FACER: An API usage-based code-example recommender for opportunistic reuse

[1]  Shamsa Abid.  Recommending related functions from API usage-based function clone structures , 2019, ESEC/SIGSOFT FSE.

[2]  Sushil Krishna Bajracharya,et al.  Sourcerer: mining and searching internet-scale software repositories , 2008, Data Mining and Knowledge Discovery.

[3]  Robert J. Walker,et al.  Strathcona example recommendation tool , 2005, ESEC/FSE-13.

[4]  R. Holmes,et al.  Using structural context to recommend source code examples , 2005, Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005..

[5]  Brenda S. Baker,et al.  A theory of parameterized pattern matching: algorithms and applications , 1993, STOC.

[6]  Collin McMillan,et al.  Portfolio: finding relevant functions and their usage , 2011, 2011 33rd International Conference on Software Engineering (ICSE).

[7]  John J. Leggett,et al.  WLPMiner: Weighted Frequent Pattern Mining with Length-Decreasing Support Constraints , 2005, PAKDD.

[8]  Shi-Jen Lin,et al.  MACs: Mining API code snippets for code reuse , 2011, Expert Syst. Appl..

[9]  Zhenchang Xing,et al.  What do developers search for on the web? , 2017, Empirical Software Engineering.

[10]  Hamid Abdul Basit,et al.  Evolutionary Perspective of Structural Clones in Software , 2019, IEEE Access.

[11]  Koushik Sen,et al.  SNIFF: A Search Engine for Java Using Free-Form Queries , 2009, FASE.

[12]  R. Bodík,et al.  Jungloid mining: helping to navigate the API jungle , 2005, PLDI.

[13]  D. Defays,et al.  An Efficient Algorithm for a Complete Link Method , 1977, Comput. J..

[14]  Kim Mens,et al.  Source Code-Based Recommendation Systems , 2014, Recommendation Systems in Software Engineering.

[15]  Fabio Palomba,et al.  Self-Reported Activities of Android Developers , 2018, 2018 IEEE/ACM 5th International Conference on Mobile Software Engineering and Systems (MOBILESoft).

[16]  Ahmed E. Hassan,et al.  Fresh apps: an empirical study of frequently-updated mobile apps in the Google play store , 2015, Empirical Software Engineering.

[17]  Xiaodong Gu,et al.  Deep Code Search , 2018, 2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE).

[18]  Shinji Kusumoto,et al.  CCFinder: A Multilinguistic Token-Based Code Clone Detection System for Large Scale Source Code , 2002, IEEE Trans. Software Eng..

[19]  Reid Holmes,et al.  Live API documentation , 2014, ICSE.

[20]  Long Chen,et al.  Capturing source code semantics via tree-based convolution over API-enhanced AST , 2019, CF.

[21]  Xin Chen,et al.  Recommending APIs for API Related Questions in Stack Overflow , 2018, IEEE Access.

[22]  Kathryn T. Stolee,et al.  How developers search for code: a case study , 2015, ESEC/SIGSOFT FSE.

[23]  Eran Yahav,et al.  Programming with "Big Code" , 2016, Found. Trends Program. Lang..

[24]  Mira Mezini,et al.  Learning from examples to improve code completion systems , 2009, ESEC/SIGSOFT FSE.

[25]  Slinger Jansen,et al.  Pragmatic and Opportunistic Reuse in Innovative Start-up Companies , 2008, IEEE Software.

[26]  Ahmed E. Hassan,et al.  A Large-Scale Empirical Study on Software Reuse in Mobile Apps , 2014, IEEE Software.

[27]  Scott R. Klemmer,et al.  Hacking, Mashing, Gluing: Understanding Opportunistic Design , 2008, IEEE Pervasive Computing.

[28]  Wei Jiang,et al.  APISynth: a new graph-based API recommender system , 2014, ICSE Companion.

[29]  Martin T. Vechev,et al.  Code completion with statistical language models , 2014, ACM-SIGPLAN Symposium on Programming Language Design and Implementation.

