{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T09:03:50Z","timestamp":1774602230548,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2017,11,20]],"date-time":"2017-11-20T00:00:00Z","timestamp":1511136000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772200"],"award-info":[{"award-number":["61772200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Pujiang Talent Program","award":["17PJ1401900"],"award-info":[{"award-number":["17PJ1401900"]}]},{"name":"Shanghai Municipal Natural Science Foundation","award":["17ZR1406900"],"award-info":[{"award-number":["17ZR1406900"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702320"],"award-info":[{"award-number":["61702320"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Municipal Education Commission Funds of Young Teacher Training Program","award":["ZZSDJ17021"],"award-info":[{"award-number":["ZZSDJ17021"]}]},{"name":"DFG","award":["SI 2171\/2 and SI 2171\/3"],"award-info":[{"award-number":["SI 2171\/2 and SI 2171\/3"]}]},{"name":"German Research Foundation","award":["AP 206\/4, AP 206\/5, and AP 206\/7"],"award-info":[{"award-number":["AP 206\/4, AP 206\/5, and AP 206\/7"]}]},{"name":"Natural Sciences and Engineering Research Council of Canada (CA)","award":["NECSIS"],"award-info":[{"award-number":["NECSIS"]}]},{"name":"Specialized Fund of Shanghai Municipal Commission of Economy and Informatization","award":["201602008"],"award-info":[{"award-number":["201602008"]}]},{"name":"Specialized Research Fund for Doctoral Program of Higher Education","award":["20130074110015"],"award-info":[{"award-number":["20130074110015"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Empir Software Eng"],"published-print":{"date-parts":[[2018,6]]},"DOI":"10.1007\/s10664-017-9573-6","type":"journal-article","created":{"date-parts":[[2017,11,20]],"date-time":"2017-11-20T09:43:18Z","timestamp":1511170998000},"page":"1826-1867","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":90,"title":["Data-efficient performance learning for configurable systems"],"prefix":"10.1007","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5787-6781","authenticated-orcid":false,"given":"Jianmei","family":"Guo","sequence":"first","affiliation":[]},{"given":"Dingyu","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Norbert","family":"Siegmund","sequence":"additional","affiliation":[]},{"given":"Sven","family":"Apel","sequence":"additional","affiliation":[]},{"given":"Atrisha","family":"Sarkar","sequence":"additional","affiliation":[]},{"given":"Pavel","family":"Valov","sequence":"additional","affiliation":[]},{"given":"Krzysztof","family":"Czarnecki","sequence":"additional","affiliation":[]},{"given":"Andrzej","family":"Wasowski","sequence":"additional","affiliation":[]},{"given":"Huiqun","family":"Yu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,11,20]]},"reference":[{"issue":"3","key":"9573_CR1","first-page":"15","volume":"23","author":"AA Abdelaziz","year":"2011","unstructured":"Abdelaziz AA, Kadir WMW, Osman A (2011) Comparative analysis of software performance prediction approaches in context of component-based system. Int J Comput Appl 23(3):15\u201322","journal-title":"Int J Comput Appl"},{"issue":"5","key":"9573_CR2","doi-asserted-by":"publisher","first-page":"49","DOI":"10.5381\/jot.2009.8.5.c5","volume":"8","author":"S Apel","year":"2009","unstructured":"Apel S, K\u00e4stner C (2009) An overview of feature-oriented software development. J Object Tech 8(5):49\u201384","journal-title":"J Object Tech"},{"issue":"5","key":"9573_CR3","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TSE.2004.9","volume":"30","author":"S Balsamo","year":"2004","unstructured":"Balsamo S, Marco AD, Inverardi P, Simeoni M (2004) Model-based performance prediction in software development: A survey. IEEE Trans Software Eng 30(5):295\u2013310","journal-title":"IEEE Trans Software Eng"},{"issue":"1","key":"9573_CR4","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra J, Bengio Y (2012) Random search for hyper-parameter optimization. J Mach Learn Res 13(1):281\u2013305","journal-title":"J Mach Learn Res"},{"key":"9573_CR5","volume-title":"Statistical learning from a regression perspective","author":"R Berk","year":"2008","unstructured":"Berk R (2008) Statistical learning from a regression perspective. Springer, Berlin"},{"key":"9573_CR6","unstructured":"Breiman L, Friedman J, Stone C, Olshen R (1984) Classication and regression trees. Wadsworth and Brooks"},{"key":"9573_CR7","doi-asserted-by":"crossref","unstructured":"Bu