| Shrikanth N.C. |
2021 |
Final Defense |
Taming Confusions in Software Engineering |
| Patrick Xia |
2021 |
Final Defense |
Assessing the Health Status of Open-Source Software Projects |
| Rui Shu |
2021 |
Final Defense |
On the Value of Hyperparameter
Optimization in Security |
| Rahul Yedida |
2021 |
ASE '21 |
Automated microservice partitioning: where are we? |
| Andre Lustosa |
2021 |
Written Prelim |
SNEAK: Faster Interactive Search-based Software Engineering(using Semi-Supervised Learning) |
| Rahul Yedida |
2021 |
Written Prelim |
When SIMPLE is better than complex: A case study on deep learning for predicting Bugzilla issue close time |
| Joymallya Chakraborty |
2021 |
Oral Prelim |
Deciphering ML Software Fairness |
| Rui Shu |
2021 |
FSE'21 |
How to Better Distinguish Security Bug Reports (Using Dual Hyperparameter Optimization) |
| Joymallya Chakraborty |
2021 |
FSE'21 |
Bias in Machine Learning Software: Why? How? What to Do? |
| Shrikanth N.C. |
2021 |
Oral Prelim |
Taming Confusions in Software Engineering |
| Rui Shu |
2020 |
Oral Prelim |
On the Value of Hyperparameter
Optimization in Security |
| Patrick Xia |
2020 |
Oral Prelim |
Predicting Project Health for Open-Source Software |
| Tim Menzies |
2020 |
ICSME'20 |
The future of software engineering (is AI) |
| Joymallya Chakraborty |
2020 |
ASE'20 |
Making Fair ML Software using Trustworthy Explanation |
| Shrikanth, N C |
2020 |
ICSE SEIP |
Assessing Practitioner Beliefs about Software Defect Prediction |
| Joymallya Chakraborty |
2020 |
Written Prelim |
Fairway: SE Principles for Building Fairer Software |
| Zhe Yu |
2020 |
Final Defense |
Software Engineering and Total Recall |
| Shrikanth N.C |
2020 |
Written Prelim |
Assessing Practitioner Beliefs about Software Defect Prediction |
| Joymallya Chakraborty |
2019 |
ASE'19 |
Software Engineering for Fairness |
| Rahul Krishna |
2019 |
Final Defense |
Generating Actionable Insights for Software Engineering |
| Joymallya Chakraborty |
2019 |
FSE'19 |
Predicting Breakdowns in Cloud Services (with SPIKE) |
| Joymallya Chakraborty |
2019 |
FSE'19 |
TERMINATOR: Better Automated UI Test Case Prioritization |
| Jianfeng Chen |
2019 |
Final Defense |
On the value of sampling and pruning on SBSE |
| Amritanshu Agrawal |
2019 |
Final Defense |
On the Nature of Software Engineering Data |
| Amritanshu Agrawal |
2019 |
Oral Prelim |
On the Nature of Software Engineering Data |
| Tim Menzies |
2019 |
CS Gateway |
Q What's Wrong with Computational Science Software? A:Nothing |
| Tim Menzies |
2019 |
CodeFreeze'19 |
SE for AI for SE (after data mining, what's next) |
| Vivek Nair |
2018 |
Final Defense |
Frugal Ways of Finding “Good”
Configurations |
| Tim Menzies |
2018 |
FSE'18 |
Applciations of Psychology to Software Analytics
|
| Tim Menzies |
2018 |
EAQSE'18 |
Empirical SE: status report
|
| Zhe Yu |
2018 |
Oral Prelim |
Total Recall and Software Engineering
|
| Tianpei (Patrick) Xia |
2018 |
Written Prelim |
Hyperparameter Optimization for Software Effort Estimation
|
| Tim Menzies |
2018 |
Keynote, FSE 2018 |
In the age of Software 2.0. what role for software engineers?
|
| Jianfeng Chen |
2018 |
Seminar, RAISE Lab |
Summer
Internship 2018
|
| Amritanshu Agrawal |
2018 |
FSE, SWAN |
Characterizing the Influence of Continuous Integration
|
| Tim Menzies |
2018 |
Seminar, RAISE Lab |
Anti-Patterns of RAISE research
|
| Zhe Yu |
2018 |
Seminar, RAISE Lab |
Summer
Internship 2018
|
| Amritanshu Agrawal |
2018 |
Seminar, RAISE Lab |
Landing a Successful Job/Internship in Current World!
