{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T12:56:36Z","timestamp":1772196996103,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":66,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,4,20]],"date-time":"2020-04-20T00:00:00Z","timestamp":1587340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"MIUR","award":["2017TWRCNB"],"award-info":[{"award-number":["2017TWRCNB"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,4,20]]},"DOI":"10.1145\/3358960.3379134","type":"proceedings-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T07:48:26Z","timestamp":1588578506000},"page":"56-66","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Learning Queuing Networks by Recurrent Neural Networks"],"prefix":"10.1145","author":[{"given":"Giulio","family":"Garbi","sequence":"first","affiliation":[{"name":"IMT School for Advanced Studies Lucca, Lucca, Italy"}]},{"given":"Emilio","family":"Incerto","sequence":"additional","affiliation":[{"name":"IMT School for Advanced Studies Lucca, Lucca, Italy"}]},{"given":"Mirco","family":"Tribastone","sequence":"additional","affiliation":[{"name":"IMT School for Advanced Studies Lucca, Lucca, Italy"}]}],"member":"320","published-online":{"date-parts":[[2020,4,20]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Mart\u00edn Abadi Ashish Agarwal and Paul Barham et Al. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/Software available from tensorflow.org.  Mart\u00edn Abadi Ashish Agarwal and Paul Barham et Al. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/Software available from tensorflow.org."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2012.64"},{"key":"#cr-split#-e_1_3_2_1_3_1.1","doi-asserted-by":"crossref","unstructured":"Davide Arcelli Vittorio Cortellessa Antonio Filieri and Alberto Leva. 2015.Control Theory for Model-based Performance-driven Software Adaptation. In QoSA. 11--20. https:\/\/doi.org\/10.1145\/2737182.2737187 10.1145\/2737182.2737187","DOI":"10.1145\/2737182.2737187"},{"key":"#cr-split#-e_1_3_2_1_3_1.2","doi-asserted-by":"crossref","unstructured":"Davide Arcelli Vittorio Cortellessa Antonio Filieri and Alberto Leva. 2015.Control Theory for Model-based Performance-driven Software Adaptation. In QoSA. 11--20. https:\/\/doi.org\/10.1145\/2737182.2737187","DOI":"10.1145\/2737182.2737187"},{"key":"e_1_3_2_1_4_1","volume-title":"Petzold","author":"Ascher Uri M.","year":"1988","unstructured":"Uri M. Ascher and Linda R . Petzold . 1988 . Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations. SIAM. Uri M. Ascher and Linda R. Petzold. 1988. Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations. SIAM."},{"key":"e_1_3_2_1_5_1","volume-title":"Menasce","author":"Awad Mahmoud","year":"2017","unstructured":"Mahmoud Awad and Daniel A . Menasce . 2017 . Deriving Parameters for Open and Closed QN Models of Operational Systems Through Black Box Optimization. In ICPE. Mahmoud Awad and Daniel A. Menasce. 2017. Deriving Parameters for Open and Closed QN Models of Operational Systems Through Black Box Optimization. In ICPE."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2004.9"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Simonetta Balsamo and Moreno Marzolla. 2005. Performance evaluation of UML software architectures with multiclass Queueing Network models. In WOSP.  Simonetta Balsamo and Moreno Marzolla. 2005. Performance evaluation of UML software architectures with multiclass Queueing Network models. In WOSP.","DOI":"10.1145\/1071021.1071025"},{"key":"e_1_3_2_1_8_1","volume-title":"Queueing networks and Markov chains: modeling and performance evaluation with computer science applications","author":"Bolch Gunter","unstructured":"Gunter Bolch , Stefan Greiner , Hermann de Meer , and Kishor Trivedi . 2005. Queueing networks and Markov chains: modeling and performance evaluation with computer science applications . Wiley . Gunter Bolch, Stefan Greiner, Hermann de Meer, and Kishor Trivedi. 2005. Queueing networks and Markov chains: modeling and performance evaluation with computer science applications. Wiley."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.peva.2013.01.001"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Fabian Brosig Nikolaus Huber and Samuel Kounev. 