[30]  Philip J. Guo,et al.  Two studies of opportunistic programming: interleaving web foraging, learning, and writing code , 2009, CHI.

[31]  Philip J. Guo,et al.  Opportunistic programming: how rapid ideation and prototyping occur in practice , 2008, WEUSE@ICSE.

[32]  Rabe Abdalkareem,et al.  On code reuse from StackOverflow: An exploratory study on Android apps , 2017, Inf. Softw. Technol..

[33]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[34]  Huan Sun,et al.  CoaCor: Code Annotation for Code Retrieval with Reinforcement Learning , 2019, WWW.

[35]  Tao Xie,et al.  Parseweb: a programmer assistant for reusing open source code on the web , 2007, ASE.

[36]  Jian Pei,et al.  MAPO: mining API usages from open source repositories , 2006, MSR '06.

[37]  Gösta Grahne,et al.  Fast algorithms for frequent itemset mining using FP-trees , 2005, IEEE Transactions on Knowledge and Data Engineering.

[38]  Koushik Sen,et al.  Aroma: code recommendation via structural code search , 2018, Proc. ACM Program. Lang..

[39]  Gang Yin,et al.  Mining and recommending software features across multiple web repositories , 2013, Internetware.

[40]  R. Wilcox.  Bivariate Analogs of the Wilcoxon–Mann–Whitney Test and the Patel–Hoel Method for Interactions , 2020 .

[41]  Jane Cleland-Huang,et al.  On-demand feature recommendations derived from mining public product descriptions , 2011, 2011 33rd International Conference on Software Engineering (ICSE).

[42]  Koushik Sen,et al.  Retrieval on source code: a neural code search , 2018, MAPL@PLDI.

[43]  Eran Yahav,et al.  Typestate-based semantic code search over partial programs , 2012, OOPSLA.

[44]  Hong Yu,et al.  Recommending Features of Mobile Applications for Developer , 2016, ADMA.

[45]  Jimmy J. Lin,et al.  Anserini: Enabling the Use of Lucene for Information Retrieval Research , 2017, SIGIR.

[46]  Hidehiko Masuhara,et al.  A spontaneous code recommendation tool based on associative search , 2011, SUITE '11.

[47]  Gerhard Fischer,et al.  Supporting reuse by delivering task-relevant and personalized information , 2002, ICSE '02.

[48]  Ying Zou,et al.  API usage pattern recommendation for software development , 2017, J. Syst. Softw..

[49]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[50]  Yan Liu,et al.  Detecting and Ranking API Usage Pattern in Large Source Code Repository: A LFM Based Approach , 2017, CD-MAKE.

[51]  Sushil Krishna Bajracharya,et al.  Leveraging usage similarity for effective retrieval of examples in code repositories , 2010, FSE '10.

[52]  Chanchal Kumar Roy,et al.  A Simple, Efficient, Context‐sensitive Approach for Code Completion , 2016, J. Softw. Evol. Process..

[53]  Cristina V. Lopes,et al.  Archetypal Internet-Scale Source Code Searching , 2008, OSS.

[54]  Gunter Saake,et al.  Software Product Lines , 2013 .

[55]  Mel Ó Cinnéide,et al.  Rascal: A Recommender Agent for Agile Reuse , 2005, Artificial Intelligence Review.

[56]  Koushik Sen,et al.  When deep learning met code search , 2019, ESEC/SIGSOFT FSE.

[57]  Gabriele Bavota,et al.  Recommending Refactoring Operations in Large Software Systems , 2014, Recommendation Systems in Software Engineering.

[58]  Ying Zou,et al.  Spotting working code examples , 2014, ICSE.

[59]  Xiaodong Gu,et al.  Deep API learning , 2016, SIGSOFT FSE.

[60]  Shinji Kusumoto,et al.  Ranking significance of software components based on use relations , 2003, IEEE Transactions on Software Engineering.