TY  - EJOU
AU  - Ali, Sadia 
AU  - Hafeez, Yaser 
AU  - Bilal, Muhammad 
AU  - Saeed, Saqib 
AU  - Kwak, Kyung Sup 

TI  - Towards Aspect Based Components Integration Framework for Cyber-Physical System
T2  - Computers, Materials \& Continua

PY  - 2022
VL  - 70
IS  - 1
SN  - 1546-2226

AB  - Cyber-Physical Systems (CPS) comprise interactive computation, networking, and physical processes. The integrative environment of CPS enables the smart systems to be aware of the surrounding physical world. Smart systems, such as smart health care systems, smart homes, smart transportation, and smart cities, are made up of complex and dynamic CPS. The components integration development approach should be based on the divide and conquer theory. This way multiple interactive components can reduce the development complexity in CPS. As reusability enhances efficiency and consistency in CPS, encapsulation of component functionalities and a well-designed user interface is vital for the better end-user's Quality of Experience (QoE). Thus, incorrect interaction of interfaces in the cyber-physical system causes system failures. Usually, interface failures occur due to false, and ambiguous requirements analysis and specification. Therefore, to resolve this issue semantic analysis is required for different stakeholders’ viewpoint analysis during requirement specification and components analysis. This work proposes a framework to improve the CPS component integration process, starting from requirement specification to prioritization of components for configurable. For semantic analysis and assessing the reusability of specifications, the framework uses text mining and case-based reasoning techniques. The framework has been tested experimentally, and the results show a significant reduction in ambiguity, redundancy, and irrelevancy, as well as increasing accuracy of interface interactions, component selection, and higher user satisfaction.
KW  - Cyber-physical systems; component-based development; case-based reasoning; prioritization; requirement management; specification; text mining

DO  - 10.32604/cmc.2022.018779