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Gas explosion accidents are the most serious type of accidents that cause losses in coal mines. In order to explore the pattern of unsafe actions related to such accidents and to regulate the behaviors of relevant work types in the operation process of underground coal mines, 116 serious gas explosion accidents in coal mines from 2005 to 2022 were statistically analyzed to explore the distribution characteristics of unsafe actions in different dimensions of gas explosion accidents in coal mines, to discuss the reasons for their occurrence, and to put forward targeted measures. The results show that: from the aspect of the coupling of work type and accident location, blasting operators and tile inspection operators have the highest number of unsafe actions in the face of digging and coal mining, respectively; from the aspect of the coupling of work type and laws and regulations, blasting operators are the operators with the highest frequency of violating the regulations, and the most violated regulations is the Coal Mine Safety Regulations.

The IFTTT style event-driven programming paradigm benefits normal users to build their own customized home automation Internet of things (IoT) system,meanwhile,it also brings serious safety and security risks.To handle this problem,Menshen was designed and implemented,an automated configuration,simulation and verification platform for event-driven home automation IoT system based on model checking.Users can easily set up their own smart home systems in Menshen,and conduct simulation and verification in a push-button style.Menshen could further demonstrate the error trace to help users to understand the behavior of the system and increase the safety and security of the system.An experiment with a large number of cases is carried out,and the results show that 86.7% cases are error-prone,and the verification only took 0.7 seconds in average.

A series of researches were conducted on the collection and organization of software engineering big data, software development knowledge representation and extraction, intelligent software development tools and service platforms. The purpose is to establish big data based intelligent software development technique systems, develop intelligent software development supporting tools, and form the next-generation intelligent software development environment and cloud-based platforms incorporating human, tools, and data. The outcome of the project includes a public service platform for the widespread innovation of the people and a series of intelligent software development environments for enterprises.

Bug triage aims to determine the priority and repair measures and is critical in ensuring software trustability. However, in the increasingly popular open-source projects, due to a large number of defects and lack of organization and management, it is challenging to triage all the bug reports by hand on time, making big-data based, automated and intelligent bug triage urgent. An intelligent bug triage technical framework based on industry and academia’s cognition was proposed, and three key tasks: bug priority classification, bug assignment, and bug reassignment, were identified comprehensively and systematically. Related technologies for the characteristics of open-source projects were proposed. The preliminary experiment results show the reasonableness and effectiveness of the above techniques.