caa a22 4500 445835311 CHVBK 20180317145328.0 cr unu---uuuuu 170323e20111201xx s 000 0 eng 10.1007/s10515-011-0082-3 doi (NATIONALLICENCE)springer-10.1007/s10515-011-0082-3 Inferring specifications for resources from natural language API documentation [Elektronische Daten] [Hao Zhong, Lu Zhang, Tao Xie, Hong Mei] Many software libraries, especially those commercial ones, provide API documentation in natural languages to describe correct API usages. However, developers may still write code that is inconsistent with API documentation, partially because many developers are reluctant to carefully read API documentation as shown by existing research. As these inconsistencies may indicate defects, researchers have proposed various detection approaches, and these approaches need many known specifications. As it is tedious to write specifications manually for all APIs, various approaches have been proposed to mine specifications automatically. In the literature, most existing mining approaches rely on analyzing client code, so these mining approaches would fail to mine specifications when client code is not sufficient. Instead of analyzing client code, we propose an approach, called Doc2Spec, that infers resource specifications from API documentation in natural languages. We evaluated our approach on the Javadocs of five libraries. The results show that our approach performs well on real scale libraries, and infers various specifications with relatively high precisions, recalls, and F-scores. We further used inferred specifications to detect defects in open source projects. The results show that specifications inferred by Doc2Spec are useful to detect real defects in existing projects. Springer Science+Business Media, LLC, 2011 Inferring specifications nationallicence API documentation nationallicence Zhong Hao Laboratory for Internet Software Technologies, Institute of Software, Chinese Academy of Sciences, Beijing, China aut Zhang Lu School of Electronics Engineering and Computer Science, Peking University, Beijing, China aut Xie Tao Department of Computer Science, North Carolina State University, Raleigh, USA aut Mei Hong School of Electronics Engineering and Computer Science, Peking University, Beijing, China aut Automated Software Engineering Springer US; http://www.springer-ny.com 18/3-4(2011-12-01), 227-261 0928-8910 18:3-4<227 2011 18 10515 https://doi.org/10.1007/s10515-011-0082-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10515-011-0082-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhong Hao Laboratory for Internet Software Technologies, Institute of Software, Chinese Academy of Sciences, Beijing, China aut NATIONALLICENCE 700 1- Zhang Lu School of Electronics Engineering and Computer Science, Peking University, Beijing, China aut NATIONALLICENCE 700 1- Xie Tao Department of Computer Science, North Carolina State University, Raleigh, USA aut NATIONALLICENCE 700 1- Mei Hong School of Electronics Engineering and Computer Science, Peking University, Beijing, China aut NATIONALLICENCE 773 0- Automated Software Engineering Springer US; http://www.springer-ny.com 18/3-4(2011-12-01), 227-261 0928-8910 18:3-4<227 2011 18 10515 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer