Browsing by Author "YAZICI, Ali"
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Item A COMPARISON OF SQL AND NoSQL DATABASES(2022-02-25) RASHD, SOUAD RASHD ALİ; YAZICI, AliThis study comprises a research about both SQL and NoSQL databases and a comparison in terms of the advantages and disadvantages of each. The comparison is implemented depending on scalability, (ACID and CAP) theory, flexibility, performance, schema, query language, cost, speed and the stored data. We described briefly several examples of SQL databases including My SQL , MS-SQL Server Express Edition , Oracle 11g Express Edition Database. Also, the study included a description for many types of NoSQL database including Key-Value Store Database, Column-Oriented Database, Document Store Database and Graph Databases. The result of the study detected that SQL database is a table based database, supports flexibility, is vertical scalable, and utilizes Structured Language Query. On the other hand, the study discovered that SQL database is not a suitable choice for hierarchical data storage, etc. Whereas in terms of NoSQL, the study discovered that NoSQL databases are less flexible, however, horizontally scalable, have a non-structured querying language and is a good choice for hierarchical databases.Item A NEW METHOD FOR SOFTWARE DEFECT PREDICTION BASED ON OPTIMIZED MACHINE LEARNING TECHNIQUES(2022-03-01) HASSEN, SHAHO ISMAEL HASSEN; YAZICI, Ali; MISHRA, AlokIn this thesis a novel and robust heuristic driven neuro-computing model was developed for software defect prediction. Unlike other classical machine learning models, neuro-computing, especially Levenberg Marquardt Neural Network (LM ANN), is considered to be more robust in terms of adaptive learning, which can be vital towards non-linear feature learning and hence defect data. However, similar to the other machine learning models, the likelihood of local minima and convergence could not be avoided due to exceedingly high weight estimation for 17 input features. Considering this fact, this research contributed a novel improved genetic algorithm, say heuristic model was developed to assist ANN for adaptive weight estimation and update during learning. Here, the key purpose of heuristic model was to help LM-ANN gaining superior weight estimation, update and hence learning without undergoing any local minima and convergence problem. This as a result helped the proposed neuro computing model to achieve higher accuracy than the classical neural network over targeted software fault datasets. In addition to the classifier or machine learning improvement, in this research the focus was made on feature engineering as well that helped alleviating any probability of class imbalance, over-fitting and convergence.Item A STUDY OF DEVOPS ADOPTION IN SOFTWARE DEVELOPMENT ORGANIZATIONS: QUALITY, PRODUCTIVITY, AND SECURITY PERSPECTIVE(2023-01-30) OTAIWI, Ziadoon Abdullah; YAZICI, Ali; MISHRA, AlokThese days, many software organizations are competing with each other to rapidly develop and deliver high-quality, reliable software. DevOps is the Development (Dev) and Operation (Ops) methodology in software development organizations and has become one of the favored methodologies in many leading companies; consequently, many organizations want to adopt this methodology. However, adopting DevOps in the software industry is a big challenge because it requires new tools, technologies, methods, culture, and experienced work teams to design reliable and deployable applications. Most of the current academic research surrounding DevOps seeks answers for how to adapt to this new methodology and how to improve performance in the organization; its focus is on velocity, quality, and productivity to produce these applications. This study aims to conduct an empirical study to fill the research gaps related to quality, productivity, and security issues in implementing the DevOps methodology in organizations. This quantitative study found that software quality, productivity, and security are improved when DevOps was adopted following the CALMS (Culture, Automation, Lean, Measurement, and Sharing) framework. However, according to quantitative data collected, there are some challenges and negative impacts on security when DevOps is adopted. This study also proposes the development of best practices, recommendations, and a model to facilitate the adoption of DevOps in organizations.Item AGILE SOFTWARE MAINTENANCE AND DEVELOPMENT USING CLOUD COMPUTING FRAMEWORK(2023-01-26) ALMASHHADANI, Mohammed; YAZICI, Ali; MISHRA, AlokAgile methods have emerged to overcome the obstacles faced in traditional software methodologies, such as the Waterfall, Prototype, Spiral, etc. There have been many studies that show the numerous features of the Agile methodologies, making them useful for software development. However, many studies have also proposed a framework to adapt the Agile methods to Cloud Computing to leverage the benefits from this environment. The existing studies focus on the adaptive development life cycle for Agile with the Cloud, but have so far been unable to include the maintenance process in a detailed manner. Among these attempts and as further contribution, the present work intends to introduce Agile software maintenance and development using Cloud Computing framework (ASMDCC) as a reference for developing software with the Cloud in respect of maintenance activities. The case study findings reveal that the combination of Agile with Cloud Computing can resolve the major issues faced in traditional software maintenance, making the role of this approach significant in globally/distributed software maintenance. Furthermore, it is shown that Cloud Computing services play a vital part in resolving software maintenance. Finally, the results indicate that using the ASMDCC framework improves the challenges faced by the maintenance team compared to the traditional environment regarding management, infrastructure, collaboration, and transparency.Item CLOUD COMPUTING SECURITY ISSUES AND SELECTION OF DEPLOYMENT MODEL AND SERVICE MODEL ACCORDING TO SECURITY REQUIREMENTS(2015-01-31) SEZEN, Arda; YAZICI, Ali; BOSTAN, AtilaThis thesis reviews the necessity of X.800 Recommendation service categories for different cloud service models and cloud deployment models together with some security solution approaches in cloud computing. The thesis evaluates the solution approaches to show that technical and non-technical approaches need to be handled together to produce comprehensive solutions. Six technical solution approach have been included to evaluate the fulfilment of X.800 Recommendation service categories. Eventually, twelve hypotheses have been formulated, tested, and accepted based on the survey data to understand the necessity of X.800 Recommendation service categories for different cloud service models and cloud deployment models.Item COMPARISON OF SCHEDULING USED IN BIG DATA FRAMEWORKS(2022-02-24) Aljumaili, Saif; KARAKAYA, Ziya; YAZICI, AliBig Data applications have grown to become one of the main ingredients in the current information technology sector, providing an opportunity for decision-makers to achieve best outcomes, for instance in commerce and business. However, the speed at which such data gathering occurs varies in storage, management, and processing, in all of which the traditional database systems cannot handle such tasks as massive data collection. Resource management and task scheduling play an essential role in Big Data processing. There are different classifications of schedulers that are based on their different features, effectiveness, performance, and so on. However, in this thesis we classify, compare and investigate the detailed information associated with several schedulers being employed in Big Data frameworks. Moreover, this thesis identifies the weakness and strengths in different use cases of these schedulers. Furthermore, the study examines scenarios for the suitability of use cases so as to determine in which case the individual scheduler has some weakness or useless. Thus, these issues we cover in this thesis are not studied in the existing studies.Item DESIGN AND IMPLEMENTATION OF A PARALLEL BOUNDARY ELEMENT METHOD SOLUTION FOR 3D PARTICLE FLOW PROBLEMS IN MICROCHANNELS(2015-01-30) KARAKAYA, Ziya; BARANOĞLU, Besim; YAZICI, AliA new formulation for tracking multiple particles in slow viscous flow for microflu idic applications is presented. The method employs the manipulation of the boundary element matrices so that a system of equations is obtained relating to the rigid body velocities of the particle to the forces applied on the particle. The formulation is spe cially designed for particle trajectory tracking and involves successive matrix multi plications for which Symmetric Multiprocessing (SMP) parallelisation is applied. It is observed that the present formulation offers an efficient numerical model to be used for particle tracking and can easily be extended for multiphysics simulations in which several physics are involved.Item GENERATING CLASS DIAGRAMS FROM SOFTWARE REQUIREMENTS IN TURKISH USING NATURAL LANGUAGE PROCESSING(2022-01-17) Demir, Fatih; TURHAN, Çiğdem; YAZICI, AliIn software engineering, designing software that meets its requirements is a challenging task. In order to assist software engineers in this difficult task, many systems have been proposed in the literature that automatically generate class diagrams from software requirements. However, most of those studies are for software requirements in English, and such studies are very few for software requirements in Turkish. In this study, a system that automatically generates UML class diagram from software requirements in Turkish is proposed. The system first analyzes software requirements using natural language processing tools, particularly the dependency parser tool. Then, this parsing result is processed by a rule-based system and the classes, attributes and methods of the classes as well as the relations between classes are extracted. The extracted items are transformed into a class diagram with the visualization tool. Promising results were obtained when the performance of the system was evaluated. Therefore, it is concluded that class diagrams can be generated using natural language processing tools, especially the dependency parser, from software requirements in Turkish.Item NOVEL SOFTWARE DEFECT PREDICTION METHOD BASED ON PCA AND OPTIMIZED LSTM(2022-01-10) AL-OBAIDI, ANMAR SADEQ JASIM; MISHRA, Alok; YAZICI, AliIn this thesis, new approach presented for software defect prediction applying PCA based LSTM. This study consists from two parts feature selection executed by PCA and classification part executed by LSTM. The aim applying PCA as feature selection is to reduce the size of input features to decrease the computation time by removing unaffected features. Then, the output of PCA wired to the LSTM that is time series classifier which classify the input software defect features to the two classes (defect and normal). The PSO applied to optimize the performance of the LSTM by updating the weight and basis of the LSTM to obtain best accuracy. The obtained results compared with common studies presented in this field.Item PRIORITIZING USE CASES FOR DEVELOPMENT OF MOBILE APPS USING AHP: A CASE STUDY IN TO-DO LIST APPS(2022-01-26) Yıldırım, Onur; PEKER, Serhat; YAZICI, AliThe intensity of use of mobile applications has increased significantly with the rapid development of communication technologies. Every day many different types of To-Do apps are uploaded to mobile application markets. However, it is very difficult for the apps to stay competitive and survive in these marketplaces. One of the success factors in the mobile application market is the functionality of mobile applications. Identifying the functions of the application is very important for mobile application developers. In this manner, this study aims to prioritize to the functionalities of mobile apps. For this purpose, Analytic Hierarchy Process (AHP) is used to assess the use cases for the development of mobile apps. The results of case study applied in to-do list apps show that AHP can be used as an efficient tool to determine the importance of the requirements in mobile apps.Item RETURN ON INVESTMENT IN TEST AUTOMATION VIA SELENIUM(2022-01-24) ATEŞOĞULLARI, Dilara; YAZICI, AliThere are multiple approaches to software testing. One of these approaches, the subject of test automations, differs in theory and practice. The Return on Investment (ROI) calculations should be used to determine which automation tests are the most suitable for the given project. In this study, the manual and automated test results of test runs, which are suitable for server test automation, are calculated according to a certain formula. Based on the result of this calculation, our aim is to ensure that the selected test automation tests are suitable for return of investment. In the light of all these, the main subject of this study is to perform ROI studies in terms of test automation tests.Item Romberg Integration: A Symbolic Approach with Mathematica(2003-08-08) YAZICI, Ali; ERGENÇ, Tanıl; ALTAŞ, İrfanHigher order approximations of an integral can be obtained from lower order ones in a systematic way. For 1-D integrals Romberg Integration is an example which is based upon the composite trapezoidal rule and the well-known Euler-Maclaurin expansion of the error. In this work, Mathematica is utilized to illustrate the method and the under lying theory in a symbolic fashion. This approach seems plausible for discussing integration in a numerical computing laboratory environment.Item THE OBSTACLES FACING THE IMPLEMENTATION OF E-GOVERNMENT SERVICES : AN EMPIRICAL STUDY FOR LIBYA(2022-02-28) Elsteel, Nouryah Omar Salim; YAZICI, AliThis study focuses on the rise of e-government services, specifically considers Libya as an example on its efforts and challenges with respect to implementing of an e-government services initiative. E-government services represent a fundamental transfer in the design and methods of government efficiency, responsibility and commitment. However, Libya in particular seems to face steep and unique challenges when it comes to the implementation of e-government services. The country often seems to lack sufficient resources, infrastructure, and know how to implement a large scale e-government services project.Furthermore, a large number of the Libyan population often have little contact with computers and the internet , and may be distrustful of technology and their government. Primarily, this study aims to clarify the challenges and suggest strategies to overcome them.Item USE OF OPTIMIZATION TECHNIQUES FOR HEALTH PREDICTION(2022-01-20) Malik, Muhammad Sufyan; YAZICI, Ali; Khan, M. UmerIn today's world, the usage of modern technology has brought many advancements in the field of medical science. Still, with all the advancements, the diagnosis and treatment of most diseases are considered a challenging task. Diabetes ailment has been studied more for tackling the symptoms rather than investigating the diagnosis in its early stages. The combination of resistance to insulin and insulin emission deficiency produces type-2 diabetes. Diabetes Mellitus Type-2 is high penetrance and still increasing around. However, the identification of DMT2 is a dilemma. If the DMT2 can be identified at an early stage, fewer preventive measures would be required, and the person can still lead a healthy and carefree life. There exist many health prediction systems in health sectors using data mining techniques. Optimization techniques are capable of providing more precise and efficient results as well. In this research study, Least squares, Quadratic programming, and Lagrangian Method are used with convex optimization to find the classification accuracy and the comparison between existing classifiers such as SVM, DT, LR, and so forth. This research demonstrates that optimization techniques can be used to envisage or diagnose health disease and can provide better results compared to other classifiers.