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Publications

The 50 most recent publications from the Department of Software and Computer Systems:

[1]
V. Palmkvist and D. Broman, "Creating domain-specific languages by composing syntactical constructs," in 21st International Symposium on Practical Aspects of Declarative Languages, PADL 2019, 2019, pp. 187-203.
[2]
A. Gammerman et al., "Conformal and probabilistic prediction with applications : editorial," Machine Learning, vol. 108, no. 3, pp. 379-380, 2019.
[3]
U. Johansson et al., "Efficient Venn predictors using random forests," Machine Learning, vol. 108, no. 3, pp. 535-550, 2019.
[4]
T. Vasiloudis, H. Cho and H. Boström, "Block-distributed Gradient Boosted Trees," in SIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019, pp. 1025-1028.
[5]
M. Koubarakis et al., "From copernicus big data to extreme earth analytics," in Advances in Database Technology - EDBT, 2019, pp. 690-693.
[6]
M. Ismail et al., "ePipe: Near Real-Time Polyglot Persistence of HopsFS Metadata," in 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2019, pp. 92-101.
[7]
M. Rodriguez-Cancio, B. Combemale and B. Baudry, "Approximate Loop Unrolling," in CF '19 - PROCEEDINGS OF THE 16TH ACM INTERNATIONAL CONFERENCE ON COMPUTING FRONTIERS, 2019, pp. 94-105.
[8]
O. L. Vera-Perez et al., "A comprehensive study of pseudo-tested methods," Journal of Empirical Software Engineering, vol. 24, no. 3, pp. 1195-1225, 2019.
[9]
M. Boman and T. Heger, "Circles of Impression : External Foresight in Global Enterprises," in Futures Thinking and Organizational Policy, D. A. Schreiber and Z. L. Berge Ed., Cham : Palgrave Macmillan, 2019, pp. 179-199.
[10]
L. Giaretta and S. Girdzijauskas, "Gossip Learning : Off the Beaten Path," in 2019 IEEE International Conference on Big Data (IEEE Big Data 2019), December 9-12, 2019, Los Angeles, CA, USA, 2019.
[11]
N. Harrand et al., "A journey among Java neutral program variants," Genetic Programming and Evolvable Machines, vol. 20, no. 4, pp. 531-580, 2019.
[12]
R. Castañeda Lozano et al., "Combinatorial register allocation and instruction scheduling," ACM Transactions on Programming Languages and Systems, vol. 41, no. 3, 2019.
[13]
N. Safinianaini, H. Boström and V. Kaldo, "Gated hidden markov models for early prediction of outcome of internet-based cognitive behavioral therapy," in 17th Conference on Artificial Intelligence in Medicine, AIME 2019, 2019, pp. 160-169.
[14]
L. Kroll et al., "Arc : An IR for batch and stream programming," in Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2019, pp. 53-58.
[15]
L. Bahri and S. Girdzijauskas, "Blockchain technology : Practical P2P computing (Tutorial)," in Proceedings - 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems, FAS*W 2019, 2019, pp. 249-250.
[16]
P. Trunfio and V. Vlassov, "Clouds for scalable Big Data processing," International Journal of Parallel, Emergent and Distributed Systems, vol. 34, no. 6, pp. 629-631, 2019.
[17]
B. Danglot et al., "A snowballing literature study on test amplification," Journal of Systems and Software, vol. 157, 2019.
[18]
B. Danglot et al., "Automatic test improvement with DSpot : a study with ten mature open-source projects," Journal of Empirical Software Engineering, vol. 24, no. 4, pp. 2603-2635, 2019.
[19]
M. Garcia Lozano et al., "Veracity assessment of online data," Decision Support Systems, vol. 129, 2020.
[20]
L. Kroll, "Compile-time Safety and Runtime Performance in Programming Frameworks for Distributed Systems," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 13, 2020.
[21]
A. Soliman et al., "Decentralized and Adaptive K-Means Clusteringfor Non-IID Data using HyperLogLog Counters," in Proceedings of The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Singapore, 11-16 May 2020., 2020.
[22]
M. Meldrum et al., "Arcon : Continuous and deep data stream analytics," in ACM International Conference Proceeding Series, 2019.
[23]
A. Gómez-Boix et al., "A collaborative strategy for mitigating tracking through browser fingerprinting," in Proceedings of the ACM Conference on Computer and Communications Security, 2019, pp. 67-78.
[24]
N. Sheikh, Z. T. Kefato and A. Montresor, "A Simple Approach to Attributed Graph Embedding via Enhanced Autoencoder," in Complex Networks and Their Applications VIII : Volume 1 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019, 2020, pp. 797-809.
