{"oa":1,"quality_controlled":"1","ec_funded":1,"year":"2017","publication_status":"published","day":"01","citation":{"short":"K. Chatterjee, H. Fu, A. Murhekar, in:, R. Majumdar, V. Kunčak (Eds.), Springer, 2017, pp. 118–139.","ama":"Chatterjee K, Fu H, Murhekar A. Automated recurrence analysis for almost linear expected runtime bounds. In: Majumdar R, Kunčak V, eds. Vol 10426. Springer; 2017:118-139. doi:<a href=\"https://doi.org/10.1007/978-3-319-63387-9_6\">10.1007/978-3-319-63387-9_6</a>","chicago":"Chatterjee, Krishnendu, Hongfei Fu, and Aniket Murhekar. “Automated Recurrence Analysis for Almost Linear Expected Runtime Bounds.” edited by Rupak Majumdar and Viktor Kunčak, 10426:118–39. Springer, 2017. <a href=\"https://doi.org/10.1007/978-3-319-63387-9_6\">https://doi.org/10.1007/978-3-319-63387-9_6</a>.","apa":"Chatterjee, K., Fu, H., &#38; Murhekar, A. (2017). Automated recurrence analysis for almost linear expected runtime bounds. In R. Majumdar &#38; V. Kunčak (Eds.) (Vol. 10426, pp. 118–139). Presented at the CAV: Computer Aided Verification, Heidelberg, Germany: Springer. <a href=\"https://doi.org/10.1007/978-3-319-63387-9_6\">https://doi.org/10.1007/978-3-319-63387-9_6</a>","ista":"Chatterjee K, Fu H, Murhekar A. 2017. Automated recurrence analysis for almost linear expected runtime bounds. CAV: Computer Aided Verification, LNCS, vol. 10426, 118–139.","ieee":"K. Chatterjee, H. Fu, and A. Murhekar, “Automated recurrence analysis for almost linear expected runtime bounds,” presented at the CAV: Computer Aided Verification, Heidelberg, Germany, 2017, vol. 10426, pp. 118–139.","mla":"Chatterjee, Krishnendu, et al. <i>Automated Recurrence Analysis for Almost Linear Expected Runtime Bounds</i>. Edited by Rupak Majumdar and Viktor Kunčak, vol. 10426, Springer, 2017, pp. 118–39, doi:<a href=\"https://doi.org/10.1007/978-3-319-63387-9_6\">10.1007/978-3-319-63387-9_6</a>."},"status":"public","date_created":"2018-12-11T11:47:35Z","editor":[{"last_name":"Majumdar","full_name":"Majumdar, Rupak","first_name":"Rupak"},{"first_name":"Viktor","full_name":"Kunčak, Viktor","last_name":"Kunčak"}],"department":[{"_id":"KrCh"}],"conference":{"name":"CAV: Computer Aided Verification","end_date":"2017-07-28","location":"Heidelberg, Germany","start_date":"2017-07-24"},"_id":"628","alternative_title":["LNCS"],"doi":"10.1007/978-3-319-63387-9_6","scopus_import":1,"intvolume":"     10426","publisher":"Springer","author":[{"last_name":"Chatterjee","orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu"},{"first_name":"Hongfei","full_name":"Fu, Hongfei","last_name":"Fu"},{"first_name":"Aniket","full_name":"Murhekar, Aniket","last_name":"Murhekar"}],"language":[{"iso":"eng"}],"date_updated":"2021-01-12T08:06:55Z","abstract":[{"text":"We consider the problem of developing automated techniques for solving recurrence relations to aid the expected-runtime analysis of programs. The motivation is that several classical textbook algorithms have quite efficient expected-runtime complexity, whereas the corresponding worst-case bounds are either inefficient (e.g., Quick-Sort), or completely ineffective (e.g., Coupon-Collector). Since the main focus of expected-runtime analysis is to obtain efficient bounds, we consider bounds that are either logarithmic, linear or almost-linear (O(log n), O(n), O(n · log n), respectively, where n represents the input size). Our main contribution is an efficient (simple linear-time algorithm) sound approach for deriving such expected-runtime bounds for the analysis of recurrence relations induced by randomized algorithms. The experimental results show that our approach can efficiently derive asymptotically optimal expected-runtime bounds for recurrences of classical randomized algorithms, including Randomized-Search, Quick-Sort, Quick-Select, Coupon-Collector, where the worst-case bounds are either inefficient (such as linear as compared to logarithmic expected-runtime complexity, or quadratic as compared to linear or almost-linear expected-runtime complexity), or ineffective.","lang":"eng"}],"date_published":"2017-01-01T00:00:00Z","main_file_link":[{"url":"https://arxiv.org/abs/1705.00314","open_access":"1"}],"type":"conference","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","month":"01","project":[{"_id":"25892FC0-B435-11E9-9278-68D0E5697425","grant_number":"ICT15-003","name":"Efficient Algorithms for Computer Aided Verification"},{"_id":"25863FF4-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"S11407","name":"Game Theory"},{"name":"Quantitative Graph Games: Theory and Applications","_id":"2581B60A-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"279307"}],"page":"118 - 139","volume":10426,"oa_version":"Submitted Version","title":"Automated recurrence analysis for almost linear expected runtime bounds","publication_identifier":{"isbn":["978-331963386-2"]},"publist_id":"7166"}