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Morkūnas, Balys (author)
A number of Machine Learning models utilize source code as training data for automating software development tasks. A common trend is to omit inline comments from source code in order to unify and standardize the examples, even though the additional information can capture important aspects and better explain algorithms. We claim that models,...
bachelor thesis 2022
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Mouman, Nada (author)
Machine learning (ML) algorithms have been used frequently in the past years for Software Engineering tasks.<br/>One of the popular tasks researchers use is method name prediction, which helps them generate an identifier for methods with ML models such as Code2Seq.<br/>This model represents code snippets as Abstract Syntax Trees (AST) and...
bachelor thesis 2022
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Bacevičius, Vidas (author)
AI-assisted development tools use Machine Learning models to help developers achieve tasks such as Method Name Generation, Code Captioning, Smart Bug Finding and others. A common practice among data scientists training these models is to omit inline code comments from training data. We hypothesize that including inline comments in the training...
bachelor thesis 2022
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Stranski, Ivan (author)
Software testing is essential for a successful development process, however, it can be troublesome as manually writing tests can be time demanding and error-prone. EvoSuite is a test case generating tool developed to address this [18]. It can generate test cases for different test criteria - Line Coverage, Branch Coverage, Input Diversity, etc....
bachelor thesis 2022
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Toader, Daniela (author)
The perpetual desire for more qualitative software has been an excellent incentive for software engineers to create automated tools to ease and improve the process of software testing. EvoSuite is an example of a state-of-the-art tool that synthesises test cases automatically. It uses a genetic algorithm to produce test cases based on given...
bachelor thesis 2022
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Dimitrov, Stoyan (author)
To ensure that a software system operates in the correct way, it is crucial to test it extensively. Manual software testing is severely time-consuming, and developers often underestimate its importance. Consequently, many tools for automatic test generation have been developed during the past decade. EvoSuite is a state-of-the-art tool for...
bachelor thesis 2022
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Kling, Toon (author)
Recently, automating test suite generation is a problem that has drown attention in both industry and academia. One of the tools used to automatically generate test suites is EvoSuite, which is a state-of-the-art tool often used in research. It uses a genetic algorithm, which seeks to maximize certain coverage criteria, such as Branch Coverage...
bachelor thesis 2022
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Scholman, Renzo (author)
Even if a Multi-modal Multi-Objective Evolutionary Algorithm (MMOEA) is designed to find all locally optimal approximation sets of a Multi-modal Multi-objective Optimization Problem (MMOP), there is a risk that the found approximation sets are not smoothly navigable because the solutions belong to various niches, which reduces the insight for...
master thesis 2022
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Veraart, Maartje (author)
The rise of alarming cyber breaches and cyber security attacks is causing the world to consider the security of our cyber space. A Security Operations Center (SOC) is a center where the security of a company is monitored to prevent cyber breaches. Security analysts in the SOC examine alerts that come from different devices and analyse what is...
master thesis 2022
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Athmer, Casper (author)
The Train Unit Shunting and Servicing (TUSS) problem is an NP-hard problem encountered by the Dutch railway operator, Nederlandse Spoorwegen (NS). It considers trains at a shunting yard when they are not transporting passengers. It consists of four subproblems, involving assigning the trains at the yard to a transporting timetable (Matching),...
master thesis 2021
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Symeonidis, Pandelis (author)
System behavior models are highly useful for the developers of the system as they aid in system comprehension, documentation, and testing. Even though methods to obtain such models exist, e.g. profiling, tracing, source code inference and existing log-based inference methods, they can not successfully be applied to the case of large, real-time...
bachelor thesis 2021
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Bobde, Sharwin (author)
Using Recommender Systems with Evolutionary Algorithms is an extremely niche domain. It holds the key to enabling new user interaction designs, where users can effectively configure their experience with a Recommender System. This thesis answers important questions about the scientific aspects of its application to large-scale data through a...
master thesis 2021
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Werthenbach, Thomas (author)
An essential step of software development is obtaining an understanding of the behaviour of a system. Accurate state models of system behaviour might help software developers build such an understanding. There exist several techniques for automatically inferring models on system behaviour using log analysis, but these do not scale well for...
bachelor thesis 2021
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Georgescu, Calin (author)
Understanding the behaviour of a software system plays a key role in its development and maintenance processes. Unfortunately, accurate and concise models are not always available during development, due to the rapid changes in the structure and scale systems may undergo during this phase. Finite State Machines (FSM) are a natural and prevalent...
bachelor thesis 2021
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Brandirali, Tommaso (author)
Large software systems today require increasingly complex models of their execution to aid the analysis of their behavior. Such execution models are impractical to compile by hand, and current approaches to their automated generation are either not generalizable or not scalable enough. This paper addresses this problem with a new approach based...
bachelor thesis 2021
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de Hoog, Dion (author)
In this research, we use different supervised and unsupervised machine learning techniques to detect anomalies in NetFlow data. We aim to create a system for home or small-business use where the user is in control. We use WEKA for the machine learning models and feature selection. The UGR’16 dataset is used to train and test the models. We...
master thesis 2021
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Bisesser, Dinesh (author)
An increasing digital world, comes with many benefits but unfortunately also many drawbacks. The increase of the digital world means an increase in data and software. Developing more software unfortunately also means a higher probability of vulnerabilities, which can be exploited by adversaries. Adversaries taking advantage of users and software...
master thesis 2020
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Cao, Clinton (author)
The Internet is a technology that was invented in the 1960s and was used only by a few users to do simple communications between computers. Fast forward to 2020, the Internet has become a technology that is being used by billions of users. It allows users to communicate with each other across the world and even allows users to access data...
master thesis 2020
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Serentellos, V. (author)
Computer networks have nowadays assumed an increasingly important role in the expression of modern human activity through the ongoing rapid development in the field of Information and Communication Technologies (ICT). More and more individual users and businesses around the world are gaining access to networks online, while the range of services...
master thesis 2020
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Mostert, C. (author)
High-level music classification tasks such as automatic music mood annotation impose several challenges, both from a psychological and a machine learning point of view. Ground truth labels for these tasks at hand are hard to define due to the abstract and aesthetic nature of the data, being largely dependent on human psychology and perception....
master thesis 2020
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