Twitter is currently one of the most popular microblogging platforms allowing people to post short messages, news, thoughts, and so on. The Twitter user community is growing very fast. It has an average of 328 million active accounts today, making it one of the most common media for getting information during any influential or important event. Because it is freely used by the public, some credibility checking is required, especially when it comes to events of high importance. Automatic rumor detection in Arabic tweets is a challenging task due to the changes in the structural and morphological nature of the Arabic language, which makes the detection of rumors more difficult than in other languages. In this article, we proposed an effective approach for rumor detection of Arabic tweets using an eXtreme gradient boosting (XGBoost) classifier. We conducted a set of experiments on a public dataset that contained a large number of rumor and non-rumor tweets. The model uses a comprehensive set of features, including content-based, user-based, and topic-based features, allowing one to look at credibility from different angles. The experimental results demonstrated that the proposed XGBoost-based approach achieves 97.18% accuracy on 60% of the dataset as a training set, which is the highest accuracy rate compared with the other methods used in recent related work.

Body Sensor Networks (BSNs) is the emerging driver to revolutionize the entire landscape of the medical field. However, sensor-based handheld devices suffer from high power drain and limited battery life, due to their resource-constrained nature. Hybridization of different energy control methods and protocol layers is a best approach to enhance the performance perimeters for smart and connected healthcare. Thus, this paper mainly contributes in two ways. First, adaptive duty-cycle optimization algorithm (ADO), is proposed which optimizes the active time by considering the specific power level which leads to more energy saving instead of increasing the sleep period unlike the traditional methods. Second, joint Green and sustainable healthcare framework is proposed. Extensive theoretical and experimental analysis is performed by adopting real-time data sets with Monte Carlo simulation in MATLAB, and it is revealed that proposed algorithm enhance reliability and energy saving by 24.43%, 36.54%, respectively. Thus it can be said that proposed algorithm have more potential for energy constrained sensor devices in smart and connected healthcare platform.

Abstract Software industry is adopting global software development (GSD) due to its potential to produce quality products at a lower cost. However, the GSD firms face many challenges that make development activities more complicated, especially related to the requirements engineering (RE) process. The objectives of this article are to investigate and prioritize the barriers faced by the GSD organizations during the RE process. First, we identified 17 barriers related to the RE process in the GSD projects. Next, the identified barriers were further validated with real‐world GSD practitioners using a questionnaire survey. Finally, we applied the analytical hierarchy process to prioritize the investigated barriers with respect to their significance for the RE process in the GSD domain. The results show that coordination is the most significant barrier category for the RE process in GSD projects. Lack of standard and procedure for RE in GSD, lack of synchronized communication infrastructure, and lack of mutual understanding between the overseas RE teams are also high‐ranked barriers for the RE process in GSD. The authors believe that the findings of this study will assist practitioners and researchers in developing effective strategies and plans for the successful implementation of the RE process in the GSD context.

Abstract Managing the cloud‐based software development outsourcing (CSDO) activities across the geographically distributed development sites are much challenging. This study aims to identify the success factors (SFs) for CSDO and prioritize them based on their significance. To achieve this objective, we conducted a systematic literature review (SLR) and survey study with industrial and academic experts. Finally, we applied the analytical hierarchy process (AHP) to develop the framework based on the prioritization of the identified SFs. We believe that the findings of this study will assist the industry practitioners and researchers in developing effective strategies for the successful implementation of CSDO activities.

Abstract Planning and managing of requirement change management (RCM) process in global software development (GSD) are a complicated task, but the RCM plays a significant role in developing the quality software within time and budget. The key aim of this study is to prioritize the factors that could positively influence the RCM program in GSD context. To achieve the study objective, the questionnaire survey study was conducted to get the feedback of the practitioners concerning the success factors of RCM in GSD context. Moreover, the fuzzy analytical hierarchy process (FAHP) was applied. The application of FAHP is novel in this research domain as it has been effectively applied previously in various other research areas, for example, supplier selection, electronics and electrical, personnel selection, and agile software development. The results of this study will provide the prioritization‐based taxonomy of RCM success factors and also contribute by introducing the novel FAHP approach in the research domain of RCM in GSD. The FAHP approach assists the practitioners to reduce the uncertainty and vague opinions of RCM experts.

Abstract DevOps is a new software engineering paradigm adopted by various software organizations to develop the quality software within time and budget. The implementation of DevOps practices is critical, and there are no guidelines to assess and improve the DevOps activities in software organizations. Hence, there is a need to develop a readiness model for DevOps (RMDevOps) with an aim to assist the practitioners for implementation of DevOps practices in software firms. To achieve the study objective, we conducted a systematic literature review (SLR) study to identify the critical challenges and associated best practices of DevOps. A total of 18 challenges and 73 best practices were identified from the 69 primary studies. The identified challenges and best practices were further evaluated by conducting a survey with industry practitioners. The RMDevOps was developed based on other well‐established models in software engineering domain, for example, software process improvement readiness model (SPIRM) and software outsourcing vendor readiness model (SOVRM). Finally, case studies were conducted with three different organizations with an aim to validate the developed model. The results show that the RMDevOps is effective to assess and improve the DevOps practices in software organizations.

The economic and strategic gain attracts the software industry to adopt the global software development (GSD) phenomenon. Besides the significant advantages, the GSD firms also face certain critical challenges mainly related to security and management perspective. Blockchain is the new revolutionary technology that offers over the globe secure storage via distributed databases. The objective of this study is to investigate how the adoption of blockchain is beneficial for the GSD project. We have conducted interviews with academic researchers and case studies with industry practitioners to identify the impact of blockchain on GSD projects. We have identified ten key critical areas of GSD the effectively addressed by using the blockchain technology in GSD context. A comparative analysis is conducted with the finding of academic researcher and industry practitioners, and the results ((W=0.86, p=0.005) shows that there is a strong agreement between the understanding of academic researchers and industry practitioners. Besides, we have developed a hypothetical model based on the findings of both studies that shows the positive relationship of blockchain implementation in the GSD domain. We believe that the findings of this study will encourage the practitioners and researchers to develop the new plan and strategies for the adoption of blockchain in GSD.

Abstract Software development is a complex task, and the introduction of multi‐site development teams spread across the globe makes it even harder. Requirement changes during the software development process are inevitable, and failing to manage evolving requirements is one of the contributors to project failures. Requirements change management (RCM) becomes difficult in global software development (GSD) projects due to the need to communicate and coordinate between stakeholders in a distributed environment. This research work aims to identify the factors that have positive impacts on RCM activities in GSD. We conducted a multi‐vocal literature review (MLR) and a questionnaire survey study to identify the RCM success factors. The results of the t‐test (ie, t = 0.0347 and P = .700 > .05) and correlation (rs (25) = 0.573, P = .003) indicates that there is no significant difference between the findings of MLR and the questionnaire survey. The identified factors were further analyzed in the context of client and vendor organizations to better understand the RCM success factors in both types of GSD firms. The findings of this study can provide a useful framework for tackling problems associated with RCM in a GSD environment that is significant to the progression of GSD firms.

The trustworthiness of an industrial Internet of Things (IIoT) network is an important stakeholder expectation. Maintaining the trustworthiness of such a network is crucial to void the loss of lives. A trustworthy IIoT system combines the security characteristics of IT trustworthiness-safety, security, privacy, reliability, and resilience. Conventional security tools and techniques are not enough to safeguard the IIoT platform due to the difference in protocols, limited upgrade opportunities, mismatch in protocols, and older versions of the operating system used in the industrial system. In this article, we propose to improve the trustworthiness of an IIoT network [i.e., supervisory control and data acquisition (SCADA) network] through a reliable and salable cyberattack detection model. In particular, an ensemble-learning model based on the combination of a random subspace (RS) learning method with random tree (RT) is proposed for detecting cyberattacks of SCADA by using the network traffics from the SCADA-based IIoT platform. The novelty of the proposed model is that it uses the industrial protocol-based network traffic and the RS to solve the sensitivity of irrelevant features and ensemble RT to reduce the overfitting problem, thereby constructs a detection engine based on industrial protocols and achieves high detection rates. The proposed model has been tested over 15 datasets of the SCADA network. Experimental results reveal that the proposed model outperforms conventional detection techniques and, thus, improves the security and related measure of the trustworthiness of the IIoT platform.