2011. Automated extraction of architecture-level performance models of distributed component-based systems. In ASE.  Fabian Brosig Nikolaus Huber and Samuel Kounev. 2011. Automated extraction of architecture-level performance models of distributed component-based systems. In ASE.","DOI":"10.1109\/ASE.2011.6100052"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Fabian Brosig Samuel Kounev and Klaus Krogmann. 2009. Automated Extraction of Palladio Component Models from Running Enterprise Java Applications. In VALUETOOLS.  Fabian Brosig Samuel Kounev and Klaus Krogmann. 2009. Automated Extraction of Palladio Component Models from Running Enterprise Java Applications. In VALUETOOLS.","DOI":"10.4108\/ICST.VALUETOOLS2009.7981"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Bihuan Chen Yang Liu and Wei Le. 2016. Generating performance distributions via probabilistic symbolic execution. In ICSE.  Bihuan Chen Yang Liu and Wei Le. 2016. Generating performance distributions via probabilistic symbolic execution. In ICSE.","DOI":"10.1145\/2884781.2884794"},{"key":"e_1_3_2_1_13_1","unstructured":"Tian Qi Chen Yulia Rubanova Jesse Bettencourt and David K Duvenaud. 2018. Neural ordinary differential equations. In Advances in neural information processing systems. 6571--6583.  Tian Qi Chen Yulia Rubanova Jesse Bettencourt and David K Duvenaud. 2018. Neural ordinary differential equations. In Advances in neural information processing systems. 6571--6583."},{"key":"e_1_3_2_1_14_1","unstructured":"Fran\u00e7ois Chollet et al. 2015. Keras. https:\/\/keras.io.  Fran\u00e7ois Chollet et al. 2015. Keras. https:\/\/keras.io."},{"key":"e_1_3_2_1_15_1","volume-title":"Antinisca Di Marco, and Paola Inverardi","author":"Cortellessa Vittorio","year":"2011","unstructured":"Vittorio Cortellessa , Antinisca Di Marco, and Paola Inverardi . 2011 . Model-Based Software Performance Analysis. Springer . Vittorio Cortellessa, Antinisca Di Marco, and Paola Inverardi. 2011. Model-Based Software Performance Analysis. Springer."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13568-2_21"},{"key":"e_1_3_2_1_17_1","volume-title":"Indirect estimation of service demands in the presence of structural changes. Performance Evaluation73","author":"Cremonesi Paolo","year":"2014","unstructured":"Paolo Cremonesi and Andrea Sansottera . 2014. Indirect estimation of service demands in the presence of structural changes. Performance Evaluation73 ( 2014 ),18--40. Paolo Cremonesi and Andrea Sansottera. 2014. Indirect estimation of service demands in the presence of structural changes. Performance Evaluation73 (2014),18--40."},{"key":"e_1_3_2_1_18_1","volume-title":"WICSA 2004","author":"Di Marco A.","year":"2004","unstructured":"A. Di Marco and P. Inverardi . 2004. Compositional generation of software architecture performance QN models . In WICSA 2004 . 37--46. https:\/\/doi.org\/10.1109\/WICSA. 2004 .1310688 10.1109\/WICSA.2004.1310688 A. Di Marco and P. Inverardi. 2004. Compositional generation of software architecture performance QN models. In WICSA 2004. 37--46. https:\/\/doi.org\/10.1109\/WICSA.2004.1310688"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2008.74"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Joshua Garcia Ivo Krka Chris Mattmann and Nenad Medvidovic. 2013. Obtaining ground-truth software architectures. In ICSE. 901--910.  Joshua Garcia Ivo Krka Chris Mattmann and Nenad Medvidovic. 2013. Obtaining ground-truth software architectures. In ICSE. 901--910.","DOI":"10.1109\/ICSE.2013.6606639"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Jaco Geldenhuys Matthew B. Dwyer and Willem Visser. 2012. Probabilistic Symbolic Execution. In ISSTA. 166--176.  Jaco Geldenhuys Matthew B. Dwyer and Willem Visser. 2012. Probabilistic Symbolic Execution. In ISSTA. 166--176.","DOI":"10.1145\/2338965.2336773"},{"key":"e_1_3_2_1_22_1","volume-title":"Stochastic Simulation of Chemical Kinetics. Annual Review of Physical Chemistry58, 1","author":"Gillespie Daniel T.","year":"2007","unstructured":"Daniel T. Gillespie . 2007. Stochastic Simulation of Chemical Kinetics. Annual Review of Physical Chemistry58, 1 ( 2007 ), 35--55. Daniel T. Gillespie. 