Moa Johansson

Associate Professor at Data Science and AI

Source: chalmers.se
Image of Moa Johansson

Showing 28 publications

2022

TriCo—Triple Co-piloting of Implementation, Specification and Tests

Wolfgang Ahrendt, Dilian Gurov, Moa Johansson et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 13701 LNCS, p. 174-187
Paper in proceeding
2022

Machine Learning of Pacing Patterns for Half Marathon

Johan Atterfors, Johan Lamm, Moa Johansson
Preprint
2022

Machine Learning Techniques for Gait Analysis in Skiing

Savya Sachi Gupta, Moa Johansson, Dan Kuylenstierna et al
Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference, p. 126-129
Paper in proceeding
2022

Generating Weekly Training Plans in the Style of a Professional Swimming Coach Using Genetic Algorithms and Random Trees

Rikard Eriksson, Johan Nicander, Moa Johansson et al
Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference (Advances in Intelligent Systems and Computing 1426). Vol. 1426, p. 61-68
Paper in proceeding
2021

Conjectures, tests and proofs: An overview of theory exploration

Moa Johansson, Nicholas Smallbone
Electronic Proceedings in Theoretical Computer Science, EPTCS. Vol. 341, p. 1-16
Paper in proceeding
2021

Automated Conjecturing in QuickSpec

Moa Johansson, Nicholas Smallbone
1 st Mathematical Reasoning in General Artificial Intelligence Workshop, ICLR 2021.
Paper in proceeding
2020

Template-based Theory Exploration: Discovering Properties of Functional Programs by Testing

Sólrún Einarsdóttir, Nicholas Smallbone, Moa Johansson
ACM International Conference Proceeding Series, p. 67-78
Paper in proceeding
2020

Theory exploration: Conjecturing, testing and reasoning about programs

Moa Johansson
Electronic Proceedings in Theoretical Computer Science, EPTCS. Vol. 320
Paper in proceeding
2019

Preface

José Júlio Alferes, Moa Johansson
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 11372 LNCS, p. V-VI
Other text in scientific journal
2019

Identifying cross country skiing techniques using power meters in ski poles.

Moa Johansson, Marie Korneliusson, Nickey Lizbat Lawrence
Communications in Computer and Information Science. Vol. 1056, p. 52-57
Paper in proceeding
2019

Lemma Discovery for Induction: A Survey

Moa Johansson
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 11617 LNAI, p. 125-139
Paper in proceeding
2019

Proving Type Class Laws for Haskell

Andreas Arvidsson, Moa Johansson, Robin Touche
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 10447 LNCS, p. 61-74
Paper in proceeding
2018

Into the infinite - theory exploration for coinduction

Sólrún Einarsdóttir, Moa Johansson, Johannes Åman Pohjala
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 11110 LNAI, p. 70-86
Paper in proceeding
2018

Towards Machine Learning on Data from Professional Cyclists

Oscar Ivarsson, Agrin Hilmkil, Moa Johansson et al
Proceedings of the XII World Congress of Performance Analysis of Sport. Vol. 2018
Paper in proceeding
2017

Quick Specifications for the Busy Programmer

Nicholas Smallbone, Moa Johansson, Koen Lindström Claessen et al
Journal of Functional Programming. Vol. 27
Journal article
2017

QuickSpec: a lightweight theory exploration tool for programmers (system demonstration)

Maximilian Algehed, Koen Lindström Claessen, Moa Johansson et al
SIGPLAN Notices (ACM Special Interest Group on Programming Languages). Vol. 52 (10), p. 38-39
Journal article
2017

Automated theory exploration for interactive theorem proving: An introduction to the hipster system

Moa Johansson
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 10499 LNCS, p. 1-11
Paper in proceeding
2017

QuickSpec: A lightweight theory exploration tool for programmers (system demonstration)

Maximilian Algehed, Koen Claessen, Moa Johansson et al
Haskell 2017 - Proceedings of the 10th ACM SIGPLAN International Symposium on Haskell, co-located with ICFP 2017, p. 38-39
Paper in proceeding
2016

Preface

Michael Kohlhase, Moa Johansson, B. Miller et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9791, p. V-VII
Other text in scientific journal
2015

TIP: Tons of Inductive Problems

Koen Lindström Claessen, Moa Johansson, Dan Rosén et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9150, p. 332-336
Paper in proceeding
2015

The Theory behind TheoryMine

A. Bundy, F. Cavallo, L. Dixon et al
IEEE Intelligent Systems. Vol. 30 (4), p. 64-69
Journal article
2015

Interpolation Systems for Ground Proofs in Automated Deduction: a Survey

M.P. Bonacina, Moa Johansson
Journal of Automated Reasoning. Vol. 54 (4), p. 353-390
Journal article
2015

On Interpolation in Automated Theorem Proving

M.P. Bonacina, Moa Johansson
Journal of Automated Reasoning. Vol. 54 (1), p. 69-97
Journal article
2015

Conditional Lemma Discovery and Recursion Induction in Hipster.

Moa Johansson, Irene Lobo Valbuena
Proceedings of the International Workshop on Automated Verification of Critical Systems (AVoCS). Electronic Communications of the EASST.. Vol. 72
Paper in proceeding
2014

Hipster: Integrating theory exploration in a proof assistant

Moa Johansson, Dan Rosén, Nicholas Smallbone et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8543, p. 108-122
Paper in proceeding
2013

Automating Inductive Proofs using Theory Exploration

Koen Lindström Claessen, Dan Rosén, Moa Johansson et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7898, p. 392-406
Paper in proceeding
2013

Proof-pattern recognition and lemma discovery in ACL2

J. Heras, E. Komendantskaya, Moa Johansson et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8312, p. 389-406
Paper in proceeding

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Showing 3 research projects

2023–2026

NeSSy: Neuro-symbolic Synthesis via Reinforcement Learning

Moa Johansson Formal methods
Swedish Research Council (VR)

2020–2023

Bias and methods of AI technology studying political behaviour

Moa Johansson Formal methods
Marianne och Marcus Wallenberg Foundation

2015–2018

Learning and Exploration in Automated Theorem Proving

Moa Johansson Software Technology (Chalmers)
Swedish Research Council (VR)

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