[25]
C. Soto Valero and M. Pic, "Assessing the causal impact of the 3-point per victory scoring system in the competitive balance of laliga," International Journal of Computer Science in Sport, vol. 18, no. 3, pp. 69-88, 2019.
[26]
M. Isaksson and K. Norrman, "Secure Federated Learning in 5G Mobile Networks," in IEEE Globecom 2020, 2020.
[27]
E. Castegren and K. Fernandez-Reyes, "Developing a monadic type checker for an object-oriented language : An experience report," in SLE 2019 - Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering, co-located with SPLASH 2019, 2019, pp. 184-196.
[28]
D. Broman, "A vision of miking : Interactive programmatic modeling, sound language composition, and self-learning compilation," in SLE 2019 - Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering, co-located with SPLASH 2019, 2019, pp. 55-60.
[29]
K. Hammar et al., "Deep text classification of Instagram data using word embeddings and weak supervision," WEB INTELLIGENCE, vol. 18, no. 1, pp. 53-67, 2020.
[30]
H. Linusson, U. Johansson and H. Boström, "Efficient conformal predictor ensembles," Neurocomputing, vol. 397, pp. 266-278, 2020.
[31]
[32]
R. Aler, J. M. Valls and H. Boström, "Study of Hellinger Distance as a splitting metric for Random Forests in balanced and imbalanced classification datasets," Expert systems with applications, vol. 149, 2020.
[33]
B. Danglot et al., "An approach and benchmark to detect behavioral changes of commits in continuous integration," Journal of Empirical Software Engineering, vol. 25, no. 4, pp. 2379-2415, 2020.
[34]
D. Broman and O. Eriksson, "Functional programmatic modeling in modelyze," in ACM International Conference Proceeding Series, 2019.
[35]
S. Natarajan et al., "From code to weakly hard constraints : A pragmatic end-to-end toolchain for timed C," in Proceedings - Real-Time Systems Symposium, 2019, pp. 167-180.
[36]
R. Senise et al., "Preface," World Review of Science, Technology and Sustainable Development, vol. 16, no. 1, pp. 1-3, 2020.
[37]
U. Johansson et al., "Customized interpretable conformal regressors," in Proceedings - 2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019, 2019, pp. 221-230.
[38]
J. Cabrera Arteaga et al., "Superoptimization of WebAssembly bytecode," in Conference Companion of the 4th International Conference on Art, Science, and Engineering of Programming, 2020.
[39]
U. Johansson, T. Löfström and H. Boström, "Calibrating probability estimation trees using Venn-Abers predictors," in SIAM International Conference on Data Mining, SDM 2019, 2019, pp. 28-36.
[40]
S. Haridi, "A history of the Oz multiparadigm language," History of Programming Languages HOPL-4, vol. 4, no. 83, pp. 1-56, 2020.
[41]
F. E. Eassa et al., "ACC_TEST : Hybrid Testing Approach for OpenACC-Based Programs," IEEE Access, vol. 8, pp. 80358-80368, 2020.
[42]
N. Harrand et al., "Java decompiler diversity and its application to meta-decompilation," Journal of Systems and Software, vol. 168, 2020.
[43]
J. L. Wessén, C. Schulte and M. Carlsson, "Scheduling of Dual-Arm Multi-Tool Assembly Robots and Workspace Layout Optimization," in Proceedings of 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research,, 2020.
[44]
J. Zeng, "Augmenting Transactional Memory with the Future Abstraction," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2020:50, 2020.
[45]
S. Pozzoli et al., "Domain expertise–agnostic feature selection for the analysis of breast cancer data," Artificial Intelligence in Medicine, vol. 108, 2020.
[46]
Z. T. Kefato, "Gossip and Attend: Context-Sensitive Graph Representation Learning," in In Proc. of the 14-th International AAAI Conference on Web and Social Media, ICWSM'20, 2020.
[48]
L. Zhang et al., "A Chaos Engineering System for Live Analysis and Falsification of Exception-handling in the JVM," IEEE Transactions on Software Engineering, 2019.
[49]
L. Strandberg and I. Nyqvist, "Visualisering av vägdata i en AR-app," , 2020.
[50]
L. Giaretta and S. Girdzijauskas, "Gossip Learning : Off the Beaten Path," in 2019 IEEE international conference on big data (big data), 2019, pp. 1117-1124.
Full list in the KTH publications portal
Page responsible:Web editors at EECS
Belongs to: Software and Computer Systems
Last changed: Apr 12, 2018