2007. Stochastic Simulation of Chemical Kinetics. Annual Review of Physical Chemistry58, 1 (2007), 35--55."},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings of the 1982 SIGPLAN Symposium on Compiler Construction (SIGPLAN'82)","author":"Graham Susan L.","unstructured":"Susan L. Graham , Peter B. Kessler , and Marshall K. Mckusick . 1982. Gprof: A Call Graph Execution Profiler . In Proceedings of the 1982 SIGPLAN Symposium on Compiler Construction (SIGPLAN'82) . 120--126. Susan L. Graham, Peter B. Kessler, and Marshall K. Mckusick. 1982. Gprof: A Call Graph Execution Profiler. In Proceedings of the 1982 SIGPLAN Symposium on Compiler Construction (SIGPLAN'82). 120--126."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"J. Guo K. Czarnecki S. Apel N. Siegmund and A. Wasowski. 2013. Variability-aware performance prediction: A statistical learning approach. In ASE.  J. Guo K. Czarnecki S. Apel N. Siegmund and A. Wasowski. 2013. Variability-aware performance prediction: A statistical learning approach. In ASE.","DOI":"10.1109\/ASE.2013.6693089"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"J. Hillston. 1996.A Compositional Approach to Performance Modelling. Cambridge University Press.  J. Hillston. 1996.A Compositional Approach to Performance Modelling. Cambridge University Press.","DOI":"10.1017\/CBO9780511569951"},{"key":"e_1_3_2_1_26_1","unstructured":"C Hrischuk J Rolia and C Murray Woodside. 1995. Automatic generation of a software performance model using an object-oriented prototype. In MASCOTS.  C Hrischuk J Rolia and C Murray Woodside. 1995. Automatic generation of a software performance model using an object-oriented prototype. In MASCOTS."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Emilio Incerto Annalisa Napolitano and Mirco Tribastone. 2018. Moving Horizon Estimation of Service Demands in Queuing Networks. In MASCOTS.  Emilio Incerto Annalisa Napolitano and Mirco Tribastone. 2018. Moving Horizon Estimation of Service Demands in Queuing Networks. In MASCOTS.","DOI":"10.1109\/MASCOTS.2018.00040"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2897053.2897060"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Emilio Incerto Mirco Tribastone and Catia Trubiani. 2017. Software Performance Self-Adaptation through Efficient Model Predictive Control. In ASE.  Emilio Incerto Mirco Tribastone and Catia Trubiani. 2017. Software Performance Self-Adaptation through Efficient Model Predictive Control. In ASE.","DOI":"10.1109\/ASE.2017.8115660"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"Pooyan Jamshidi Miguel Velez Christian K\u00e4stner and Norbert Siegmund. 2018. Learning to sample: exploiting similarities across environments to learn performance models for configurable systems. In ESEC\/FSE.  Pooyan Jamshidi Miguel Velez Christian K\u00e4stner and Norbert Siegmund. 2018. Learning to sample: exploiting similarities across environments to learn performance models for configurable systems. In ESEC\/FSE.","DOI":"10.1145\/3236024.3236074"},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the 7th International Conference on Network and Services Management. International Federation for Information Processing, 1--9.","author":"Kalbasi Amir","year":"2011","unstructured":"Amir Kalbasi , Diwakar Krishnamurthy , Jerry Rolia , and Michael Richter . 2011 . MODE: Mix driven on-line resource demand estimation . In Proceedings of the 7th International Conference on Network and Services Management. International Federation for Information Processing, 1--9. Amir Kalbasi, Diwakar Krishnamurthy, Jerry Rolia, and Michael Richter. 2011. MODE: Mix driven on-line resource demand estimation. In Proceedings of the 7th International Conference on Network and Services Management. International Federation for Information Processing, 1--9."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2019.00112"},{"key":"e_1_3_2_1_33_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Ba . 2015 . Adam : A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015,San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds .). http:\/\/arxiv.org\/abs\/1412.6980 Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015,San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http:\/\/arxiv.org\/abs\/1412.6980"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Matthias Kowal Ina Schaefer and Mirco Tribastone. 2014. Family-Based Performance Analysis of Variant-Rich Software Systems. In Fundamental Approaches to Software Engineering (FASE). 94--108.  Matthias Kowal Ina Schaefer and Mirco Tribastone. 2014. Family-Based Performance Analysis of Variant-Rich Software Systems. In Fundamental Approaches to Software Engineering (FASE). 94--108.","DOI":"10.1007\/978-3-642-54804-8_7"},{"key":"#cr-split#-e_1_3_2_1_35_1.1","doi-asserted-by":"crossref","unstructured":"Matthias Kowal Max Tschaikowski Mirco Tribastone and Ina Schaefer. 2015. Scaling Size and Parameter Spaces in Variability-Aware Software Performance Models. In ASE. 407--417. https:\/\/doi.org\/10.1109\/ASE.2015.16 10.1109\/ASE.2015.16","DOI":"10.1109\/ASE.2015.16"},{"key":"#cr-split#-e_1_3_2_1_35_1.2","doi-asserted-by":"crossref","unstructured":"Matthias Kowal Max Tschaikowski Mirco Tribastone and Ina Schaefer. 2015. Scaling Size and Parameter Spaces in Variability-Aware Software Performance Models. In ASE. 407--417. https:\/\/doi.org\/10.1109\/ASE.2015.16","DOI":"10.1109\/ASE.2015.16"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.peva.2009.07.007"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.2307\/3212147"},{"key":"e_1_3_2_1_38_1","volume-title":"Panel: AI and Performance. In International Conference on Performance Engineering (ICPE). https:\/\/icpe2019","author":"Litoiu Marin","year":"2019","unstructured":"Marin Litoiu . 2019 . Panel: AI and Performance. In International Conference on Performance Engineering (ICPE). https:\/\/icpe2019 .spec.org\/conference-program.html#session5 Marin Litoiu. 2019. Panel: AI and Performance. In International Conference on Performance Engineering (ICPE). https:\/\/icpe2019.spec.org\/conference-program.html#session5"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.peva.2004.12.001"},{"key":"e_1_3_2_1_40_1","volume-title":"Computing Missing Service Demand Parameters for Performance Models. InInt. CMG Conference. 241--248","author":"Menasce Daniel A","year":"2008","unstructured":"Daniel A Menasce . 2008 . Computing Missing Service Demand Parameters for Performance Models. InInt. CMG Conference. 241--248 . Daniel A Menasce. 2008. Computing Missing Service Demand Parameters for Performance Models. InInt. CMG Conference. 241--248."},{"key":"e_1_3_2_1_41_1","unstructured":"Tom M. Mitchell. 1997.Machine learning. McGraw-Hill. http:\/\/www.worldcat.org\/oclc\/61321007  Tom M. Mitchell. 1997.Machine learning. McGraw-Hill. http:\/\/www.worldcat.org\/oclc\/61321007"},{"key":"e_1_3_2_1_42_1","unstructured":"Object Management Group. 2007.UML Profile for Modeling and Analysis of Real-Time and Embedded Systems (MARTE). Beta 1. OMG. OMG document numberptc\/07-08-04.  Object Management Group. 2007.UML Profile for Modeling and Analysis of Real-Time and Embedded Systems (MARTE). Beta 1. OMG. OMG document numberptc\/07-08-04."},{"key":"e_1_3_2_1_43_1","volume-title":"CPU demand for web serving: Measurement analysis and dynamic estimation.Performance Evaluation65, 6--7","author":"Pacifici Giovanni","year":"2008","unstructured":"Giovanni Pacifici , Wolfgang Segmuller , Mike Spreitzer , and Asser Tantawi . 2008. CPU demand for web serving: Measurement analysis and dynamic estimation.Performance Evaluation65, 6--7 ( 2008 ), 531--553. Giovanni Pacifici, Wolfgang Segmuller, Mike Spreitzer, and Asser Tantawi. 2008. CPU demand for web serving: Measurement analysis and dynamic estimation.Performance Evaluation65, 6--7 (2008), 531--553."},{"key":"e_1_3_2_1_44_1","volume-title":"Learning state space trajectories in recurrent neural networks. Neural Computation1, 2","author":"Pearlmutter Barak A","year":"1989","unstructured":"Barak A Pearlmutter . 1989. Learning state space trajectories in recurrent neural networks. Neural Computation1, 2 ( 1989 ), 263--269. Barak A Pearlmutter. 1989. Learning state space trajectories in recurrent neural networks. Neural Computation1, 2 (1989), 263--269."},{"key":"e_1_3_2_1_45_1","volume-title":"Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models. CoRRabs\/1708.08296","author":"Samek Wojciech","year":"2017","unstructured":"Wojciech Samek , Thomas Wiegand , and Klaus-Robert M\u00fcller . 