|
| Rahul Krishna |
2018 |
Seminar, Raise Lab |
Eliciting Domain Knowledge
from Legacy Systems
|
| Rahul Krishna |
2018 |
ICSE-SEIP |
Connection Between Issues, Bugs, and Enhancements
(Lessons Learned from 800+ Projects)
|
| Jianfeng Chen |
2018 |
IEEE Cloud |
Micky: A Cheaper Alternative for Selecting Cloud Instances
|
Jianfeng Chen |
2018 |
IEEE Cloud |
Riot: A Stochastic-based Method for Workflow Scheduling in the Cloud
|
| Wei Fu |
2017 |
FSE'17 |
Easy over Hard: A Case Study on Deep Learning
|
| Wei Fu |
2017 |
FSE'17 |
Revisiting Unsupervised Learning for Defect Prediction
|
| Wei Fu |
2016 |
Written Prelim |
Tuning for Software Analytics: is it Really Necessary?
|
| Wei Fu |
2017 |
Oral Prelim |
Faster Methods for Software Analytids!
|
| Wei Fu |
2018 |
Defense |
Simpler Software Analytics: When? When Not?
|
| Zhe Yu |
2017 |
Written Prelim |
How to Read Less:
On the Benefit of Human-in-the-loop Incremental Learning for Systematic Literature Reviews
|
| Jianfeng Chen |
2017 |
Written Prelim |
SWAY:
A Baseline Method for Search-Based Software Engineering
|
| Jianfeng Chen |
2018 |
Oral Prelim |
On the
value of Sampling and Pruning for Search-Based Software Engineering
|
| Vivek Nair |
2016 |
Written Prelim |
Frugal: Cheaper Methods for SBSE |
| Vivek Nair |
2017 |
Oral Prelim |
Frugal ways to find good configurations (for configurable systems)
|
| Vivek Nair |
2017 |
SWAN'17 |
Plant a (decision) TREE and save the
world*! |
| Vivek Nair |
2017 |
FSE'17 |
Using Bad Learners to
find Good Configurations |
| Amritanshu Agrawal |
2017 |
Written Prelim |
What is Wrong With Topic Modeling?
|
| Amritanshu Agrawal |
2018 |
ICSE |
Is "Better Data" Better Than "Better Data Miners"? (On the Benefits of
Tuning SMOTE for Defect Prediction)
|
| Amritanshu Agrawal |
2018 |
ICSE-SEIP |
We Don't Need Another Hero? (The Impact of "Heroes" on Software
Development)
|
| George Mathew |
2017 |
Written Prelim |
"SHORT"er Reasoning About Larger Requirement Models
|
| George Mathew |
2017 |
RE'17 |
"SHORT"er Reasoning About Larger Requirement Models
|
| Tim Menzies |
2017 |
Invited Talk, Monash Univeristy, 2017 |
More less: seeking simpler software analytics (why?, how?) |
| Tim Menzies |
2017 |
Keynote: data-drive search-based SE |
when data mienrs meet optimizers |
| Tim Menzies |
2016 |
SSBSE'17 |
An (Accidental) Exploration of Alternatives to Evolutionary Algorithms
|
| Tim Menzies |
2018 |
Keynote RAISE18
Inivted talk, Naval Research Labs
Invited talk SE ML summer school |
Software assurance and AI: how to achieve SA assurance for systems that
use machine learning or other AI methods
|
| Tim Menzies |
2017 |
Invited talk
CREST52, UCL |
Analytics without SBSE Considered Harmful |
| Tim Menzies |
2016 |
Invited talk, workshop on search-based SE |
Data Science2 =
( Test * DataScience ) |
| Tim Menzies |
2017 |
Invited talk, IBM developers conference |
Empriical SE research @data.IBM.honeypot |
| Tim Menzies |
2018 |
MSR'18 |
Data-Driven Search-based SE |
| Tim Menzies |
2015 |
FSE'15 |
GALE:
geometric active learning for search-based SE |
| Tim Menzies |
2018 |
FSE'17 |
Are delayed issues Harder to Resolve? |
| Rahul Krishna |
2016 |
ASE 2016 |
Too Much Automation? |
| Rahul Krishna |
2017 |
Written Exam |
Don’t Tell Me What Is; Tell Me What Ought To Be! Planning in Software
Engineering |
| Rahul Krishna |
2017 |
ASE 17 Doctoral Symposium |
Learning Effective Changes in Software Engineering
|
| Zhe Yu |
2017 |
HPCC Community Day 2017 |
Needle
in a Haystack
|
| Zhe Yu |
2017 |
CLEF'17 |
Data
Balancing for Technologically Assisted Reviews
|
| Zhe Yu |
2016 |
BIGDSE'16 |
BigSE:
Lessons Learned from Validating Industrial Text Mining
|
Lab @