Department of Computer Science

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Author: search.filters.author.Dr. Tariq UmerSubject: search.filters.subject.Information technology

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    An Empirical Study of SQA Topics in Tester Discussions on Stack Exchange
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Nimra Ikram; SP22-RCS-004; Dr. Tariq Umer; LHR TP 9491
    Software quality assurance (SQA) is becoming more and more well-known all over the world since it is crucial to the reliable and efficient implementation of mobile and web applications. Software test engineers can obtain SQA tools and frameworks like Selenium, Automation, Selenium-web driver, and manual-testing etc. Because of the popularity of SQA, software test engineers routinely discuss SQA related application difficulties on social media platforms such as Stack Exchange (SE). This study attempts to identify challenges encountered by software test engineers during the creation of SQA based apps utilizing the SE data set. Understanding software test engineers talks on SE can provide insights into the amount of time, difficulty, and popularity of SQA based difficulties. Throughout this paper, we gathered 10,593 SE postings discussing SQA difficulties. Topics are identified and arranged into categories and subcategories based on their relationships. Each topic's difficulty and popularity have been examined. Our study showed various findings. Software test engineers highlight five SQA related questions on SE: Testing Techniques, SQA Communication and Collaboration, Software Testing, UI Automation Strategies and Best Practices and Defect Management. Secondly, the topic of Test Coverage Analysis of Test Methodology (Fused_Popularity=4.50) is the most popular in the Testing Techniques topic, followed by Cross Browser and Control Handling in Database Design Testing topic (Fused_Popularity=2.57) within the Software Testing category. Thirdly, SQA based issues across all topics are rapidly expanding on SE, with new queries submitted everyday about testing tools, testing challenges, and acceptance. Fourth, Framework support, Test Automation ,and Selenium Python Web driver Best Practices are the most common categories for 'how' questions. However, many searches in other categories start with 'What'. Fifthly, SE most popular SQA topics are Software Testing (Fused_Popularity=10.8) and UI Automation Strategies and Best Practices (Fused_Popularity=7.0). Sixth, the questions for Testing Technique (Fused_Difficulty = 11.06) and Software Testing (Fused_Difficulty = 4.4) are particularly difficult than the other classification. Our empirical findings could benefit the number of those who are involved: software test engineers, and SQA researchers. Software Test Engineers and researchers can expand their understanding of new ways and create unique techniques for making difficult SQA issues easier to understand
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    A Digital Twin-Assisted Hybrid Decision-Making Model for Autonomous Vehicles Behavior Analysis
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) Hina Saleem; SP22-RCS-005; LHR TP 8682; Dr. Tariq Umer
    This thesis aims to center its attention on the development of a prototype of a Digital Twin that can be utilized for the analysis of autonomous vehicle behavior. The objective of the project was to explore the potential connection and configuration of Digital Twin and Autonomous Vehicles in order to create a visualization-based model for analyzing vehicle behavior. Two methods were employed to establish the connection between autonomous vehicles and a Digital Twin. The first method involved simulating a instinctive model using historical data to recreate scenarios. The second method involved simulating a computational model to incorporate a texture from the physical environment into the DT. In order to initiate the configuration of the DT, Carla was employed to generate states representing the ahead going speed and acceleration of a vehicle, thereby allowing for testing of the OpenModelica models. Additionally, efforts were made to increase the statistics by utilizing Carla as a realistic tool to integrate Autonomous Vehicles with Carla. This thesis introduces a configuration that introduces the concept of the DT being one step ahead of the PT. The PT, which is based on machine learning, was introduced as a means of generating similar parameters to those of a vehicle in a physical environment, thereby allowing for testing of this setting. However, the research did not inspect methods for integrating the same 3D geography in Carla and the machine learning-based simulator, which limited the experiments conducted while the machine learning simulators served as the PT. Furthermore, the statistics between Carla and OM was unable to investigate the concept of reflecting x back action to the PT. Consequently, a second design diagram, based on the knowledge acquired in this project, is presented in the thesis, with the potential for further investigation. In conclusion, this thesis presents a Digital Twin-based methodologies utilized throughout the project establish a strong foundation for future research in the development of a Digital Twin-based model for autonomous vehicles
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    Design and Development of a Trust-based secure Authentication scheme for Internet of Drones (IoD) Networks
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) Fatima Fayyaz; FA21-RCS-004; LHR TP 8674; Dr. Tariq Umer
    Drone advancement is prevailing in the latest trends in various sectors. The concept and deployment of commercial drones can provide services in different fields of life. They can be very beneficial in terms of serving industrial, agricultural, construction, packet delivery, videography, and health care providing services in managing, securing, and broadcasting operations. Diversification of networks and dynamic conditions due to heterogeneousness in types of drones and their ownership, a trust factor between these drones is a very critical issue in their intercommunication. Attacker can easily capture the data from a un-secured public channel and can misuse it against participants. Internet of Drone network protection is very important and challenging, as it ensures message integrity, message authenticity and secure authorization access. The lack of this trust factor has just left the Internet of Drones (IoD) domain exposed to security and privacy threats. The drone nodes can only establish a connection to other drones if they are considered legitimate or corporate (friendly) nodes, the rest of them will not be able to make any connection as they are non-corporate (adversary) or unauthorized. The proposed trust factor is based on a security model that establishes trust by continuous authentication and monitoring access attempts between nodes located in the corporate cluster for data delivery. Hence, a trust-based network authenticated framework is much needed for overcoming these security issues. For achieving secure data decimation and intercommunication it is highly important to create a trust-based, threat-free, environment for IOD networks and to provide the strength to security framework in vulnerable authentication schemes against different type of attacks i.e.; replay and impersonation attack, this paper analyzes the research gaps and proposes a new framework for authentication schemes. Considering the previous proposed factors and techniques, this research focuses on establishing a new architecture for providing secure authentication among Internet of Drones (IoD) environment. This paper presents the more secure framework by mutual authentication and key exchange protocol in IoD with continuous chained Hash Function. System generates temporary symmetric keys to establish connection between two nodes, hence devices can mutually authenticate and establishes connection in an untraceable manner. For the verification of sender identity, chained-hashed way is presented. Session keys between devices are updated after every transaction to maintain secrecy. The evaluation of cost and effectiveness of the proposed method with previous protocol are computed. The outcomes demonstrated that our techniques are more secure than previous frameworks.
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    Data Driven Vehicular Heterogeneity based Intelligent Collision Avoidance System for IoV
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2022) Iqra Adnan; SP21-RCS-004; LHR TP 8056; Dr. Tariq Umer
    The Internet of Vehicles (IoV) is becoming a trending field of research for researchers. Its implementation in the real world is increasing day by day to facilitate drivers in driving and provide safe road conditions to travelers to be safe from accidents. Many research studies on IoV focused on the issue of collision avoidance between vehicles on the road. Companies like the world’s biggest car company TESLA use IoV and certain machine learning algorithms to make their cars autonomous. Keeping in view the importance of collision avoidance issues between vehicles on the road. Our proposed work is to perform an analysis of real-life vehicular data based on the characteristics of different types of vehicles moving on the roads. Due to the heterogeneousness of the types of vehicles (cars, buses), their parameters are also different. From the vehicular data based on this heterogeneousness, we intended to find out the different parameters’ roles for the collision avoidance system. Using the capabilities of machine learning techniques on the gathered data, a framework for the collision avoidance system is suggested for vehicles on the roads. Performance analysis of the framework for predicting the accident well before the time for the drivers is presented for better road conditions.