X, Rao J, Xu C (2009) A reinforcement learning approach to online web systems auto-configuration. In: Proceedings of 29th IEEE international conference on distributed computing systems (ICDCS), pp 2\u201311","DOI":"10.1109\/ICDCS.2009.76"},{"issue":"1","key":"9573_CR8","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.jss.2003.05.005","volume":"74","author":"S Chen","year":"2005","unstructured":"Chen S, Liu Y, Gorton I, Liu A (2005) Performance prediction of component-based applications. J Syst Softw 74(1):35\u201343","journal-title":"J Syst Softw"},{"key":"9573_CR9","doi-asserted-by":"crossref","unstructured":"Courtois M, Woodside CM (2000) Using regression splines for software performance analysis. In: Proceedings of second international workshop on software and performance, pp 105\u2013114","DOI":"10.1145\/350391.350416"},{"key":"9573_CR10","volume-title":"Generative programming: methods, tools, and applications","author":"K Czarnecki","year":"2000","unstructured":"Czarnecki K, Eisenecker U (2000) Generative programming: methods, tools, and applications. Addison-Wesley, Boston"},{"key":"9573_CR11","unstructured":"Deisenroth M, Mohamed S, Doshi-Velez F, Krause A, Welling M (2016) ICML Workshop on data-efficient machine learning. \n                    https:\/\/sites.google.com\/site\/dataefficientml\/"},{"key":"9573_CR12","unstructured":"Domhan T, Springenberg JT, Hutter F (2015) Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves. In: Proceedings of the twenty-fourth international joint conference on artificial intelligence (IJCAI), pp 3460\u20133468"},{"key":"9573_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-4541-9","volume-title":"An introduction to the bootstrap","author":"B Efron","year":"1993","unstructured":"Efron B, Tibshirani R (1993) An introduction to the bootstrap. Chapman & Hall, Chapman"},{"key":"9573_CR14","doi-asserted-by":"crossref","unstructured":"Grechanik M, Fu C, Xie Q (2012) Automatically finding performance problems with feedback-directed learning software testing. In: Proceedings of international conference on software engineering. IEEE, pp 156\u2013166","DOI":"10.1109\/ICSE.2012.6227197"},{"key":"9573_CR15","doi-asserted-by":"crossref","unstructured":"Guo J, Czarnecki K, Apel S, Siegmund N, W\u0105sowski A (2013) Variability-aware performance prediction: a statistical learning approach. In: Proceedings of international conference on automated software engineering. IEEE, pp 301\u2013311","DOI":"10.1109\/ASE.2013.6693089"},{"key":"9573_CR16","unstructured":"Hand DJ, Mannila H, Smyth P (2001) Principles of data mining. The MIT Press, Cambridge"},{"issue":"3","key":"9573_CR17","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1109\/MS.2011.25","volume":"28","author":"J Happe","year":"2011","unstructured":"Happe J, Koziolek H, Reussner R (2011) Facilitating performance predictions using software components. IEEE Soft 28(3):27\u201333","journal-title":"IEEE Soft"},{"key":"9573_CR18","doi-asserted-by":"crossref","unstructured":"Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning data mining. In: Inference, and prediction, 2nd edn. Springer","DOI":"10.1007\/978-0-387-84858-7"},{"key":"9573_CR19","unstructured":"Hsu CW, Chang CC, Lin CJ (2003) A practical guide to support vector classification. Tech. rep., Department of Computer Science, National Taiwan University, Taipei City"},{"key":"9573_CR20","doi-asserted-by":"crossref","unstructured":"Huang P, Ma X, Shen D, Zhou Y (2014) Performance regression testing target prioritization via performance risk analysis. In: Proceedings of international conference on software engineering. ACM, pp 60\u201371","DOI":"10.1145\/2568225.2568232"},{"key":"9573_CR21","doi-asserted-by":"crossref","unstructured":"Hutter F, Hoos HH, Leyton-Brown K (2011) Sequential model-based optimization for general algorithm configuration. In: Proceedings of international conference on learning and intelligent optimization. Springer, pp 507\u2013523","DOI":"10.1007\/978-3-642-25566-3_40"},{"key":"9573_CR22","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.artint.2013.10.003","volume":"206","author":"F Hutter","year":"2014","unstructured":"Hutter F, Xu L, Hoos HH, Leyton-Brown K (2014) Algorithm runtime prediction: methods & evaluation. Artif Intell 206:79\u2013111","journal-title":"Artif Intell"},{"key":"9573_CR23","doi-asserted-by":"crossref","unstructured":"Jamshidi P, Casale G (2016) An uncertainty-aware approach to optimal configuration of stream processing