20+ Best Computer Science Dissertation Topics
In the following piece, you will find a list of computer science dissertation topics. The topics in this list are in random order and can be used as a guide to come up with a topic for your own proposal. If none of these ideas appeal to you, read “Selecting Computer Science Dissertation Topics” for more information on how to choose a good topic. Get 20+ Best Computer Science Dissertation Topics from our compilations below. You can hire us to write your paper.
Simulation of programs that extract information from HTML pages is one of the most important tasks in computer science. In this area, there is a branch called Web Data Mining which studies algorithms that extract data from HTML pages using structured query language (SQL) or programming languages such as Java, Perl, and Python.
In this dissertation topic we focus on simulating these programs, which can be used to encode existing programs in natural language, to test existing programs in natural language, and to generate HTML pages programmatically. The main goal of this dissertation is to find out which part of the process is more challenging: parsing HTML documents, extracting information from them, or generating new ones.
- “Topics related to encoding SQL queries using Natural Language”
- “Topics related to encoding programs in natural language”
- “Topics related to generating HTML pages programmatically”
Time series prediction problem is of great importance for many areas such as finance, ecology, and medicine. On the other hand, it has become more challenging because of increasing number of time series available on the internet.
In a more general sense, it is possible to compile almost all modern programming languages on a modern CPU.
However, the academic community has not yet explored this topic in-depth. Here are some ideas for further investigation:
- Write a JIT compiler for a Scheme dialect, which could include Racket or any other Scheme with sufficient performance.
- Compile Python to x86-64 machine code and compare it to the PyPy project (which only interprets Python).
- Implement a Ruby compiler that can perform JIT compilation into machine code; this would be similar in difficulty to the above, but much more work is already
Algorithms and data structures for program analysis and transformation are critical for the success of modern programming languages. Program analysis is crucial to improve existing compilers, debugging tools, optimizers,
Program transformation enhances program structure and speed up computations by re-writing or transforming programs in a high-level functional language used as an internal representation. It opens new perspectives for program optimizations and even whole domain specific languages.
Program analysis and transformation have a large overlap in the problems addressed, so not surprisingly, much research has been done in both areas simultaneously. Current compilers for functional languages are mostly based on combining static program analysis with simple transformations. The complexity of these tools is due to the fact that features such as higher order functions, type inference or laziness have to be supported in a way that is compatible with the tool.
In the last years, several new ideas have been proposed in both areas by researchers from various backgrounds ([PLDI’08] [MICRO’10] [ICFP’11]). The combined results of these research trends require a much richer language for program analysis and transformation.
Many methods for measuring software quality exist today. However, these existing methods have their own shortcomings and limitations. In this thesis we propose a new framework called \’community-based software quality assessment\’. The framework is based on the assumption that if people appreciate it, they will be more willing to use software products. We also assume that by being used, the software product will become better. The framework is composed of six sub-models which are used to assess software quality. Each sub-model consists of a series of hypotheses that together represent how people perceive the quality of computer products.
This area of research deals with the development of compilers that convert high-level programming languages into low-level programming languages. High-level languages are easy to use for humans, but in order to be executed by a computer, they must be converted into a lower level language, which is easier for the machine to understand.
Compilers are used because it is often easier to write a compiler for a high-level language than to develop the software directly in machine code. These compilers are designed to be able to take advantage of special hardware or any other programs that might already exist, because this speeds up the execution time.
One topic of research involves static program analysis. This is where we try to estimate the resource requirements of a program without actually executing it. This is important because we want to know how much resources a program will use before downloading and installing it on the computer.
Multi-resolution algorithms are used in many different fields. Multiresolution techniques have applications in image processing, medical imaging, movies and other entertainment mediums, simulation tools for physical systems, data compression, information retrieval and word recognition, etc.
Computer Graphics is a very diverse field of study that includes topics such as how to generate 3D models for real-time games, how to generate 2D images using pixel shaders or ray tracing, the design of 3D modeling tools, etc.
Computer graphics is necessary for applications such as video games, virtual worlds and movies. For example imagine playing a game without seeing what it’s like to explore wilderness landscapes! Without computer graphics many entertainment mediums would not exist.
Rapid development in 3D graphics has resulted in the need for efficient rendering algorithms, requiring detailed knowledge of computer science programming languages to implement them. Researchers are trying to improve 3D graphics by making it more realistic and physically accurate.
Distributed computing is the process of using multiple computers to solve one problem. The research area includes research into distributed system theory, design and implementation. Issues include fault-tolerance (especially the end-to-end arguments), concurrency (including atomic transactions and transactional memory), consistency (in particular eventual consistency, which studies how the global state of a distributed system can be updated despite the possibility of computer failure), distributed naming, coordination languages, replication methods (for improving availability and performance) research into specific algorithms for distributed systems, etc.
Numerical methods for solving linear algebraic equations. e.g. singular value decomposition, iterative refinement techniques
This research dissertation topic is very broad and can lead you to specific research topics that would be great research dissertation topics. For example, “Numerical methods for solving linear algebraic equations using the method of successive approximation.”
