 and Healthcare which transitions to increased interconnectivity, automation and smart decision making. The integration context of Industry 4.0 into Healthcare is only partly understood. Little was done until now to consolidate what is known on the integration benefits and the challenges. This article reports results of a systematic mapping study that analysed 69 papers to extract knowledge about the concepts of Industry 4.0 and the emerging Healthcare 4.0., and the relationships between them. We found 10 different perspectives of Healthcare 4.0, ranging from strategic to tactical and operational levels. Next, our results show: (i) nine applications of Industry 4.0 in the Healthcare domain: Augmented Reality and Simulation, Autonomous Robotics, Cybersecurity, Big Data Analytics, Internet of Things, Cloud Computing, Additive Manufacturing and Systems Integration; and (ii) 10 benefits and nine challenges in Healthcare 4.0. The most frequently mentioned benefits are patients' diagnosis, monitoring, treatment, and financial benefits. The most researched challenges are data fragmentation, heterogeneity, complexity, and privacy.

imageThis paper reports results of a systematic literature review on the integration of industry 4.0 and healthcare. Based on 69 selected primary studies, we presents the state‐of‐the art research on this topic and on the benefits and challenges of integrating Industry 4.0 into Healthcare.

Mobile apps with tested Graphical User Interface (GUI) tend to have higher downloads in the apps store. In recent years, few efforts were made to analyse the research community and research status of the literature for GUI testing on mobile apps, which brings an obstacle to characterise and understand this field. In this study, the authors propose a systematic mapping study to gain insights into the field. First, the authors conduct an extensive search of relevant literature over seven popular digital libraries. From 4427 candidate studies, 114 primary studies published between January 2011 and September 2022 were selected. Next, the authors analyse these primary studies from the perspectives of bibliometric and qualitative analysis. For the bibliometric analysis, first, the authors analyse the popular research topics and their relationships. Second, the authors study the authors' community. For the qualitative analysis, the authors analyse the objectives, approaches and evaluation metrics employed in these primary studies. Their investigation reports several major findings: (1) there are relatively more studies on two topics, that is, test case generation and the automated test; (2) the most productive authors tend to collaborate and often have relatively broad research interests; (3) the functionality is the main objective of GUI testing; the model‐based approach is the most widely used.

This paper presents a systematic mapping study to gain insight into GUI testing for mobile apps. Through bibliometric analysis, the paper identifies the GUI testing research communities, influential authors, papers and popular topic trends. Additionally, the paper identifies the common approaches and the evaluation metrics used in GUI testing for mobile apps through qualitative analysis.image

Software organisations aim to develop and maintain high‐quality software systems. Due to large amounts of behaviour data available, software organisations can conduct data‐driven software maintenance. Indeed, software quality assurance and improvement programs have attracted many researchers' attention. Bayesian Networks (BNs) are proposed as a log analysis technique to discover poor performance indicators in a system and to explore usage patterns that usually require temporal analysis. For this, an action research study is designed and conducted to improve the software quality and the user experience of a web application using BNs as a technique to analyse software logs. To this aim, three models with BNs are created. As a result, multiple enhancement points have been identified within the application ranging from performance issues and errors to recurring user usage patterns. These enhancement points enable the creation of cards in the Scrum process of the web application, contributing to its data‐driven software maintenance. Finally, the authors consider that BNs within quality‐aware and data‐driven software maintenance have great potential as a software log analysis technique and encourage the community to deepen its possible applications. For this, the applied methodology and a replication package are shared.

In this paper, Bayesian networks are proposed as a log analysis technique to discover poor performance indicators in a system and to explore usage patterns. For this, an action research study is designed and conducted to improve the software quality and the user experience of a web application using Bayesian networks as a technique to analyse software logs. As a result, multiple enhancement points have been identified within the application, ranging from performance issues and errors to recurring user usage patterns.image

In the context of requirements specification in Global Software Development, aspects such as differences in culture, language and schedule affect software development teams; however, we do not know the effect of these issues. Compare the native language requirements with the foreign language requirements concerning external quality. We conducted a controlled experiment of one‐factor two treatments within‐subjects with 17 experimental subjects. Wilcoxon test indicates that there is evidence to reject the null hypothesis (p‐value = 0.008); there is a statistically significant difference. The external quality value obtained with native language requirements is superior to the external quality produced with the foreign language. The effect size equals an absolute value of 0.45, which corresponds to a medium effect. The language used in the requirements specification influences the external quality; using the native language in the requirements specification significantly increases the external quality. The result obtained in this research should be considered to evaluate the roles and English language skills of GSD team members and their effect on external software quality. We also suggest considering the English language skills of the experimental subjects in the experimental laboratories since language could influence the results of the experiments.

A controlled experiment to determine whether the language of the requirements influences the external quality of the software product.image

As agile software development and extreme programing have become increasingly popular, continuous integration (CI) has become a widely used collaborative work method. However, it is common to make changes frequently to a project during CI. If existing testing methods are applied to CI directly, it will be difficult to make testing resources focus on changes generated by CI, which results in insufficient testing for changes. To solve this problem, we propose a fuzz testing method for CI. First, differential analysis is performed to determine the change points generated during CI, change points are added to the taint source set, and static analysis is conducted to calculate the distances between each basic block and the taint sources. Then, the project under test is instrumented according to the distances. During fuzz testing, testing resources are allocated based on seed coverage to test the change points effectively. Using the proposed methods, we implement CIDFuzz as a prototype tool, and experiments are conducted on four open‐source projects that use CI. Experimental results show that, compared with AFL and AFLGo, CIDFuzz can reduce the time costs of covering change points up to 39.59% and 41.64%, respectively. Also, CIDFuzz can reduce the time costs of reproducing vulnerabilities up to 34.78% and 25.55%.

This paper proposes a fuzz testing method for continuous integration, and testing resources are allocated based on the coverage of seeds to test the change points more effectively. Based on the proposed approach, CIDFuzz is implemented as a prototype tool, and experiments are conducted on four open‐source projects that use continuous integration. The results of the experiments show that, compared with AFL and AFLGo, CIDFuzz can reduce the time costs for covering change points reproducing vulnerabilities.image