Improving Error Notification Comprehension through Visual Overlays in IDEs

My graduate consortium submission, Improving Error Notification Comprehension through Visual Overlays in IDEs has been accepted to the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) in Melbourne, Australia. The abstract of the paper follows:

Error notifications, as presented by modern integrated development environments, are cryptic and confusing to developers. My dissertation research will demonstrate that modifying production compilers to expose detailed semantics about compilation errors is feasible, and that these semantics can be leveraged through diagrammatic representations using visual overlays on the source code to significantly improve compiler error notification comprehension.

Google Internship Redux


I’m returning to Mountain View, California this summer to intern for Google, from June 16 to September 5. This time around, I will be working with the Knowledge: Translate team on interactive visualizations applied to the domain of machine learning.

Compiler Error Notifications Revisited

Our paper, Compiler Error Notifications Revisited: An Interaction-First Approach for Helping Developers More Effectively Comprehend and Resolve Error Notifications, has been accepted to ICSE 2014: New Ideas and Emerging Results.

Interaction Framework

The abstract of the paper follows:

Error notifications and their resolutions, as presented by modern IDEs, are still cryptic and confusing to developers. We propose an interaction-first approach to help developers more effectively comprehend and resolve compiler error notifications through a conceptual interaction framework. We propose novel taxonomies that can serve as controlled vocabularies for compiler notifications and their resolutions. We use preliminary taxonomies to demonstrate, through a prototype IDE, how the taxonomies make notifications and their resolutions more consistent and unified.

Windows could not search for new updates

Add me to the list of annoyed users who are receiving Code 80244FFF with no resolution from Microsoft (at least, Microsoft does not seem to have acknowledged the problem).


I’ve tried the following options so far, and am open to other suggestions:


Update: After applying the Windows 8.1 Update, I now receive Code 80240442. So all I’ve really done is trade one error code for another.

There does seem to be a workaround for this issue, but it involves temporarily modifying your Internet Options when wanting to run Windows Update. First, find Internet Options, either through the Start Menu or under Control Panel:

Internet Options

Then, go under the Connections tab and click LAN settings. Check “Use a proxy server for your LAN”:

LAN Settings

Click Advanced, and enter the following settings:

Proxy Settings

For HTTP and Secure, use for the “Proxy address to use” and 8888 for the port. Under Exceptions, type <-loopback>.

You may have to reboot your machine. Then, run Windows Update as you normally would.

Frontiers in Education

Frontiers in Education
This week I attended the Frontiers in Education conference (October 23-26) in Oklahoma City, Oklahoma, where I presented my work on A Community College Blended Learning Classroom Experience through Artificial Intelligence in Games. This is my first Computer Science Education paper.

The paper reports on the experience of teaching an industry-validated course on Artificial Intelligence in Computer Games within the Simulation and Game Design department at a two-year community college during a 16-week semester. The course format used a blended learning just-in-time teaching approach, which included active learning programming exercises and one-on-one student interactions.

ACT-R Models of the Concentration Game

Our paper on Speed/Accuracy Tradeoff in ACT-R Models of the Concentration Game Game has appeared in the 2013 International Conference on Cognitive Modeling.

This paper describes the development of subsymbolic ACT-R models for the Concentration game. Performance data is taken from an experiment in which participants played the game under two conditions: minimizing the number of mismatches/turns during a game, and minimizing the time to complete a game. Conflict resolution and parameter tuning are used to implement an accuracy model and a speed model that capture the differences for the two conditions. Visual attention drives exploration of the game board in the models. Modeling results are generally consistent with human performance, though some systematic differences can be seen. Modeling decisions, model limitations, and open issues are discussed.

Press: [Teaching a Computer to Play