237 citations · 2.5k across the 105 of their papers we have counts for
17 papers · 1 filter
Low-Level Augmented Bayesian Optimization for Finding the Best Cloud VM
Chin-Jung Hsu, Vivek Nair, Vincent W. Freeh +1
With the advent of big data applications, which tends to have longer execution time, choosing the right cloud VM to run these applications has significant performance as well as ec…
We Don't Need Another Hero? The Impact of "Heroes" on Software Development
Amritanshu Agrawal, Akond Rahman, Rahul Krishna +2
A software project has "Hero Developers" when 80% of contributions are delivered by 20% of the developers. Are such heroes a good idea? Are too many heroes bad for software quality…
What is the Connection Between Issues, Bugs, and Enhancements? (Lessons Learned from 800+ Software Projects)
Rahul Krishna, Amritanshu Agrawal, Akond Rahman +2
Agile teams juggle multiple tasks so professionals are often assigned to multiple projects, especially in service organizations that monitor and maintain a large suite of software…
RIOT: a Stochastic-based Method for Workflow Scheduling in the Cloud
Jianfeng Chen, Tim Menzies
Cloud computing provides engineers or scientists a place to run complex computing tasks. Finding a workflow's deployment configuration in a cloud environment is not easy. Tradition…
Learning Actionable Analytics from Multiple Software Projects
Rahul Krishna, Tim Menzies
The current generation of software analytics tools are mostly prediction algorithms (e.g. support vector machines, naive bayes, logistic regression, etc). While prediction is usefu…
FLASH: A Faster Optimizer for SBSE Tasks
Vivek Nair, Zhe Yu, Tim Menzies
Most problems in search-based software engineering involve balancing conflicting objectives. Prior approaches to this task have required a large number of evaluations- making them…
FAST: an Intelligent Assistant for Finding Relevant Papers
Zhe Yu, Tim Menzies
Literature reviews are essential for any researcher trying to keep up to date with the burgeoning software engineering literature. FAST is a novel tool for reducing the effort…
Is "Better Data" Better than "Better Data Miners"? (On the Benefits of Tuning SMOTE for Defect Prediction)
Amritanshu Agrawal, Tim Menzies
We report and fix an important systematic error in prior studies that ranked classifiers for software analytics. Those studies did not (a) assess classifiers on multiple criteria a…
Better Predictors for Issue Lifetime
Mitch Rees-Jones, Matthew Martin, Tim Menzies
Predicting issue lifetime can help software developers, managers, and stakeholders effectively prioritize work, allocate development resources, and better understand project timeli…
Bellwethers: A Baseline Method For Transfer Learning
Rahul Krishna, Tim Menzies
Software analytics builds quality prediction models for software projects. Experience shows that (a) the more projects studied, the more varied are the conclusions; and (b) project…
Easy over Hard: A Case Study on Deep Learning
Wei Fu, Tim Menzies
While deep learning is an exciting new technique, the benefits of this method need to be assessed with respect to its computational cost. This is particularly important for deep le…
Revisiting Unsupervised Learning for Defect Prediction
Wei Fu, Tim Menzies
Collecting quality data from software projects can be time-consuming and expensive. Hence, some researchers explore "unsupervised" approaches to quality prediction that does not re…
Replicating and Scaling up Qualitative Analysis using Crowdsourcing: A Github-based Case Study
Di Chen, Kathryn T. Stolee, Tim Menzies
Due to the difficulties in replicating and scaling up qualitative studies, such studies are rarely verified. Accordingly, in this paper, we leverage the advantages of crowdsourcing…
Using Bad Learners to find Good Configurations
Vivek Nair, Tim Menzies, Norbert Siegmund +1
Finding the optimally performing configuration of a software system for a given setting is often challenging. Recent approaches address this challenge by learning performance model…
"SHORT"er Reasoning About Larger Requirements Models
George Mathew, Tim Menzies, Neil A. Ernst +1
When Requirements Engineering(RE) models are unreasonably complex, they cannot support efficient decision making. SHORT is a tool to simplify that reasoning by exploiting the "key"…
Faster Discovery of Faster System Configurations with Spectral Learning
Vivek Nair, Tim Menzies, Norbert Siegmund +1
Despite the huge spread and economical importance of configurable software systems, there is unsatisfactory support in utilizing the full potential of these systems with respect to…
Beyond Evolutionary Algorithms for Search-based Software Engineering
Jianfeng Chen, Vivek Nair, Tim Menzies
Context: Evolutionary algorithms typically require a large number of evaluations (of solutions) to converge - which can be very slow and expensive to evaluate.Objective: To solve s…