Publications

2018

Contribution to book anthology

Madsen, M. & Lhoták, O. (2018). Implicit Parameters for Logic Programming. In D. Sabel & P. Thiemann (Eds.), Proceedings of the 20th International Symposium on Principles and Practice of Declarative Programming Article 14 Association for Computing Machinery. https://doi.org/10.1145/3236950.3236953

Madsen, M. & Lhoták, O. (2018). Safe and Sound Program Analysis with Flix. In E. Bodden & F. Tip (Eds.), ISSTA 2018 - Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis (pp. 38-48). Association for Computing Machinery. https://doi.org/10.1145/3213846.3213847

Madsen, M., Zarifi, R. & Lhoták, O. (2018). Tail Call Elimination and Data Representation for Functional Languages on the Java Virtual Machine. In J. Xue & C. Dubach (Eds.), CC 2018 - Proceedings of the 27th International Conference on Compiler Construction, Co-located with CGO 2018 (pp. 139-150). Association for Computing Machinery. https://doi.org/10.1145/3178372.3179499

Mezzetti, G., Møller, A. & Torp, M. T. (2018). Type Regression Testing to Detect Breaking Changes in Node.js Libraries. In T. D. Millstein (Ed.), 32nd European Conference on Object-Oriented Programming, ECOOP 2018 (Vol. 109, pp. 7:1-7:24). Article 7 Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH. https://doi.org/10.4230/LIPIcs.ECOOP.2018.7

2018

Contribution to conference

Gebauer, L., Højlund, A. & Vuust, P. (2018). The no-standard musical multi-feature paradigm (MuMUFE). Poster session presented at MMN 2018: The 8th Mismatch Negativity Conference, Helsinki, Finland.

Møller, C., Højlund, A., Hansen, N. C. & Vuust, P. (2018). Pitch-related mismatch negativity as an index of musical aptitude. Poster session presented at MMN2018: The 8th Mismatch Negativity conference, Helsinki, Finland.

Petersen, B., Friis Andersen, A. S., Dietz, M., Højlund, A., Brattico, E., Haumann, N. T., Michel, F., Kamaric Riis, S. & Vuust, P. (2018). Musical Listening in Electric Hearing –Two Novel EEG Paradigms for Studying Music Discrimination in Cochlear Implant Users. Poster session presented at 2nd International Music and CI symposium, Montreal, Canada.

Petersen, B., Friis Andersen, A. S., Dietz, M., Højlund, A., Brattico, E., Haumann, N. T., Michel, F., Kamaric Riis, S. & Vuust, P. (2018). The CI MuMuFe - a new MMN paradigm for measuring music discrimination in electric hearing. Poster session presented at MMN 2018: The 8th Mismatch Negativity Conference, Helsinki, Finland.

2019

Contribution to journal

Chatterjee, K., Goharshady, A. K., Okati, N. & Pavlogiannis, A. (2019). Efficient Parameterized Algorithms for Data Packing. Proceedings of the ACM on Programming Languages, 3(POPL), Article 53. https://doi.org/10.1145/3290366

Chatterjee, K., Goharshady, A. K., Goyal, P., Ibsen-Jensen, R. & Pavlogiannis, A. (2019). Faster algorithms for dynamic algebraicqueries in basic RSMs with constant treewidth. ACM Transactions on Programming Languages and Systems, 41(4), Article 23. https://doi.org/10.1145/3363525

Chatterjee, K., Pavlogiannis, A. & Toman, V. (2019). Value-centric Dynamic Partial Order Reduction. Proceedings of the ACM on Programming Languages, 3(OOPSLA), Article 124. https://doi.org/10.1145/3360550

Højlund, A., Gebauer, L., McGregor, W. B. & Wallentin, M. (2019). Context and perceptual asymmetry effects on the mismatch negativity (MMNm) to speech sounds: an MEG study. Language, Cognition and Neuroscience, 34(5), 545-560. https://doi.org/10.1080/23273798.2019.1572204

Kristensen, E. K. & Møller, A. (2019). Reasonably-Most-General Clients for JavaScript Library Analysis. Proceedings of the International Conference on Software Engineering, 83-93. https://doi.org/10.1109/ICSE.2019.00026