systems. In: International symposium on modeling, analysis and simulation of computer and telecommunication systems, pp 39\u201348","DOI":"10.1109\/MASCOTS.2016.17"},{"key":"9573_CR24","doi-asserted-by":"crossref","unstructured":"Jovic M, Adamoli A, Hauswirth M (2011) Catch me if you can: performance bug detection in the wild. In: Proceedings of international conference on object oriented programming systems languages and applications. ACM, pp 155\u2013170","DOI":"10.1145\/2048066.2048081"},{"key":"9573_CR25","unstructured":"Kohavi R (1995) A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of international joint conference on artificial intelligence. Morgan Kaufmann, pp 1137\u20131145"},{"key":"9573_CR26","unstructured":"Kwon Y, Lee S, Yi H, Kwon D, Yang S, Chun BG, Huang L, Maniatis P, Naik M, Paek Y (2013) Mantis: automatic performance prediction for smartphone applications. In: Proceedings of the 2013 USENIX conference on annual technical conference. USENIX Association, pp 297\u2013308"},{"key":"9573_CR27","doi-asserted-by":"crossref","unstructured":"Lee BC, Brooks DM, de Supinski BR, Schulz M, Singh K, McKee SA (2007) Methods of inference and learning for performance modeling of parallel applications. In: Proceedings of the 12th ACM SIGPLAN symposium on principles and practice of parallel programming (PPOPP), pp 249\u2013258","DOI":"10.1145\/1229428.1229479"},{"issue":"8","key":"9573_CR28","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1109\/TSE.2015.2415793","volume":"41","author":"S Nadi","year":"2015","unstructured":"Nadi S, Berger T, K\u00e4stner C., Czarnecki K (2015) Where do configuration constraints stem from? An extraction approach and an empirical study. IEEE Trans Softw Eng 41(8):820\u2013841","journal-title":"IEEE Trans Softw Eng"},{"key":"9573_CR29","doi-asserted-by":"crossref","unstructured":"Osogami T, Kato S (2007) Optimizing system configurations quickly by guessing at the performance. In: Proceedings of international conference on measurement and modeling of computer systems, pp 145\u2013156","DOI":"10.1145\/1254882.1254899"},{"key":"9573_CR30","doi-asserted-by":"crossref","unstructured":"Provost FJ, Jensen D, Oates T (1999) Efficient progressive sampling. In: Proceedings of international conference on knowledge discovery and data Mining. ACM, pp 23\u201332","DOI":"10.1145\/312129.312188"},{"key":"9573_CR31","doi-asserted-by":"crossref","unstructured":"Ramirez A, Cheng B (2011) Automatic derivation of utility functions for monitoring software requirements. In: Proceedings of international conference on model driven engineering languages and systems. IEEE","DOI":"10.1007\/978-3-642-24485-8_37"},{"key":"9573_CR32","unstructured":"Salkind NJ (2003) Exploring research. Prentice Hall PTR"},{"key":"9573_CR33","doi-asserted-by":"crossref","unstructured":"Sarkar A, Guo J, Siegmund N, Apel S, Czarnecki K (2015) Cost-efficient sampling for performance prediction of configurable systems. In: Proceedings of international conference on automated software engineering. IEEE, pp 342\u2013352","DOI":"10.1109\/ASE.2015.45"},{"issue":"9","key":"9573_CR34","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1016\/j.infsof.2014.01.012","volume":"56","author":"S She","year":"2014","unstructured":"She S, Ryssel U, Andersen N, Wasowski A, Czarnecki K (2014) Efficient synthesis of feature models. Inf Soft Tech 56(9):1122\u20131143","journal-title":"Inf Soft Tech"},{"key":"9573_CR35","doi-asserted-by":"crossref","unstructured":"Siegmund N, Grebhahn A, Apel S, K\u00e4stner C (2015) Performance-influence models for highly configurable systems. In: Proceedings of international symposium on the foundations of software engineering, pp 284\u2013294","DOI":"10.1145\/2786805.2786845"},{"key":"9573_CR36","doi-asserted-by":"crossref","unstructured":"Siegmund N, Kolesnikov S, K\u00e4stner C, Apel S, Batory D, Rosenm\u00fcller M, Saake G (2012a) Predicting performance via automated feature-interaction detection. In: Proceedings of international conference on software engineering. IEEE","DOI":"10.1109\/ICSE.2012.6227196"},{"issue":"3-4","key":"9573_CR37","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1007\/s11219-011-9152-9","volume":"20","author":"N Siegmund","year":"2012","unstructured":"Siegmund N, Rosenm\u00fcller M, Kuhlemann M, K\u00e4stner C, Apel S, Saake G (2012b) SPL conqueror: toward optimization of non-functional properties in software product lines. Softw Qual J 20(3-4):487\u2013517","journal-title":"Softw Qual