DocumentCode
731527
Title
Employing Source Code Information to Improve Question-Answering in Stack Overflow
Author
Diamantopoulos, Themistoklis ; Symeonidis, Andreas L.
Author_Institution
Electr. & Comput. Eng. Dept., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
fYear
2015
fDate
16-17 May 2015
Firstpage
454
Lastpage
457
Abstract
Nowadays, software development has been greatly influenced by question-answering communities, such as Stack Overflow. A new problem-solving paradigm has emerged, as developers post problems they encounter that are then answered by the community. In this paper, we propose a methodology that allows searching for solutions in Stack Overflow, using the main elements of a question post, including not only its title, tags, and body, but also its source code snippets. We describe a similarity scheme for these elements and demonstrate how structural information can be extracted from source code snippets and compared to further improve the retrieval of questions. The results of our evaluation indicate that our methodology is effective on recommending similar question posts allowing community members to search without fully forming a question.
Keywords
question answering (information retrieval); software engineering; source code (software); question-answering; similarity scheme; software development; source code information; source code snippets; stack overflow; structural information; Communities; Data mining; HTML; Indexes; Java; Search problems; Software; Indexing; Search Engines; Source Code Mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Mining Software Repositories (MSR), 2015 IEEE/ACM 12th Working Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/MSR.2015.62
Filename
7180116
Link To Document