Quiroga Martinez, D. R., Hansen, N. C., Højlund, A., Pearce, M., Brattico, E. & Vuust, P. (2019). Reduced prediction error responses in high-as compared to low-uncertainty musical contexts. Cortex, 120, 181-200. https://doi.org/10.1101/422949, https://doi.org/10.1016/j.cortex.2019.06.010

Stein, B., Nielsen, B. B., Chang, B-Y. E. & Møller, A. (2019). Static Analysis with Demand-driven Value Refinement. Proceedings of the ACM on Programming Languages, 3(OOPSLA), Article 140. https://doi.org/10.1145/3360566

Tkadlec, J., Pavlogiannis, A., Chatterjee, K. & Nowak, M. A. (2019). Population structure determines the tradeoff between fixation probability and fixation time. Communications Biology, 2(1), Article 138. https://doi.org/10.1038/s42003-019-0373-y

2019

Book anthology

Dongmei, Z. & Møller, A. (Eds.) (2019). ISSTA 2019: Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis. Association for Computing Machinery. ISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis https://dl.acm.org/citation.cfm?id=3293882&picked=prox

2019

Contribution to book anthology

Møller, A. & Torp, M. T. (2019). Model-based testing of breaking changes in Node.js libraries. In S. Apel, M. Dumas, A. Russo & D. Pfahl (Eds.), ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 409-419). Association for Computing Machinery. https://doi.org/10.1145/3338906.3338940

2019

Contribution to conference

Møller, C., Højlund, A., Bærentsen, K. B., Hansen, N. C., Skewes, J. & Vuust, P. (2019). You get what you need: individual differences in visually-induced amplification of the auditory mismatch negativity. Poster session presented at Neuroscience Day 2019, Aarhus, Denmark.

Petersen, B., Friis Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Brattico, E., Michel, F., Kamaric Riis, S. & Vuust, P. (2019). Objective Measurements of Music Discrimination in Individual Experienced and Recently Implanted Cochlear Implant Users. Poster session presented at 2019 Conference on Implantable Auditory Prostheses (CIAP), Lake Tahoe, California, United States.

Petersen, B., Friis Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Brattico, E., Michel, F., Kamaric Riis, S. & Vuust, P. (2019). Objective Measurements of Music Discrimination in Individual Experienced and Recently Implanted Cochlear Implant Users. Abstract from CI2019 Pediatric: 16th Symposium on Cochlear Implants in Children, Hollywood, FL, United States.

Petersen, B., Friis Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Brattico, E., Michel, F., Kamaric Riis, S. & Vuust, P. (2019). The Sound of Music – Two Novel EEG-Paradigms for Measuring Discrimination of Music in Cochlear Implant Users. Abstract from CI2019 Pediatric: 16th Symposium on Cochlear Implants in Children, Hollywood, FL, United States.

Petersen, B., Friis Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Brattico, E., Michel, F., Kamaric Riis, S. & Vuust, P. (2019). The Sound of Music: Two Novel EEG-Paradigms for Measuring Discrimination of Music in Cochlear Implant Users. Abstract from 2019 Conference on Implantable Auditory Prostheses (CIAP), Lake Tahoe, California, United States.

2020

Contribution to journal

Hyder, R., Højlund, A., Jensen, M., Østergaard, K. & Shtyrov, Y. (2020). Objective assessment of automatic language comprehension mechanisms in the brain: Novel E/MEG paradigm. Psychophysiology, 57(5), Article e13543. https://doi.org/10.1111/psyp.13543

Li, Y., Tan, T., Møller, A. & Smaragdakis, Y. (2020). A Principled Approach to Selective Context Sensitivity for Pointer Analysis. ACM Transactions on Programming Languages and Systems, 42(2), Article 10. https://doi.org/10.1145/3381915

Pavlogiannis, A., Schaumberger, N., Schmid, U. & Chatterjee, K. (2020). Precedence-Aware Automated Competitive Analysis of Real-Time Scheduling. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(11), 3981-3992. Article 9211419. https://doi.org/10.1109/TCAD.2020.3012803

