Blaine Donley

Full Stack Developer

Email: blaine@blainedonley.com Phone: (540) 842-0805 Fax: (855) 782-7679 Address: Stafford, Virginia

Overview

Blaine Donley is the Owner of Quaso LLC. He is a former doctoral candidate in the Computer Science Department of George Mason University's Volgenau School of Engineering in the Information Technology Program. Blaine is actively designing and developing software for a variety of businesses.

Recent Projects

Complete

Custom Billing System

Front-end web development of a custom billing system using React, Salesforce Lightning Design components, Express, Enzyme, Jest, and Webpack using an Open Source Backend

Complete

Restaurant App

Front-end app development for Android, iOS, and web browsers using Ionic, Cordova, and Angular.js.

Complete

Memorization App

App development for iOS using Swift and XCode.

Active

Sentiment Analysis

End-to-end development of a real-time surveying system for the collection and analysis of patient feedback; includes a patent pending algorithm for sentiment analysis.

Complete

CMMI Maturity Level 3

Assisted a fast-growning, mid-sized government contractor in successfully achieving CMMI Maturity Level 2 and 3 for the CMMI development constellation version 1.3; participation included developing processes and procedures, developing multiple ASP.NET MVC pilot projects, and participating in CMMI appraisal team.

Complete

Decision Support System

Architected and, with a small team, developed an agent-based, ontology-driven decision support tool for evolutionary algorithm

Publications

Complete

A Model-based Approach to Testing Stateful Web Applications
2nd International Conference on Software Testing, Verification, and Validation
ICST 2009, Denver, Colorado USA. April 1, 2009.

Existing software testing techniques are not designed to detect faults caused by improper management of state in stateful web applications. This research proposes an efficient and effective method to perform data flow testing of stateful, hypertext-based web applications. The approach suggests that faults caused by improper management of state in web applications can be adequately detected by extending traditional data flow testing techniques to include the semantics of web application transitions and state management approaches and through the use of data flow coverage criteria based on these semantics.