Important Dates & Schedule

Date Topic & Material Deliverable
14.9 Introduction
21.9 Empirical Research & Examples of such (Information Needs and Bug Fixes)

Papers on Information Needs

Information Needs in Collocated Software Development Teams, Ko et al., ICSE 2007.

The design of bug fixes, Murphy-Hill et al., ICSE 2013.

Papers on (Empirical) Research

What makes good research in software engineering?, Shaw, International Journal on Software Tools for Technology, 2002.

Preliminary guidelines for empirical research in software engineering, Kitchenham et al., IEEE Transactions on Software Engineering, 2002.


Experimental models for validating technology, Zelkowitz et al., IEEE Computer, 1998.

response papers, participation in class
28.9 Biometrics, Emotions and Development Activity

Do moods affect programmers' debug performance?, Khan et al., Cognition, Technology and Work, 2011.

Real-Time Representation Versus Response Elicitation in Biosensor Data, Matthews et al., CHI 2015.

Stuck and Frustrated or In Flow and Happy: Sensing Developers’ Emotions and Progress, Müller and Fritz, ICSE 2015.

Summarizing and Measuring Development Activity, Treude et al., ESEC-FSE 2015.

Bored Mondays and Focused Afternoons: The Rhythm of Attention and Online Activity in the Workplace, Mark et al., CHI 2014.


Are Happy Developers more Productive? The Correlation of Affective States of Software Developers ane their-self-assessed productivity, Graziotin et al., Proceedings of the 14th Internationl Conference on Product-Focused Software Process Improvement, 2013.

Understanding Understanding Source Code with Functional Magnetic Resonance Imaging, Siegmund et al., ICSE 2014.

response papers, leading of part of the discussion, participation
5.10 Interruptions and Machine Learning

On the need for attention-aware systems: Measuring effects of interruption on task performance, error rate, and affective state, Bailey and Konstan, Computers in Human Behavior, 2006.

Using Mental Load for Managing Interruptions in Physiologically Attentive User Interfaces, Chen and Vertegaal, CHI, 2005.

A Brief Introduction into Machine Learning, Raetsch, 2004.

response paper, lead discussion; proposal for project by the end of the week
9.10 Project Proposal
12.10 Week for discussing proposals
19.10 Presenting proposals to class Final Project Proposal + Proposal presentation
26.10 Weekly Scrum in Research + weekly meeting (10-20 mins) short update report
2.11 Eye-Tracking in SE

Improving Automated Source Code Summarization via an Eye-Tracking Study of Programmers, Rodeghero et al., ICSE 2014.

Tracing Software Developers' Eyes and Interactions for Change Tasks, Kevic et al., ESEC-FSE 2015.

EyeDE: Gaze-enhanced Software Development Environments, Glücker et al., CHI 2014.

An Eye Tracking Study on camelCase and under_score Identifier Styles, Sharif and Maletic, ICPC 2010.

response papers, leading of part of the discussion
9.11 Weekly meeting (10-20 mins) short update report
16.11 Weekly meeting (10-20 mins) short update report
23.11 Weekly meeting (10-20 mins) one page writeup of results
30.11 Weekly meeting (10-20 mins) draft of project report with related work section of final report.
Optional: Full Paper Review
7.12 you will receive two other reports for reviewing Project Report
14.12 Presenting end results to class presentation, reviews of other papers