J"},{"key":"9573_CR38","doi-asserted-by":"crossref","unstructured":"Siegmund N, Sobernig S, Apel S (2017) Attributed variability models: outside the comfort zone. In: Proceedings of international symposium on the foundations of software engineering, pp 268\u2013278","DOI":"10.1145\/3106237.3106251"},{"key":"9573_CR39","doi-asserted-by":"crossref","unstructured":"Sincero J, Schr\u00f6der-Preikschat W, Spinczyk O (2010) Approaching non-functional properties of software product lines: learning from products. In: Proceedings of Asia-Pacific software engineering conference. IEEE","DOI":"10.1109\/APSEC.2010.26"},{"key":"9573_CR40","unstructured":"Snoek J, Larochelle H, Adams RP (2012) Practical Bayesian optimization of machine learning algorithms. In: Proceedings of 26th annual conference on neural information processing systems (NIPS), pp 2960\u20132968"},{"key":"9573_CR41","doi-asserted-by":"crossref","unstructured":"Tawhid R, Petriu D (2011) Automatic derivation of a product performance model from a software product line model. In: Proceedings of international software product line conference. IEEE, pp 80\u201389","DOI":"10.1109\/SPLC.2011.27"},{"key":"9573_CR42","doi-asserted-by":"crossref","unstructured":"Thereska E, Doebel B, Zheng A, Nobel P (2010) Practical performance models for complex, popular applications. In: Proceedings SIGMETRICS. ACM, pp 1\u201312","DOI":"10.1145\/1811039.1811041"},{"key":"9573_CR43","doi-asserted-by":"crossref","unstructured":"Valov P, Guo J, Czarnecki K (2015) Empirical comparison of regression methods for variability-aware performance prediction. In: Proceedings of international software product line conference. ACM, pp 186\u2013190","DOI":"10.1145\/2791060.2791069"},{"key":"9573_CR44","doi-asserted-by":"crossref","unstructured":"Valov P, Petkovich J, Guo J, Fischmeister S, Czarnecki K (2017) Transferring performance prediction models across different hardware platforms. In: Proceedings of the 8th ACM\/SPEC on international conference on performance engineering (ICPE), pp 39\u201350","DOI":"10.1145\/3030207.3030216"},{"key":"9573_CR45","doi-asserted-by":"crossref","unstructured":"Westermann D, Happe J, Krebs R, Farahbod R (2012) Automated inference of goal-oriented performance prediction functions. In: Proceedings of international conference on automated software engineering. ACM","DOI":"10.1145\/2351676.2351703"},{"key":"9573_CR46","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-9890-3","volume-title":"Data Mining with Rattle and R: the art of excavating data for knowledge discovery","author":"G Williams","year":"2011","unstructured":"Williams G (2011) Data Mining with Rattle and R: the art of excavating data for knowledge discovery. Springer, Berlin"},{"key":"9573_CR47","doi-asserted-by":"crossref","unstructured":"Xi B, Liu Z, Raghavachari M, Xia CH, Zhang L (2004) A smart hill-climbing algorithm for application server configuration. In: Proceedings of international conference on World Wide Web, pp 287\u2013296","DOI":"10.1145\/988672.988711"},{"key":"9573_CR48","doi-asserted-by":"crossref","unstructured":"Zhang Y, Guo J, Blais E, Czarnecki K (2015) Performance prediction of configurable software systems by fourier learning. In: Proceedings of international conference on automated software engineering. IEEE, pp 365\u2013373","DOI":"10.1109\/ASE.2015.15"},{"key":"9573_CR49","doi-asserted-by":"crossref","unstructured":"Zhang Y, Guo J, Blais E, Czarnecki K, Yu H (2016) A mathematical model of performance-relevant feature interactions. In: Proceedings of the 20th international systems and software product line conference (SPLC), pp 25\u201334","DOI":"10.1145\/2934466.2934469"}],"container-title":["Empirical Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10664-017-9573-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-017-9573-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-017-9573-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T16:41:20Z","timestamp":1568997680000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10664-017-9573-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,20]]},"references-count":49,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,6]]}},"alternative-id":["9573"],"URL":"https:\/\/doi.org\/10.1007\/s10664-017-9573-6","relation":{},"ISSN":["1382-3256","1573-7616"],"issn-type":[{"value":"1382-3256","type":"print"},{"value":"1573-7616","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11,20]]},"assertion":[{"value":"20 November 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}