2017. Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models. CoRRabs\/1708.08296 ( 2017 ). Wojciech Samek, Thomas Wiegand, and Klaus-Robert M\u00fcller. 2017. Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models. CoRRabs\/1708.08296 (2017)."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"crossref","unstructured":"Abhishek B Sharma Ranjita Bhagwan Monojit Choudhury Leana Golubchik Ramesh Govindan and Geoffrey M Voelker. 2008. Automatic request categorization in internet services. ACM SIGMETRICS Performance Evaluation Review36 2(2008) 16--25.  Abhishek B Sharma Ranjita Bhagwan Monojit Choudhury Leana Golubchik Ramesh Govindan and Geoffrey M Voelker. 2008. Automatic request categorization in internet services. ACM SIGMETRICS Performance Evaluation Review36 2(2008) 16--25.","DOI":"10.1145\/1453175.1453179"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"crossref","unstructured":"Norbert Siegmund Alexander Grebhahn Sven Apel and Christian K\u00e4stner. 2015. Performance-influence Models for Highly Configurable Systems. In ESEC\/FSE.  Norbert Siegmund Alexander Grebhahn Sven Apel and Christian K\u00e4stner. 2015. Performance-influence Models for Highly Configurable Systems. In ESEC\/FSE.","DOI":"10.1145\/2786805.2786845"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Norbert Siegmund Sergiy S. Kolesnikov Christian K\u00e4stner Sven Apel Don Batory Marko Rosenm\u00fcller and Gunter Saake. 2012. Predicting performance viaautomated feature-interaction detection. InICSE. 167--177.  Norbert Siegmund Sergiy S. Kolesnikov Christian K\u00e4stner Sven Apel Don Batory Marko Rosenm\u00fcller and Gunter Saake. 2012. Predicting performance viaautomated feature-interaction detection. InICSE. 167--177.","DOI":"10.1109\/ICSE.2012.6227196"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.peva.2015.07.005"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"William J. Stewart. 2007. Performance Modelling and Markov Chains. In SFM. 1--33.  William J. Stewart. 2007. Performance Modelling and Markov Chains. In SFM. 1--33.","DOI":"10.1007\/978-3-540-72522-0_1"},{"key":"e_1_3_2_1_51_1","unstructured":"Charles Sutton and Michael I Jordan. 2011. Bayesian inference for queueing networks and modeling of Internet services. The Annals of Applied Statistics(2011) 254--282.  Charles Sutton and Michael I Jordan. 2011. Bayesian inference for queueing networks and modeling of Internet services. The Annals of Applied Statistics(2011) 254--282."},{"key":"e_1_3_2_1_52_1","volume-title":"Reiss","author":"Tarvo Alexander","year":"2014","unstructured":"Alexander Tarvo and Steven P . Reiss . 2014 . Automated analysis of multithreaded programs for performance modeling. InASE. Alexander Tarvo and Steven P. Reiss. 2014. Automated analysis of multithreaded programs for performance modeling. InASE."},{"key":"e_1_3_2_1_53_1","volume-title":"js: Using Java Script to build high-performance network programs","author":"Tilkov Stefan","year":"2010","unstructured":"Stefan Tilkov and Steve Vinoski . 2010. Node. js: Using Java Script to build high-performance network programs . IEEE Internet Computing 14, 6 ( 2010 ), 80--83. Stefan Tilkov and Steve Vinoski. 2010. Node. js: Using Java Script to build high-performance network programs. IEEE Internet Computing14, 6 (2010), 80--83."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"crossref","unstructured":"Mirco Tribastone. 2010. Relating layered queueing networks and process algebra models. In WOSP\/SIPEW.  Mirco Tribastone. 2010. Relating layered queueing networks and process algebra models. In WOSP\/SIPEW.","DOI":"10.1145\/1712605.1712634"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2012.66"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2011.81"},{"key":"e_1_3_2_1_57_1","volume-title":"Scalable Differential Analysis of Process Algebra Models","author":"Tribastone Mirco","year":"2012","unstructured":"Mirco Tribastone , Stephen Gilmore , and Jane Hillston . 2012. Scalable Differential Analysis of Process Algebra Models .IEEE Transactions on Software Engineering 38, 1 ( 2012 ), 205--219. https:\/\/doi.org\/10.1109\/TSE.2010.82 10.1109\/TSE.2010.82 Mirco Tribastone, Stephen Gilmore, and Jane Hillston. 