A data mining architecture using parallelism and multiple knowledge sources for fraud detection in credit card transactions
This research aims to discover computer science dissertation topics that will provide scholars with a clear direction in their research. With the research done by these scholars, they can then proceed to publishing their research in well-respected journals and have a high chance of getting published. Their research can be used to better mankind in different ways, from exposing cybercrime to improving Internet search engines.
Data mining, as defined by the National Institute of Standards and Technology (NIST), is research on algorithms, architecture, modeling and other areas that combine to help analysts extract useful information from a large dataset. Some research has been done in this field with regards to commercial credit card transactions. However, a research that focuses on expanding research to multiple knowledge sources and parallelism will help the research community in designing new systems that can better detect credit card frauds.
A research done in this area is seen as a research paper and it should be submitted in an academic journal to ensure thorough review and peer evaluation of the research. It should also follow ethical research guidelines, such as research that uses the research data properly and is free of plagiarism. It should also be written in a professional manner and structured according to standard research paper formats.
Quality of service (QoS) mechanisms are key to assuring the quality of computer services. QoS is particularly important when one considers cloud computing, where multiple distributed resources are aggregated in order to provide services over the Internet. A research area that has emerged to address this need for assuring QoS is Web service management under QoS constraints.
Research in this area focuses on how to reason about the different QoS requirements of each component in an overall system, taking into account their interdependencies; how to ensure that these components are monitored and controlled; and finally how to adjust resource allocation when changes occur (e.g., node arrivals or departures, workload changes).
This research tends to be at a theoretical level and so research in this area is largely research into algorithms for solving problems. However, there are a number of opportunities here. For example, research could also look at the ‘best practices’ to follow when developing systems within this context – e.g., what design patterns (e.g., the client-star pattern) would best handle such research.
Conduct research on research topics such as distributed transaction processing, replicated and distributed databases, advanced concurrency control protocols for large-scale transactional systems.
Research dissertation topics such as research in research areas such as research data management or research in research areas such as research data management or semantic web technologies
Conduct research on mixed-integer linear programming, a class of mathematical optimization problems popular in operations research and combinatorial optimization. Research areas include the development of approximation algorithms, heuristics, metaheuristics, exact algorithms, and research.
Mixed-integer linear programming; mixed integer linear programming; mixed integer programming; polynomial time algorithm; approximation algorithm; heuristic algorithm; branch-and-bound method; branch and bound method; branch & bound method.
There has been a growing concern among online users about the safety and privacy of their personal information, especially when it comes to e-commerce transactions. The research area focuses on the research through which we could provide an end-to-end solution that can help in authenticating and securing e-commerce transactions.
This research area focuses on the research through which we could provide an end-to-end solution that can help in authenticating and securing e-commerce transactions. This research area is closely related with the research work being carried out in cryptography research, which deals with the techniques of securing.
The research community has witnessed many research dissertations related to the research of Program Transformation Systems. PTSs are software systems that help programmers in transforming a source program into another target program identical or equivalent to the original source. They are classified into three major types namely, refactoring, rewriting, and super-type/sub type relations and their research has been a focus of research for both research scholars and research students for over 30 years. They provide computer programmers with the flexibility to change how a program is written without changing its behavior or other programs that depend on it.
An analysis of the main models of parallel computer organization with emphasis on their computational power
What is a parallel computer organization?
A set of elements which are capable of executing several operations simultaneously.
What research problem is this research addressing?
The research will provide an analysis on the main models of parallel computer organization with emphasis on their computational power. Furthermore, it will compare how these models have evolved throughout history and what prevents them from being the best option for research.
What research question must be answered?
– What are the main models of parallel computer organization with emphasis on their computational power?
– How have these models evolved throughout history and what prevents them from being the best option for research?
What is known about this research problem?
The development of computer architecture in itself was mainly focused on speed. However, in the last years it has shifted towards research which studied how to improve computation power. As Moore law starts to slow down, research in this field is expected to become even more important in the next few years.
This line of supports research in other fields, like the data warehouse research, by providing research concepts. The research done on formal concept analysis (FCA) is not well-connected to research done on resource discovery. This topic provides a better way of doing research on FCA by adding concepts for FCA to existing research literature.
For example, if one research on research progresses in the research of data warehousing, then the research progress of FCA progresses too.
Influence analysis in software engineering research is research on the phenomenon of important figures in research literature. Information about influential figures, their work and research can be used to discover trends or research areas that are more popular. It can also be used to identify topics that might otherwise not get attention using traditional peer-review journals.
In this research paper we will look at two different research papers that have been thoroughly studied by researchers from different research groups from all over the world. In contrast to research on influence of research literature, research across research is research about the phenomenon of closely related research work being done by different research groups from various locations around the world. This research will use a system called FCA for formal concept analysis research which is used for research on data sets to discover research areas that are closely related.
Translation between web services interface definition languages is a research problem; some research works on methods to define translation between interface definition languages (IDLs) use formal concept analysis (FCA). FCA is an information retrieval method, but research on its usage for translation of web services has not been covered in the research literature.
The motivation for this research is that “translation” can be used in research on “resource discovery” for concept languages such as FCA, and research can build on research. To verify this motivation the research literature is studied to find recent research that has used formal concept analysis (FCA) and research keywords related to resource discovery; apart from a few exceptions there is no relevant research found in this study.