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]
H. Peiro Sajjad, "Methods and Algorithms for Data-Intensive Computing : Streams, Graphs, and Geo-Distribution," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2019:13, 2019.
[3]
A. Gammerman et al., "Conformal and probabilistic prediction with applications : editorial," Machine Learning, vol. 108, no. 3, pp. 379-380, 2019.
[4]
U. Johansson et al., "Efficient Venn predictors using random forests," Machine Learning, vol. 108, no. 3, pp. 535-550, 2019.
[5]
I. Oz et al., "Regression-Based Prediction for Task-Based Program Performance," Journal of Circuits, Systems and Computers, vol. 28, no. 4, 2019.
[6]
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.
[7]
M. Alferez et al., "Modeling variability in the video domain : language and experience report," Software quality journal, vol. 27, no. 1, pp. 307-347, 2019.
[8]
M. Koubarakis et al., "From copernicus big data to extreme earth analytics," in Advances in Database Technology - EDBT, 2019, pp. 690-693.
[9]
X. Lin et al., "Message from the BDCloud 2018 Chairs," 16th IEEE International Symposium on Parallel and Distributed Processing with Applications, 17th IEEE International Conference on Ubiquitous Computing and Communications, 8th IEEE International Conference on Big Data and Cloud Computing, 11th IEEE International Conference on Social Computing and Networking and 8th IEEE International Conference on Sustainable Computing and Communications, ISPA/IUCC/BDCloud/SocialCom/SustainCom 2018, pp. XXIX-XXX, 2019.
[10]
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.
[11]
S. Niazi et al., "HopsFS: Scaling Hierarchical File System Metadata Using NewSQL Databases," in Encyclopedia of Big Data Technologies, Sherif Sakr, Albert Y. Zomaya Ed., : Springer, 2019, pp. 16-32.
[12]
K. Hakimzadeh and J. Dowling, "Karamel : A System for Timely Provisioning Large-Scale Software Across IaaS Clouds," in 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), 2019, pp. 391-395.
[13]
K. Hakimzadeh and J. Dowling, "Ops-Scale : Scalable and Elastic Cloud Operations by a Functional Abstraction and Feedback Loops," in 2019 IEEE 13th International Conference on Self-Adaptive And Self-Organizing Systems (SASO), 2019, pp. 62-71.
[14]
M. Ismail et al., "Scalable Block Reporting for HopsFS," in 2019 IEEE International Congress on Big Data (BigData Congress), 2019, pp. 157-164.
[15]
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.
[16]
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.
[17]
R. Castañeda Lozano and C. Schulte, "Survey on Combinatorial Register Allocation and Instruction Scheduling," ACM Computing Surveys, vol. 52, no. 3, 2019.
[18]
B. Åkerblom, E. Castegren and T. Wrigstad, "Progress Report : Exploring API Design for Capabilities for Programming with Arrays," in ECOOP 2019, 2019.
[19]
N. Apolonia et al., "Socially aware microcloud service overlay optimization in community networks," Software, practice & experience, vol. 49, no. 1, 2019.
[20]
M. Boman et al., "Learning machines in Internet-delivered psychological treatment," Progress in artificial intelligence, vol. 8, no. 4, pp. 475-485, 2019.
[21]
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.
[22]
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.
[23]
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.
[24]
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.
[25]
B. Danglot et al., "A snowballing literature study on test amplification," Journal of Systems and Software, vol. 157, 2019.
[26]
J. Cabrera Arteaga, M. Monperrus and B. Baudry, "Scalable comparison of JavaScript V8 bytecode traces," in VMIL 2019, SPLASH, 2019, pp. 22-31.
[27]
R. Castañeda Lozano et al., "Combinatorial register allocation and instruction scheduling," ACM Transactions on Programming Languages and Systems, vol. 41, no. 3, 2019.
[28]
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.
[29]
P. Laperdrix et al., "Morellian analysis for browsers : Making web authentication stronger with canvas fingerprinting," in Detection of Intrusions and Malware, and Vulnerability Assessment : 16th International Conference, DIMVA 2019, Gothenburg, Sweden, June 19–20, 2019, Proceedings, 2019, pp. 43-66.
[30]
T. Vasiloudis, G. D. F. Morales and H. Boström, "Quantifying Uncertainty in Online Regression Forests," Journal of machine learning research, vol. 20, pp. 1-35, 2019.
[31]
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.
[32]
N. Harrand et al., "A journey among Java neutral program variants," Genetic Programming and Evolvable Machines, vol. 20, no. 4, pp. 531-580, 2019.
[33]
K. Ghoorchian, "Graph Algorithms for Large-Scale and Dynamic Natural Language Processing," Doctoral thesis : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2019:85, 2019.
[34]
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.
[35]
S. Frimodig and C. Schulte, "Models for Radiation Therapy Patient Scheduling," in 25th International Conference on Principles and Practice of Constraint Programming, CP 2019, 2019, pp. 421-437.
[36]
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.
[37]
M. Garcia Lozano et al., "Veracity assessment of online data," Decision Support Systems, vol. 129, 2020.
[38]
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.
[39]
M. Meldrum et al., "Arcon : Continuous and deep data stream analytics," in ACM International Conference Proceeding Series, 2019.
[40]
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.
[41]
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.
[42]
H. Linusson, U. Johansson and H. Boström, "Efficient conformal predictor ensembles," Neurocomputing, 2019.
[43]
S. Imtiaz, R. Sadre and V. Vlassov, "On the case of privacy in the iot ecosystem : a survey," in Proceedings - 2019 IEEE International Congress on Cybermatics: 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019, 2019, pp. 1015-1024.
[44]
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.
[45]
[46]
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.
[47]
M. Isaksson and K. Norrman, "Secure Federated Learning in 5G Mobile Networks," (Manuscript).
[48]
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.
[49]
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.
[50]
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.
Full list in the KTH publications portal
Page responsible:Web editors at EECS
Belongs to: Software and Computer Systems
Last changed: Apr 12, 2018