## 2 Materials and Methods
### Related Studies of Smart City's Software  
A smart city is a technology that combines smart technology and smart infrastructure. Smart software plays an important role in integrating these technologies. One part of a smart city is focusing on solving transportation problems such as traffic information analysis, transportation monitoring, public transportation systems, and accident reporting. In particular, a smart city, Sejong, in Korea needs smart software for autonomous traffic systems, pedestrian control systems, and vehicle control systems, which are directly linked to safety issues. These systems must be accurate and perform at the right time. For this, many researchers are conducting various studies on safety, reliability, and performance. In [23], [PERSON] et al. proposed an Internet of Things (IoT)-based traffic control system to overcome the effects of traffic congestion. The proposed system measures the actual traffic density on the road and uses real-time video image processing technology. The system also determines traffic density on both sides of the road and activates the user's software application to control traffic. In [24], [PERSON] et al. deals with the problem of detecting and identifying malicious vehicles CEAP (collection, exchange, analysis, propagation), which is a cluster-based intelligent detection model for malicious vehicles. This model combines support vector machine (SVM) classification and monitoring concepts to optimize the decision-making process. This method uses machine learning techniques of SVM in an incremental and online manner to classify whether or not multi-agent Vehicular Ad-Hoc Network (VANET)'s smart vehicles are cooperative. This method collaboratively collects representative evidence to make an integrated decision, and analyzes the collected data using online SVM. This method can improve the accuracy of detection and the routing process, and then reduce false information. In [25], quality of service optimized link state routing (QoS-OLSR) protocol deals with the VANET clustering problem. Many researchers have proposed several clustering algorithms for VANET and MANETs (mobile ad hoc networks). However, mobility-based algorithms ignore the quality of service requirements that are important to VANET's safety, emergency, and multimedia services. Moreover, because the QoS algorithm is dedicated to MANET, it ignores high-speed mobility constraints. To solve these problems, QoS-OLSR [25] proposed a method of forming a stable cluster and maintaining stability in the event of communication or link failure and satisfying service quality requirements. In [26], [PERSON] claims that performance, security, and safety are necessary because our daily lives are rapidly relying on smart-end systems such as smartphones, wearable devices, and emerging autonomous vehicles. These types of assurance are essential to the design and implementation of software for smart-end systems. The current system lacks the ability to test and verify performance, security, and safety requirements for software against new attempts. Therefore, this study proposes the test method of smart-end systems' performance, security, and safety requirements; detection of important security principles through program analysis; and verification of compliance with safety requirements. These studies are important as a way to solve traffic problems in smart cities. However, each study is slightly different as follows. The work of [23] has developed a system for traffic control. In contrast, [24] and [25] are about the stability and service on the network, which is different from the purpose of our study. In [26], the research is related to the performance, security, and verification of the software in the smart end system, which is like the purpose of our study. However, this research attempts to develop a secure software by testing and verifying the requirements of performance, security, and safety aspects of the smart-end-system.