Asked and Answered: Intelligent Data Science in Software Projects

• Applicants: Professor Dr.-Ing. Patrick Mäder; Professor Dr.-Ing. Kai-Uwe Sattler
• Subject Area: Software Engineering and Programming Languages
• Term: from 2017 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 344029884

Stakeholders of software development projects have various information needs for making rational decisions during their daily work. Studies show that receiving a direct answer to an information need is becoming one of the most desirable functions for information consumers. However, satisfying these needs requires substantial knowledge of where and how the relevant information is stored and consumes valuable time that is often not available. That leads to a situation where critical development decisions are based on gut feeling. Our research project will address this deficiency by investigating data extraction, enrichment and analytics methods on documents and data produced during all phases of the software development process. These methods will be used to develop an approach called Asked and Answered (AA) for querying and question answering on project-specific knowledge bases. Software and systems engineering projects accumulate a mass of data in the form of domain documents, requirements, safety analysis, design, code, test cases, simulations, version control data, fault logs, model checkers, project plans and so on. When combined with the power of software analytics, this data can deliver the precise answers to questions that stakeholders demand. In particular, it can support decision-making, process improvement, safety analysis, and a myriad other software engineering tasks. AA will allow project stakeholders to pose a wide-range of questions relevant to their common tasks. Answering those questions requires their transformation into an executable query, retrieving raw data from a knowledge base, executing known software analytic functions, collating the results, and then presenting an answer that is meaningful to the questioner. The proposed work will focus on three objectives: (1) identifying and defining concepts for question formulation on software artifacts; (2) extracting, maintaining, and enriching development information in a common knowledge base; and (3) developing a question answering approach for the software engineering domain. This requires tackling several challenging problems including transforming questions into executable queries; integrating software analytic functions into the data retrieval process; delivering a query engine that understands the nuances of the SE domain and optimizes queries accordingly; and integrating common SE tools and repositories into both the query and answer process. By making project data more accessible, AA supports the development and delivery of high quality, competitive software solutions. Ongoing industrial collaborations will assist us in transitioning results to practice in a timely manner. The problem we want to address is multidisciplinary as it combines software engineering and database systems concepts, making the two PIs a well-prepared team for undertaking the proposed effort.

• DFG Programme: Research Grants