Petersen, B., Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Michel, F., Kamaric Riis, S., Brattico, E. & Vuust, P. (2020). The CI MuMuFe: A New MMN Paradigm for Measuring Music Discrimination in Electric Hearing. Frontiers in Neuroscience, 14, Article 2. https://doi.org/10.3389/fnins.2020.00002

Quiroga Martinez, D. R., Hansen, N. C., Højlund, A., Pearce, M., Brattico, E. & Vuust, P. (2020). Decomposing neural responses to melodic surprise in musicians and non-musicians: evidence for a hierarchy of predictions in the auditory system. NeuroImage, 215, Article 116816. https://doi.org/10.1016/j.neuroimage.2020.116816

Quiroga Martinez, D. R., Hansen, N. C., Højlund, A., Pearce, M., Brattico, E. & Vuust, P. (2020). Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians. European Journal of Neuroscience, 51(11), 2250-2269. https://doi.org/10.1111/ejn.14667

Tkadlec, J., Pavlogiannis, A., Chatterjee, K. & Nowak, M. A. (2020). Limits on amplifiers of natural selection under death-Birth updating. PLOS Computational Biology, 16(1), Article e1007494. https://doi.org/10.1371/journal.pcbi.1007494

Møller, A. & Veileborg, O. H. (2020). Eliminating abstraction overhead of Java stream pipelines using ahead-of-time program optimization. Proceedings of the ACM on Programming Languages, 4(OOPSLA), Article 168. https://doi.org/10.1145/3428236

Nielsen, B. B., Torp, M. T. & Møller, A. (2020). Detecting Locations in JavaScript Programs Affected by Breaking Library Changes. Proceedings of the ACM on Programming Languages, 4(OOPSLA), Article 187. https://doi.org/10.1145/3428255

Pavlogiannis, A. (2020). Fast, Sound, and Effectively Complete Dynamic Race Prediction. Proceedings of the ACM on Programming Languages, 4(POPL), 1-29. Article 17. https://doi.org/10.1145/3371085

2020

Contribution to book anthology

Asadi, A., Chatterjee, K., Goharshady, A. K., Mohammadi, K. & Pavlogiannis, A. (2020). Faster Algorithms for Quantitative Analysis of MCs and MDPs with Small Treewidth. In D. Van Hung & O. Sokolsky (Eds.), Automated Technology for Verification and Analysis - 18th International Symposium, ATVA 2020, Proceedings (pp. 253-270). Springer. https://doi.org/10.1007/978-3-030-59152-6_14

Chatterjee, K., Goharshady, A. K., Ibsen-Jensen, R. & Pavlogiannis, A. (2020). Optimal and Perfectly Parallel Algorithms for On-demand Data-Flow Analysis. In P. Müller (Ed.), Programming Languages and Systems- 29th European Symposium on Programming, ESOP 2020 held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020, Proceedings (pp. 112-140). Springer. https://doi.org/10.1007/978-3-030-44914-8_5

Endo, A. T. & Møller, A. (2020). NodeRacer: Event Race Detection for Node.js Applications. In 2020 IEEE 13th International Conference on Software Testing, Verification and Validation, ICST 2020: Proceedings (pp. 120-130). Article 9159075 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICST46399.2020.00022

Madsen, M., Lhoták, O. & Tip, F. (2020). A Semantics for the Essence of React. In R. Hirschfeld & T. Pape (Eds.), 34th European Conference on Object-Oriented Programming (ECOOP 2020) (Vol. 166, pp. 12:1-12:26). Article 12 Schloss Dagstuhl--Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ECOOP.2020.12

Madsen, M. & Lhoták, O. (2020). Fixpoints for the masses: programming with first-class Datalog constraints. In Proceedings of the ACM on Programming Languages (OOPSLA ed., Vol. 4). Association for Computing Machinery. https://doi.org/10.1145/3428193

Madsen, M. & Pol, J. V. D. (2020). Polymorphic types and effects with Boolean unification. In Proceedings of the ACM on Programming Languages (OOPSLA ed., Vol. 4). Association for Computing Machinery. https://doi.org/10.1145/3428222