2012. Scalable Differential Analysis of Process Algebra Models.IEEE Transactions on Software Engineering 38, 1 (2012), 205--219. https:\/\/doi.org\/10.1109\/TSE.2010.82"},{"key":"e_1_3_2_1_58_1","volume-title":"Leveraging Applications of Formal Methods, Verification, and Validation (Lecture Notes in Computer Science)","author":"Tribastone Mirco","year":"2010","unstructured":"Mirco Tribastone , Philip Mayer , and Martin Wirsing . 2010. Performance Prediction of Service-Oriented Systems with Layered Queueing Networks . In Leveraging Applications of Formal Methods, Verification, and Validation (Lecture Notes in Computer Science) , Tiziana Margaria and Bernhard Steffen (Eds.), Vol. 6416 . Springer , 51--65. http:\/\/cse.lab.imtlucca.it\/~mirco.tribastone\/papers\/isola 2010 .pdf Mirco Tribastone, Philip Mayer, and Martin Wirsing. 2010. Performance Prediction of Service-Oriented Systems with Layered Queueing Networks. In Leveraging Applications of Formal Methods, Verification, and Validation (Lecture Notes in Computer Science), Tiziana Margaria and Bernhard Steffen (Eds.), Vol. 6416. Springer, 51--65. http:\/\/cse.lab.imtlucca.it\/~mirco.tribastone\/papers\/isola2010.pdf"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"crossref","unstructured":"Pavel Valov Jean-Christophe Petkovich Jianmei Guo Sebastian Fischmeister and Krzysztof Czarnecki. 2017. Transferring Performance Prediction ModelsAcross Different Hardware Platforms. In ICPE.  Pavel Valov Jean-Christophe Petkovich Jianmei Guo Sebastian Fischmeister and Krzysztof Czarnecki. 2017. Transferring Performance Prediction ModelsAcross Different Hardware Platforms. In ICPE.","DOI":"10.1145\/3030207.3030216"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"crossref","unstructured":"Weikun Wang and Giuliano Casale. 2013. Bayesian service demand estimationusing Gibbs sampling. In MASCOTS.  Weikun Wang and Giuliano Casale. 2013. Bayesian service demand estimationusing Gibbs sampling. In MASCOTS.","DOI":"10.1109\/MASCOTS.2013.78"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"crossref","unstructured":"Weikun Wang Giuliano Casale Ajay Kattepur and Manoj Nambiar. 2016. Maximum likelihood estimation of closed queueing network demands from queuelength data. In ICPE.  Weikun Wang Giuliano Casale Ajay Kattepur and Manoj Nambiar. 2016. Maximum likelihood estimation of closed queueing network demands from queuelength data. In ICPE.","DOI":"10.1145\/2851553.2851565"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/FOSE.2007.32"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"crossref","unstructured":"Sergey Zagoruyko and Nikos Komodakis. 2016. Wide residual networks. arXiv preprint arXiv:1605.07146(2016).  Sergey Zagoruyko and Nikos Komodakis. 2016. Wide residual networks. arXiv preprint arXiv:1605.07146(2016).","DOI":"10.5244\/C.30.87"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"crossref","unstructured":"Dmitrijs Zaparanuks and Matthias Hauswirth. 2012. Algorithmic Profiling. In PLDI. 67--76.  Dmitrijs Zaparanuks and Matthias Hauswirth. 2012. Algorithmic Profiling. In PLDI. 67--76.","DOI":"10.1145\/2345156.2254074"}],"event":{"name":"ICPE '20: ACM\/SPEC International Conference on Performance Engineering","location":"Edmonton AB Canada","acronym":"ICPE '20","sponsor":["SIGMETRICS ACM Special Interest Group on Measurement and Evaluation","SIGSOFT ACM Special Interest Group on Software Engineering"]},"container-title":["Proceedings of the ACM\/SPEC International Conference on Performance Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3358960.3379134","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3358960.3379134","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:26Z","timestamp":1750202006000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3358960.3379134"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,20]]},"references-count":66,"alternative-id":["10.1145\/3358960.3379134","10.1145\/3358960"],"URL":"https:\/\/doi.org\/10.1145\/3358960.3379134","relation":{},"subject":[],"published":{"date-parts":[[2020,4,20]]},"assertion":[{"value":"2020-04-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}