Tag: Computer Science

Automatically Generating Cost-Effective Test Suites for Web Applications (Sara Sprenkle)

Hybrid: this project is scheduled to begin on 6/2/2025 and run for 10 weeks, finishing on 8/8/2025.

Project Description

Web applications are pervasive and must be well-tested to maintain high quality. Test suites should uncover faults in the software, represent typical usage, and be generated and executed at a relatively low cost. In this project, we will explore applying genetic algorithms to web application testing using actual user requests. Genetic algorithms have many tunable parameters (e.g., fitness function and mutation operator probabilities) that greatly affect their results. We will explore the parameter space and recommend the combinations of parameters that yield the best results for several subject web applications. We will then empirically compare test suites generated using genetic algorithms with those generated with other techniques.

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Prerequisites

Taken CSCI-209

Special Comments

Project Information (subject to change)

Estimated Start Date: 6/2/2025

Estimated End Date: 8/8/2025

Estimated Project Duration: 10 weeks

Maximum Number of Students Sought: 1

Research Location: Hybrid

Contact Information: Sara Sprenkle (email: SprenkleS@wlu.edu)

CLOSED: Algorithm Design in Online Scheduling (Kefu Lu)

On campus: this project is scheduled to begin on 6/9/2025 and run for 10 weeks, finishing on 8/15/2025.

Project Description

When given a collection of tasks to finish which have deadlines, which one should be prioritized first? How much time should be assigned to each task? Is it even possible to finish them all? The study of scheduling in computer science is about figuring out the optimal schedule to run programs in order fulfill quality of service metrics. This project will focus on finding the best algorithms to address a series of scheduling problems in the context of distributed computing – where there are a bunch of programs to run and also a bunch of computers to run them on! In this project, students will be learning about algorithm design, efficiency, and approximation algorithms. Discussing algorithm design problems in person is most productive for research, especially in the beginning. We can also switch to more flexible meetings later on if you wish to do so. The hope is that we discover an algorithm which works well and then we can submit the result for publication. In any case, this should be an interesting glimpse into the process of algorithm design.

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Prerequisites

This project does not require any programming. However, it is preferable if you have taken CSCI-111 OR CSCI-112.

Special Comments

Students who are currently taking or have taken CSCI-211 will be starting off ahead as they will have a lot of additional context. I highly encourage you to set up a quick chat if you have questions about the project.

Project Information (subject to change)

Estimated Start Date: 6/9/2025

Estimated End Date: 8/15/2025

Estimated Project Duration: 10 weeks

Maximum Number of Students Sought: 2

Research Location: On campus

Contact Information: Kefu Lu (email: klu@wlu.edu)

CLOSED: Nonlinear Gaming Skill Demographics (Elizabeth Matthews)

Hybrid: this project is scheduled to begin on 6/16/2025 and run for 10 weeks, finishing on 8/22/2025.

Project Description

Current research in academia uses a linear or binary distinction in participants when categorizing them by their video game skill level. My research has shown this to be an unreliable and non-standardized metric within academia, and next I intend to develop a nonlinear gaming personas categorization to better improve others’ research. You will need to perform user studies and statistical analysis in the programming language R.

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Prerequisites

CSCI 209 completion is required. Prior knowledge of the programming language R or statistical methods recommended but not required.

Special Comments

Project Information (subject to change)

Estimated Start Date: 6/16/2025

Estimated End Date: 8/22/2025

Estimated Project Duration: 10 weeks

Maximum Number of Students Sought: 2

Research Location: Hybrid

Contact Information: Elizabeth Matthews (email: lmatthews@wlu.edu)