3 citations · 6 across the 6 of their papers we have counts for
8 papers
MOOT: a Repository of Many Multi-Objective Optimization Tasks
Tim Menzies, Tao Chen, Yulong Ye +4
Software engineers must make decisions that trade off competing goals (faster vs. cheaper, secure vs. usable, accurate vs. interpretable, etc.). Despite MSR's proven techniques for…
Less Noise, More Signal: the DRR Effect for Better Optimizations of a Range of SE Tasks
Andre Lustosa, Tim Menzies
SE analytics problems do not always need complex AI. Better and faster solutions can sometimes be obtained by matching the complexity of the problem to the complexity of the soluti…
Streamlining Software Reviews: Efficient Predictive Modeling with Minimal Examples
Tim Menzies, Andre Lustosa
This paper proposes a new challenge problem for software analytics. In the process we shall call "software review", a panel of SMEs (subject matter experts) review examples of soft…
iSNEAK: Partial Ordering as Heuristics for Model-Based Reasoning in Software Engineering
Andre Lustosa, Tim Menzies
A "partial ordering" is a way to heuristically order a set of examples (partial orderings are a set where, for certain pairs of elements, one precedes the other). While these order…
Learning from Very Little Data: On the Value of Landscape Analysis for Predicting Software Project Health
Andre Lustosa, Tim Menzies
When data is scarce, software analytics can make many mistakes. For example, consider learning predictors for open source project health (e.g. the number of closed pull requests in…
SNEAK: Faster Interactive Search-based SE
Andre Lustosa, Jaydeep Patel, Venkata Sai Teja Malapati +1
When AI tools can generate many solutions, some human preference must be applied to determine which solution is relevant to the current project. One way to find those preferences i…
Fairer Software Made Easier (using "Keys")
Tim Menzies, Kewen Peng, Andre Lustosa
Can we simplify explanations for software analytics? Maybe. Recent results show that systems often exhibit a "keys effect"; i.e. a few key features control the rest. Just to say th…
Preference Discovery in Large Product Lines
Andre Lustosa, Tim Menzies
When AI tools can generate many solutions, some human preference must be applied to determine which solution is relevant to the current project. One way to find those preferences i…