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Department of Computer Science

Publications

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

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

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

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

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

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

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

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. Advance online publication. https://doi.org/10.1111/ejn.14667

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

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

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

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

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

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

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

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

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

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

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

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

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). 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.

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

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

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.

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

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.

Chatterjee, K., Ibsen-Jensen, R., Goharshady, A. K. & Pavlogiannis, A. (2018). Algorithms for Algebraic Path Properties in Concurrent Systems of Constant Treewidth Components. ACM Transactions on Programming Languages and Systems, 40(3), Article 9. https://doi.org/10.1145/3210257

Chatterjee, K., Pavlogiannis, A., Koessler, A. & Schmid, U. (2018). Automated competitive analysis of real-time scheduling with graph games. Real-Time systems, 54(1), 166-207. https://doi.org/10.1007/s11241-017-9293-4

Pavlogiannis, A., Tkadlec, J., Chatterjee, K. & Nowak, M. A. (2018). Construction of arbitrarily strong amplifiers of natural selection using evolutionary graph theory. Communications Biology, 1(1), Article 71. https://doi.org/10.1038/s42003-018-0078-7

Alimadadi, S., Zhong, D., Madsen, M. & Tip, F. (2018). Finding Broken Promises in Asynchronous JavaScript Programs. Proceedings of the ACM on Programming Languages , 2(OOPSLA), 162:1-162:26. Article 162. https://doi.org/10.1145/3276532

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

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.

Chatterjee, K., Choudhary, B. & Pavlogiannis, A. (2018). Optimal Dyck Reachability for Data-Dependence and Alias Analysis. Proceedings of the ACM on Programming Languages, 2(POPL), Article 30. https://dl.acm.org/doi/abs/10.1145/3158118

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.

Adamsen, C. Q., Møller, A., Alimadadi, S. & Tip, F. (2018). Practical AJAX Race Detection for JavaScript Web Applications. In G. T. Leavens, A. Garcia & C. S. Păsăreanu (Eds.), ESEC/FSE 2018 - Proceedings of the 2018 26th ACM Joint Meeting on European So ftware Engineering Conference and Symposium on the Foundations of So ftware Engineering (pp. 38-48). Association for Computing Machinery. https://doi.org/10.1145/3236024.3236038

Li, Y., Tan, T., Møller, A. & Smaragdakis, Y. (2018). Precision-Guided Context Sensitivity for Pointer Analysis. Proceedings of the ACM on Programming Languages , 2(OOPSLA), 141:1-141:29. Article 141. https://doi.org/10.1145/3276511

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

Li, Y., Tan, T., Møller, A. & Smaragdakis, Y. (2018). Scalability-First Pointer Analysis with Self-Tuning Context-Sensitivity. In G. T. Leavens, A. Garcia & C. S. Păsăreanu (Eds.), ESEC/FSE 2018 - Proceedings of the 2018 26th ACM Joint Meeting on European So ftware Engineering Conference and Symposium on the Foundations of So ftware Engineering (pp. 129-140). Association for Computing Machinery. https://doi.org/10.1145/3236024.3236041

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

Gansonre, C., Højlund, A., Leminen, A., Bailey, C. & Shtyrov, Y. (2018). Task-free auditory EEG paradigm for probing multiple levels of speech processing in the brain. Psychophysiology, 55(11), Article e13216. https://doi.org/10.1111/psyp.13216

Møller, A. (2018). Technical Perspective: WebAssembly: A Quiet Revolution of the Web. Communications of the A C M, 61(12), 106-106. https://doi.org/10.1145/3282508

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.

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.

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

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Revised 17.04.2023

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Sofia Hedegaard Rasmussen