CodeQL documentation

Academic publications

2019

Unsupervised Recalibration.
Albert Ziegler and Pawel Czyz. Under submission.

The standard coder:
a machine learning approach to measuring the effort required to produce source code change
.
Ian Wright and Albert Ziegler.
Proceedings of the 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, RAISE 2019, Montreal.

2018

Measuring software development productivity: a machine learning approach.
Jean Helie, Ian Wright, Albert Ziegler.
Paper presented at the 'Machine Learning for Programming' Workshop
affiliated with the 2018 Federated Logic Conference (FLoC).

2017

Algebraic Data Types for Object-oriented Datalog.
Max Schäfer;, Pavel Avgustinov, Oege de Moor. Draft paper.

2016

QL: Object-oriented Queries on Relational Data.
Pavel Avgustinov, Oege de Moor, Michael Peyton Jones, Max Schäfer.;
European Conference on Object-Oriented Programming (ECOOP).

2015

Tracking Static Analysis Violations Over Time to Capture Developer Characteristics.
Pavel Avgustinov, Arthur I. Baars, Anders S. Henriksen, Greg Lavender, Galen Menzel,
Oege de Moor, Max Schäfer;, Julian Tibble.
International Conference on Software Engineering (ICSE). Experimental data.

2010

Type Inference for Datalog with Complex Type Hierarchies.
Max Schäfer;, Oege de Moor. Principles of Programming Languages (POPL).

2008

Type Inference for Datalog and Its Application to Query Optimisation.
Oege de Moor, Damien Sereni, Pavel Avgustinov, Mathieu Verbaere.
Principles of Database Systems (PODS).

Adding Magic to an Optimising Datalog Compiler.
Damien Sereni, Pavel Avgustinov, Oege de Moor.
International Conference on Management of Data (SIGMOD).

2007

QL: Object-Oriented Queries Made Easy.
Oege de Moor, Damien Sereni, Mathieu Verbaere, Elnar Hajiyev, Pavel Avgustinov,
Torbjörn; Ekman, Neil Ongkingco, Julian Tibble.
Generative and Transformational Techniques in Software Engineering (GTTSE).
The final publication is available at Springer.

QL for Source Code Analysis.
Oege de Moor, Mathieu Verbaere, Elnar Hajiyev, Pavel Avgustinov, Torbjörn; Ekman,
Neil Ongkingco, Damien Sereni, Julian Tibble.
Source Code Analysis and Manipulation (SCAM). Also available via IEEE Xplore.