christianadriano Goto Github PK

allgrads-hackathon

hackathon!!!

bayesianclassifiers_professioncategories

Classification of subjects professions using Bayesian Random Forest and Bayesian Logistic Regression

bayesianstudies

Scripts created to compute posterior probabilities

blog_code

A repo for holding example code

cd_faultunderstanding_causaldiscovery

Explore causal models for the accuracy of fault understanding

complexity_metrics

Computes different complexity metrics, Halstead, LOCs, Cyclomatic Complexity, etc.

cr_deeplearning_causalrobustness

Investigating approaches to prevent confounding in deep networks

crowd-debug-firefly

Infrastructure to crowdsource software debugging by means of a question and answer approach.

crowd-debug-qa

Experimentation with crowd debugging via questions and answers

datawrangling

Utility functions and examples of data wrangling

de_timeseriesanalysis

Tests for stationarity using R and Python libraries

ds_graph_metrrics

Descriptive statistics based on graphs metrics

dw_microtasks

Data wrangling scripts to preprocess data from crowdsourced microtasks

dw_scalascripts

Processing various datasets from Self-driving accidents and crowdsourcing tasks

excelwriter

explain-my-redesign

Investigating a Large Language Model (LLM) based tool for explaning software redesign

explainfix

Investigating a Large Language Model (LLM) based tool for explaning bug fixes

gm_taskdurations_gaussianmixtures

Expectation Maximization to build Gaussian mixture models of the duration of task executions.

luciola

data visualization for crowd fault localization data

luciola-utility

Project to study how utility theory to match workers to answers with the goal minimizing the number of questions asked in order to locate faults. This is my first attempt to model the problems of when to stop asking questions as a sequential decision problem.

machinelearningalgorithms

Basic algorithms I have been playing with

markovchain_tasksequencing

Markov Chain model to prioritize tasks (fault localization questions to ask a crowd of programmers))

markovchains_discretecontinuous

mb_faultunderstanding_multiarmedbandits

Explore different designs of Multi-Armed Bandits, mostly Contextual Bayesian Bandits

miniature-garbanzo

Daily coding practice, programming tips, best practices, etc.

ml4se-experiments

Data for running the experiments

ml_bayesianlearningexperiments

Comparative experiments with various Bayesian learning methods

ml_datadrivencontrol

Exploring Machine Learning Control for Dynamical Nonlinear Systems

ml_faultunderstanding

Replication of experiments, Descriptive statistics (ANOVA, Chi2square, Wilcoxon, Power calculations), Correlation Analysis (Kendall-tau), Predictive models (logistic regression). Goal is to investigate the factors that impact the accuracy of fault understanding. The analyzed factors are attributes of programmers (profession, year of experience) and tasks (duration, confidence).

ml_featureengineering

Select features by doing correlation analysis, PCA, decision trees, and information entropy