001447719 000__ 04361cam\a2200529\a\4500 001447719 001__ 1447719 001447719 003__ OCoLC 001447719 005__ 20230310004131.0 001447719 006__ m\\\\\o\\d\\\\\\\\ 001447719 007__ cr\un\nnnunnun 001447719 008__ 220625s2022\\\\si\\\\\\ob\\\\000\0\eng\d 001447719 019__ $$a1330896430 001447719 020__ $$a9789811696435$$q(electronic bk.) 001447719 020__ $$a9811696438$$q(electronic bk.) 001447719 020__ $$z981169642X 001447719 020__ $$z9789811696428 001447719 0247_ $$a10.1007/978-981-16-9643-5$$2doi 001447719 035__ $$aSP(OCoLC)1333081393 001447719 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dGW5XE$$dYDX$$dEBLCP$$dOCLCF$$dOCLCQ$$dUKAHL$$dOCLCQ 001447719 049__ $$aISEA 001447719 050_4 $$aQA76.76.T48 001447719 08204 $$a005.1/4$$223/eng/20220629 001447719 24500 $$aIntelligent crowdsourced testing /$$cQing Wang, Zhenyu Chen, Junjie Wang, Yang Feng, editors. 001447719 260__ $$aSingapore :$$bSpringer,$$c2022. 001447719 300__ $$a1 online resource (251 pages) 001447719 336__ $$atext$$btxt$$2rdacontent 001447719 337__ $$acomputer$$bc$$2rdamedia 001447719 338__ $$aonline resource$$bcr$$2rdacarrier 001447719 504__ $$aIncludes bibliographical references. 001447719 5050_ $$aPart I Preliminary of Crowdsourced Testing -- 1 Introduction -- 2 Preliminaries -- 3 Book Structure -- Part II Supporting Technology for Crowdsourced Testing Workers -- 4 Characterization of Crowd Worker -- 5 Task Recommendation for Crowd Worker -- Part III Supporting Technology for Crowdsourced Testing Tasks -- 6 Crowd Worker Recommendation for Testing Task -- 7 Crowdsourced Testing Task Management -- Part IV Supporting Technology for Crowdsourced Testing Results -- 8 Classification of Crowdsourced Testing Reports -- 9 Duplicate Detection of Crowdsourced Testing Reports -- 10 Prioritization of Crowdsourced Testing Reports -- 11 Summarization of Crowdsourced Testing Reports -- 12 Quality Assessment of Crowdsourced Testing Cases -- Part V Conclusions and Future Perspectives -- 13 Conclusions -- 14 Perspectives. 001447719 506__ $$aAccess limited to authorized users. 001447719 520__ $$aIn an article for Wired Magazine in 2006, Jeff Howe defined crowdsourcing as an idea for outsourcing a task that is traditionally performed by a single employee to a large group of people in the form of an open call. Since then, by modifying crowdsourcing into different forms, some of the most successful new companies on the market have used this idea to make peoples lives easier and better. On the other hand, software testing has long been recognized as a time-consuming and expensive activity. Mobile application testing is especially difficult, largely due to compatibility issues: a mobile application must work on devices with different operating systems (e.g. iOS, Android), manufacturers (e.g. Huawei, Samsung) and keypad types (e.g. virtual keypad, hard keypad). One cannot be 100% sure that, just because a tested application works well on one device, it will run smoothly on all others. Crowdsourced testing is an emerging paradigm that can improve the cost-effectiveness of software testing and accelerate the process, especially for mobile applications. It entrusts testing tasks to online crowdworkers whose diverse testing devices/contexts, experience, and skill sets can significantly contribute to more reliable, cost-effective and efficient testing results. It has already been adopted by many software organizations, including Google, Facebook, Amazon and Microsoft. This book provides an intelligent overview of crowdsourced testing research and practice. It employs machine learning, data mining, and deep learning techniques to process the data generated during the crowdsourced testing process, to facilitate the management of crowdsourced testing, and to improve the quality of crowdsourced testing. 001447719 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 29, 2022). 001447719 650_0 $$aComputer software$$xTesting. 001447719 650_0 $$aCrowdsourcing. 001447719 655_0 $$aElectronic books. 001447719 7001_ $$aWang, Qing. 001447719 7001_ $$aChen, Zhenyu. 001447719 7001_ $$aWang, Junjie. 001447719 7001_ $$aFeng, Yang. 001447719 77608 $$iPrint version:$$aWang, Qing.$$tIntelligent Crowdsourced Testing.$$dSingapore : Springer, ©2022$$z9789811696428 001447719 852__ $$bebk 001447719 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-9643-5$$zOnline Access$$91397441.1 001447719 909CO $$ooai:library.usi.edu:1447719$$pGLOBAL_SET 001447719 980__ $$aBIB 001447719 980__ $$aEBOOK 001447719 982__ $$aEbook 001447719 983__ $$aOnline 001447719 994__ $$a92$$bISE