237 citations · 2.5k across the 105 of their papers we have counts for
19 papers · 1 filter
Better Software Analytics via "DUO": Data Mining Algorithms Using/Used-by Optimizers
Amritanshu Agrawal, Tim Menzies, Leandro L. Minku +2
This paper claims that a new field of empirical software engineering research and practice is emerging: data mining using/used-by optimizers for empirical studies or DUO. For examp…
Total Recall, Language Processing, and Software Engineering
Zhe Yu, Tim Menzies
A broad class of software engineering problems can be generalized as the "total recall problem". This short paper claims that identifying and exploring total recall language proces…
Better Metrics for Ranking SE Researchers
George Mathew, Tim Menzies
This paper studies how SE researchers are ranked using a variety of metrics and data from 35,406 authors of 35,391 papers from 34 top SE venues in the period 1992-2016. Based on th…
Crowdtesting : When is The Party Over?
Junjie Wang, Ye Yang, Zhe Yu +2
Trade-offs such as "how much testing is enough" are critical yet challenging project decisions in software engineering. Most existing approaches adopt risk-driven or value-based an…
Effective Automated Decision Support for Managing Crowdtesting
Junjie Wang, Ye Yang, Rahul Krishna +2
Crowdtesting has grown to be an effective alter-native to traditional testing, especially in mobile apps. However,crowdtesting is hard to manage in nature. Given the complexity of…
Cutting Away the Confusion From Crowdtesting
Junjie Wang, Mingyang Li, Song Wang +2
Crowdtesting is effective especially when it comes to the feedback on GUI systems, or subjective opinions about features. Despite of this, we find crowdtesting reports are highly r…
Hyperparameter Optimization for Effort Estimation
Tianpei Xia, Rahul Krishna, Jianfeng Chen +3
Software analytics has been widely used in software engineering for many tasks such as generating effort estimates for software projects. One of the "black arts" of software analyt…
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…
Why Software Effort Estimation Needs SBSE
Tianpei Xia, Jianfeng Chen, George Mathew +2
Industrial practitioners now face a bewildering array of possible configurations for effort estimation. How to select the best one for a particular dataset? This paper introduces O…
Micky: A Cheaper Alternative for Selecting Cloud Instances
Chin-Jung Hsu, Vivek Nair, Tim Menzies +1
Most cloud computing optimizers explore and improve one workload at a time. When optimizing many workloads, the single-optimizer approach can be prohibitively expensive. Accordingl…
Transfer Learning with Bellwethers to find Good Configurations
Vivek Nair, Rahul Krishna, Tim Menzies +1
As software systems grow in complexity, the space of possible configurations grows exponentially. Within this increasing complexity, developers, maintainers, and users cannot keep…
Applications of Psychological Science for Actionable Analytics
Di Chen, Wei Fu, Rahul Krishna +1
Actionable analytics are those that humans can understand, and operationalize. What kind of data mining models generate such actionable analytics? According to psychological scient…
Building Better Quality Predictors Using "-Dominance"
Wei Fu, Tim Menzies, Di Chen +1
Despite extensive research, many methods in software quality prediction still exhibit some degree of uncertainty in their results. Rather than treating this as a problem, this pape…
Scout: An Experienced Guide to Find the Best Cloud Configuration
Chin-Jung Hsu, Vivek Nair, Tim Menzies +1
Finding the right cloud configuration for workloads is an essential step to ensure good performance and contain running costs. A poor choice of cloud configuration decreases applic…
Improving Vulnerability Inspection Efficiency Using Active Learning
Zhe Yu, Christopher Theisen, Laurie Williams +1
Software engineers can find vulnerabilities with less effort if they are directed towards code that might contain more vulnerabilities. HARMLESS is an incremental support vector ma…
Bad Smells in Software Analytics Papers
Tim Menzies, Martin Shepperd
CONTEXT: There has been a rapid growth in the use of data analytics to underpin evidence-based software engineering. However the combination of complex techniques, diverse reportin…
500+ Times Faster Than Deep Learning (A Case Study Exploring Faster Methods for Text Mining StackOverflow)
Suvodeep Majumder, Nikhila Balaji, Katie Brey +2
Deep learning methods are useful for high-dimensional data and are becoming widely used in many areas of software engineering. Deep learners utilizes extensive computational power…
Data-Driven Search-based Software Engineering
Vivek Nair, Amritanshu Agrawal, Jianfeng Chen +6
This paper introduces Data-Driven Search-based Software Engineering (DSE), which combines insights from Mining Software Repositories (MSR) and Search-based Software Engineering (SB…
Finding Faster Configurations using FLASH
Vivek Nair, Zhe Yu, Tim Menzies +2
Finding good configurations for a software system is often challenging since the number of configuration options can be large. Software engineers often make poor choices about conf…