Software big data has become an important feature of software technology progress. The development and quality assurance technology for the highly trusted software also have a new technical approach: data-driven. The institute carried out research on data-driven trusted software production and quality assurance technologies and platforms.

This achievement combines the data-driven approach with traditional technologies including program analysis, process evaluation and software reuse. The main features and technological innovations include: (1) From the perspective of program analysis and software testing, propose and implement the framework combining traditional program analysis technology with data-driven approach. The framework is used in software bug detection, software bug location and repair, etc., which can double the testing speed of the basic software compiler, and improve the accuracy of automatic software defect repair from 40% to 80%. (2) From the perspective of software process, break through the limitation of qualitative research in traditional research, propose a data-driven software project measurement method, and form a set of specific indicators and methods for measuring programmer capacity, project group collaboration, and community ecological in large-scale development practice; (3) From the perspective of software reuse, propose a complete set of evidence-based trusted software evaluation methods, including software information aggregation and organization technology based on information retrieval and fusion, methods for credible evidence acquisition combining objective quality and subjective evaluation, software trustworthiness rating methods based on credible evidence, establish a new set of technical approaches for the credible evaluation of software resources; (4) Create a new software reuse model of "Internet as a resource library": realize the sustainable growth of resource scale; implement distributed resources knowledge fusion, supporting multiple types of software resources such as components, services, and tools; implement intelligent resource recommendation, effectively solve the problem of large-scale resource reuse.

This achievement has published dozens of papers in top-level software engineering journals such as TSE, TOSEM, and CCF A conferences such as POPL, ICSE, FSE, ASE, etc., and won multiple conference best paper awards or was selected as a journal cover paper.

This achievement has been widely used, including the Mozilla open source community, the OW2 open source organization, large enterprises like Huawei, Digital China, Neusoft Group, as well as major software projects in Beijing, Guangzhou, Changsha and other regional software parks and Xichang and Hainan Wenchang satellite launch bases. The achievement won the first prize of the Science and Technology Progress of Ministry of Education in 2012 ("Trustie-TSE: the environment for production and sharing of trusted software resources") and the second prize of the 2015 National Technology Invention ("Network-based method and core technology for grouping development of software" ). Based on the results of this achievement, the Institute, as the project lead unit, applied for and obtained the project "Intelligent Software Development Methods and Environment Based on Big Data" from National Key R&D Program in 2016.