Senior Design Projects

ECS193 A/B Winter & Spring 2019

Browsing and Visualizing Real-World Bugs and Fixes

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Prof. Cindy Rubio-Gonzalez
University of California, Davis

Project's details

Browsing and Visualizing Real-World Bugs and Fixes
Improving software quality is a central priority of our time. Approaches to understand, diagnose, localize, and fix software defects are usually empirically grounded in datasets of past defects and patches. A few such datasets are available; however, these datasets are difficult to create, and are typically not of the size, scale, and diversity that is representative of the software in use. To address these limitations, here at UC Davis we have designed and implemented the BugSwarm infrastructure and dataset. BugSwarm automatically mines real-world bugs and their fixes from open-source projects hosted in GitHub. To date, the BugSwarm dataset consists of over 3,000 artifacts ( pairs of bugs and fixes ) mined from Java and Python projects. BugSwarm is the largest dataset of real-world bugs, and the first to be created fully automatically!
We expect BugSwarm will have numerous clients from academia and industry who will use the artifacts to evaluate their testing and bug-finding tools. Likely, not all of BugSwarm's artifacts will be relevant to all clients. Therefore, a key component for the success of the dataset will be a website that allows to browse through the different kinds of bugs present in the dataset. We would like to provide BugSwarm's clients with a way to search through artifacts and visualize various of their characteristics, such as programming language, build system, testing framework, code complexity, bug type and fix strategy. This will be particularly challenging because of the large number of artifacts in the dataset, which is expected to continue to grow.
There will be two deliverables for this project: ( 1 ) BugSwarm Website. ( 2 ) BugSwarm Database. We currently have both a website and a database that can be used as a start point for this project.
JavaScript. Python 3.0. Java. Databases ( e.g., MongoDB ).
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30-60 min weekly or more
Client wishes to keep IP of the project
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