Mathur, U., Pavlogiannis, A. & Viswanathan, M. (2020). The Complexity of Dynamic Data Race Prediction. In Proceedings of the 35th Annual ACM/IEEE Symposium on Logic in Computer Science, LICS 2020 (pp. 713–727). Article 3394783 Association for Computing Machinery. https://doi.org/10.1145/3373718.3394783

Nielsen, B. B. & Møller, A. (2020). Value Partitioning: A Lightweight Approach to Relational Static Analysis for JavaScript. In 34th European Conference on Object-Oriented Programming, ECOOP 2020 Article 16 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ECOOP.2020.16

Staicu, C. A., Torp, M. T., Schafer, M., Møller, A. & Pradel, M. (2020). Extracting Taint Specifications for JavaScript Libraries. In ICSE '20: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering (pp. 198-209). Article 3380390 Association for Computing Machinery. https://doi.org/10.1145/3377811.3380390

Stiévenart, Q. & Madsen, M. (2020). Fuzzing channel-based concurrency runtimes using types and effects. In Proceedings of the ACM on Programming Languages (OOPSLA ed., Vol. 4). Association for Computing Machinery. https://doi.org/10.1145/3428254

2020

Working Paper

Pavlogiannis, A. (2020). The Fine-Grained Complexity of Andersen's Pointer Analysis. ArXiv. https://arxiv.org/abs/2006.01491

2021

Contribution to journal

Chatterjee, K., Ibsen-Jensen, R. & Pavlogiannis, A. (2021). Faster algorithms for quantitative verification in bounded treewidth graphs. Formal Methods in System Design, 57(3), 401-428. https://doi.org/10.1007/s10703-021-00373-5

Hansen, J. C., Kjelstrøm, A. H. & Pavlogiannis, A. (2021). Tight bounds for reachability problems on one-counter and pushdown systems. Information Processing Letters, 171, Article 106135. https://doi.org/10.1016/j.ipl.2021.106135

Hyder, R., Jensen, M., Højlund, A., Kimppa, L., Bailey, C. J., Schaldemose, J. L., Kinnerup, M. B., Østergaard, K. & Shtyrov, Y. (2021). Functional connectivity of spoken language processing in early-stage Parkinson's disease: An MEG study. NeuroImage: Clinical, 32, Article 102718. https://doi.org/10.1016/j.nicl.2021.102718

Hyder, R., Højlund, A., Jensen, M., Johnsen, E. L., Østergaard, K. & Shtyrov, Y. (2021). STN-DBS affects language processing differentially in Parkinson's disease: Multiple-case MEG study. Acta Neurologica Scandinavica, 144(2), 132-141. https://doi.org/10.1111/ane.13423

Møller, C., Garza-Villarreal, E. A., Hansen, N. C., Højlund, A., Bærentsen, K. B., Chakravarty, M. M. & Vuust, P. (2021). Audiovisual structural connectivity in musicians and non-musicians: a cortical thickness and diffusion tensor imaging study. Scientific Reports, 11(1), Article 4324. https://doi.org/10.1038/s41598-021-83135-x

Quiroga-Martinez, D. R., Hansen, N. C., Hojlund, A., Pearce, M., Brattico, E., Holmes, E., Friston, K. & Vuust, P. (2021). Musicianship and melodic predictability enhance neural gain in auditory cortex during pitch deviance detection. Human Brain Mapping, 42(17), 5595-5608. https://doi.org/10.1002/hbm.25638

Displaying results 351 to 400 out of 444

Revised 17.04.2023

Sofia Hedegaard Rasmussen

Department of Computer Science

Publications

2018

Contribution to book anthology

2018

Contribution to conference

2019

Contribution to journal

2019

Book anthology

2019

Contribution to book anthology

2019

Contribution to conference

2020

Contribution to journal

2020

Contribution to book anthology

2020

Working Paper

2021

Contribution to journal

Magnus Madsen

Andreas Pavlogiannis

Publications

2018

Contribution to book anthology

2018

Contribution to conference

2019

Contribution to journal

2019

Book anthology

2019

Contribution to book anthology

2019

Contribution to conference

2020

Contribution to journal

2020

Contribution to book anthology

2020

Working Paper

2021

Contribution to journal

Faculty

Magnus Madsen

Andreas Pavlogiannis