MaeRobot: An Open Source Test Platform for Prototyping Robots

Author(s):  
Thiago de F.O. Araújo ◽  
Miguel A. de S. Falcão ◽  
Antonio M.N. Lima ◽  
Clarissa F.C.L. Loureiro
Author(s):  
Alex Roman ◽  
Parisa Dehghanzadeh ◽  
Vida Pashaei ◽  
Abhishek Basak ◽  
Swarup Bhunia ◽  
...  

2016 ◽  
Vol 48 ◽  
pp. 531
Author(s):  
Bethany Smith ◽  
Matthew Wright ◽  
Scott Sailor ◽  
Catherine Jackson ◽  
Cherie Smith

Author(s):  
Natasha M. Costa Valentim ◽  
Adriana Lopes ◽  
Edson César ◽  
Tayana Conte ◽  
Auri Marcelo Rizzo Vincenzi ◽  
...  

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 534
Author(s):  
Jungil Kim ◽  
Eunjoo Lee

Change recommendation improves the development speed and quality of software projects. Through change recommendation, software project developers can find the relevant source files that they must change for their modification tasks. In an existing change-recommendation approach based on the change history of source files, the reliability of the recommended change patterns for a source file is determined according to the change history of the source file. If a source file has insufficient change history to identify its change patterns or has frequently been changed with unrelated source files, the existing change-recommendation approach cannot identify meaningful change patterns for the source file. In this paper, we propose a novel change-recommendation approach to resolve the limitation of the existing change-recommendation method. The basic idea of the proposed approach is to consider the change history of a test file corresponding to a given source file. First, the proposed approach identifies the test file corresponding to a given source file by using a source–test traceability linking method based on the popular naming convention rule. Then, the change patterns of the source and test files are identified according to their change histories. Finally, a set of change recommendations is constructed using the identified change patterns. In an experiment involving six open-source projects, the accuracy of the proposed approach is evaluated. The results show that the accuracy of the proposed approach can be significantly improved from 21% to 62% compared with the existing approach.


Sign in / Sign up

Export Citation Format

Share Document