Collaborative systems enable multiple independent systems to work together towards a common goal. These systems can include both human-system and system-system interactions and can be found in a variety of settings, including smart manufacturing, smart transportation, and healthcare. Safety is an important consideration for collaborative systems because one system's failure can significantly impact the overall system performance and adversely affect other systems, humans or the environment. Fail-safe mechanisms for safety-critical systems are designed to bring the system to a safe state in case of a failure in the sensors or actuators. However, a collaborative safety-critical system must do better and be safe-operational, for e.g., a failure of one of the members in a platoon of vehicles in the middle of a highway is not acceptable. Thus, failures must be compensated, and compliance with safety constraints must be ensured even under faults or failures of constituent systems. In this paper, we model and analyze safety for collaborative safety-critical systems using hierarchical Coloured Petri nets (CPN). We used an automated Human Rescue Robot System (HRRS) as a case study, modeled it using hierarchical CPN, and injected some specified failures to check and confirm the safe behavior in case of unexpected scenarios. The system behavior was observed after injecting three types of failures in constituent systems, and then safety mechanisms were applied to mitigate the effect of these failures. After applying safety mechanisms, the HRRS system's overall behavior was again observed both in terms of verification and validation, and the simulated results show that all the identified failures were mitigated and HRRS completed its mission. It was found that the approach based on formal methods (CPN modeling) can be used for the safety analysis, modeling, and verification of collaborative safety-critical systems like HRRS. The hierarchical CPN provides a rigorous way of modeling to implement complex collaborative systems.

Abstract A large volume of highly diverse and real‐time data provided by social network sites has revolutionized several data analytical sciences such as stock exchange fluctuation prediction, sentiment analysis, and political affiliations prediction. From a software engineering viewpoint, social network sites have produced an unprecedented opportunity for software development organizations to monitor the opinion of the large population of users of their systems. The extracted data from social network sites can be used to extract information about newly launched systems, and it enable software development organizations to obtain rapid technical and social feedback about their systems. This paper presents on a systematic literature review of the published research articles on how requirements engineering (RE) activities are conducted using social network sites, elaborated in studies published between 2011 and 2019. From the resulting studies, we extracted data to answer our four questions related to social network site (SNS)‐based RE approaches focusing on requirements elicitation, prioritization, and negotiation activities. Thirty‐one relevant studies were identified and analyzed to answer our research questions. Among 31 studies, 62% of the studies reportedly support requirements elicitation activity, and 14% of the studies reportedly support requirements elicitation, prioritization, and negotiation activities. Ten percent studies were about requirements elicitation and prioritization activities, 7% of the studies support both requirements elicitation and negotiation activities, and prioritization activity was supported by 7% of the studies. It was also observed that 58% of the selected studies adopted semi‐automatic approaches to conduct RE activities while 21% of the selected studies proposed automatic tools, and 21% of the selected studies adopted manual approaches to conduct RE activities. The outcomes of this systematic literature review indicate that social network sites can be a major source that can be used successfully to extract and identify user requirements. Moreover, this systematic literature review also presents implications of this study for practitioners and researchers including challenges, unresolved issues, and future research directions.

Abstract Large software development organizations manage reusable software components through a reusable software repository in order to reduce development time and cost and to improve software quality and productivity. This paper presents a hybrid DevOps process with a systematic reuse‐based software development and management process to reduce the effort and cost required for the rework and to increase productivity. The proposed approach promotes the systematic reuse of software components based on both information retrieval and ontology‐based retrieval techniques. The reusable assets are presented in different styles to ease and support the reuse process with fine‐grained reusable artifacts. To evaluate our proposed process, a pilot project, aiming to monitor the health of a patient, was developed and monitored the reuse activities throughout the whole experiment. The results revealed that our proposed process got an average gain of 35.2% in terms of developed function points by reusing 30.63% of reusable artifacts available in the reuse repository.

Due to diverse set of heterogeneous computing devices communicating with one another and fusing with physical components in Cyber-Physical Systems, software engineers may use different tools and/or modeling languages to formally describe or verify the system properties. As a result, the integration of these diverse constituents poses key challenges such as task for identifying interactions of components to be synthesized for a function in the systems. Although existing studies such as ontology and integration semantic languages have been used for specifying interactions of components in a Cyber-Physical System, these are still not applicable to discover the component interactions in collaborative Cyber-Physical Systems. It is due to the fact that functionalities of Cyber-Physical Systems are generally realized through interactions among multiple systems in a collaborative environment. This paper proposes a model interaction language, CyPhyML+ which can identify component interactions of realized functions in collaborative Cyber-Physical Systems. We show the proposed approach validity and applicability via an Automatic Incident Detection System.

When defects in safety-critical systems are exposed to actual mishaps, this can lead to property loss, injury, and/or death. Therefore, safety analysis should be performed to identify and minimize potential faults at the design phase of the software development life cycle. However, cyber-physical systems, in which multiple systems are interconnected by the network, may still pose potential risks because the composite analysis of cyber-physical systems is yet to be addressed; even though the hazard analysis for a single system is performed but it is insufficient to analyze hazards for cyber-physical systems. This paper presents an approach to support fault traceability by identifying content relationships among applied hazard analysis techniques to a cyber-physical system. The applied analysis techniques are Fault Tree Analysis, Event Tree Analysis, and Failure Mode and Effect Analysis. In this work, the relationships among these hazard analysis techniques are identified, and a Fault Traceability Graph is designed to represent the relationship among them. Our proposed approach enables to determine the propagation scope of a fault in order to find the source of a fault. Lastly, we propose a Fault Traceability Matrix to trace the faults and to make sure that all faults are controlled by the safety guards. As a result, we can effectively manage and control the faults at the design phase of the cyber-physical system to ensure the development of a safe system. We applied our proposed approach to Automatic Incident Detection System a real case study to show its validity and applicability.