activity
20182023
most citedIdentifying Self-Admitted Technical Debts with Jitterbug: A Two-step Approach

47 citations · 84 across the 13 of their papers we have counts for

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Showing cs.SEShow all

10 papers · 1 filter

cs.SE2023

Less, but Stronger: On the Value of Strong Heuristics in Semi-supervised Learning for Software Analytics

Huy Tu, Tim Menzies

In many domains, there are many examples and far fewer labels for those examples; e.g. we may have access to millions of lines of source code, but access to only a handful of warni…

cs.SE2022★ 2 cited

How to Find Actionable Static Analysis Warnings: A Case Study with FindBugs

Rahul Yedida, Hong Jin Kang, Huy Tu +3

Automatically generated static code warnings suffer from a large number of false alarms. Hence, developers only take action on a small percent of those warnings. To better predict…

cs.SE2022

DebtFree: Minimizing Labeling Cost in Self-Admitted Technical Debt Identification using Semi-Supervised Learning

Huy Tu, Tim Menzies

Keeping track of and managing Self-Admitted Technical Debts (SATDs) is important for maintaining a healthy software project. Current active-learning SATD recognition tool involves…

cs.SE2021★ 9 cited

Fair-SSL: Building fair ML Software with less data

Joymallya Chakraborty, Suvodeep Majumder, Huy Tu

Ethical bias in machine learning models has become a matter of concern in the software engineering community. Most of the prior software engineering works concentrated on finding e…

cs.SE2021★ 3 cited

FRUGAL: Unlocking SSL for Software Analytics

Huy Tu, Tim Menzies

Standard software analytics often involves having a large amount of data with labels in order to commission models with acceptable performance. However, prior work has shown that s…

cs.SE2021

Mining Scientific Workflows for Anomalous Data Transfers

Huy Tu, George Papadimitriou, Mariam Kiran +4

Modern scientific workflows are data-driven and are often executed on distributed, heterogeneous, high-performance computing infrastructures. Anomalies and failures in the workflow…

cs.SE2020★ 5 cited

The Changing Nature of Computational Science Software

Huy Tu, Rishabh Agrawal, Tim Menzies

How should software engineering be adapted for Computational Science (CS)? If we understood that, then we could better support software sustainability, verifiability, reproducibili…

cs.SE2020★ 47 cited

Identifying Self-Admitted Technical Debts with Jitterbug: A Two-step Approach

Zhe Yu, Fahmid Morshed Fahid, Huy Tu +1

Keeping track of and managing Self-Admitted Technical Debts (SATDs) are important to maintaining a healthy software project. This requires much time and effort from human experts t…

cs.SE2019★ 2 cited

Better Data Labelling with EMBLEM (and how that Impacts Defect Prediction)

Huy Tu, Zhe Yu, Tim Menzies

Standard automatic methods for recognizing problematic development commits can be greatly improved via the incremental application of human+artificial expertise. In this approach,…

cs.SE2018★ 1 cited

Can You Explain That, Better? Comprehensible Text Analytics for SE Applications

Amritanshu Agrawal, Huy Tu, Tim Menzies

Text mining methods are used for a wide range of Software Engineering (SE) tasks. The biggest challenge of text mining is high dimensional data, i.e., a corpus of documents can con…