ASE 2017

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017), October 30 – November 3, 2017, Urbana-Champaign, IL, USA

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Tool Demonstrations
TiQi: A Natural Language Interface for Querying Software Project Data
Jinfeng Lin, Yalin Liu, Jin Guo, Jane Cleland-Huang, William Goss, Wenchuang Liu, Sugandha Lohar, Natawut Monaikul, and Alexander Rasin
(University of Notre Dame, USA; DePaul University, USA)
Abstract: Abstract—Software projects produce large quantities of data such as feature requests, requirements, design artifacts, source code, tests, safety cases, release plans, and bug reports. If leveraged effectively, this data can be used to provide project intelligence that supports diverse software engineering activities such as release planning, impact analysis, and software analytics. However, project stakeholders often lack skills to formulate complex queries needed to retrieve, manipulate, and display the data in meaningful ways. To address these challenges we introduce TiQi, a natural language interface, which allows users to express software-related queries verbally or written in natural language. TiQi is a web-based tool. It visualizes available project data as a prompt to the user, accepts Natural Language (NL) queries, transforms those queries into SQL, and then executes the queries against a centralized or distributed database. Raw data is stored either directly in the database or retrieved dynamically at runtime from case tools and repositories such as Github and Jira. The transformed query is visualized back to the user as SQL and augmented UML, and raw data results are returned. Our tool demo can be found on YouTube at the following link: Keywords-Natural Language Interface, Project Data, Query


Time stamp: 2019-09-22T01:24:15+02:00