Graph edit distance (GED) is a fundamental graph similarity metric. GED computation is NP-hard [10], and exact GED computation is only feasible for small graphs. Therefore, many methods of approximate GED computation have been proposed in the literature. In this paper, we select the five representative GED approximation methods and compare their performance on two real-world datasets. We observe that non-heuristic algorithms such as LSa [1] are fast and accurate in computing true GED for small graphs, and heuristic algorithms such as GENN [4] are very effective in computing the estimated path cost. This effort helps us pinpoint suitable algorithms for different applications.

Research pertaining to threat modeling is significant. However, the existing threat modeling methods suffer from ambiguity, heterogeneity and incompleteness; furthermore, the threat models at different abstraction levels are separated from each other, and the model elements are fragmented. In the knowledge engineering community, an ontology is an explicit specification of a conceptualization. Introducing the ontology method into the study of threat models is an effective way to solve the above problems. This paper creates a multiontology framework for the threat model of information systems (IS) based on domain knowledge (attack and defense knowledge), engineering experience, and industry standards (ISO/IEC 27032). The multiontology framework includes a generalized ontology (GO), a domain ontology (DO), and an application ontology (AO). This paper builds the ontology of each layer and ultimately presents case studies. The results show that the multiontology threat model based on adversarial attack and defense effectively solves the above problems of the existing threat modeling methods. In addition, systematic threat modeling using the multiontology method can be used not only for attack path-based threat analysis but also for adversarial attack and defense-based threat analysis. This method can help detect security issues and effectively guide security personnel.

Orthogonal defect classification (ODC) is a multi-dimensional measurement system with both qualitative and quantitative characteristics. And it is currently widely used in the software industry. However, its high level of abstraction leads to limited semantic information. Therefore, it seems to have a limited role in the process of software engineering of software-intensive systems (SISs). To solve this problem, this paper first analyzes software error lifetime from the perspective of knowledge-based software engineering and proposes an error generation model. Then, the paper proposes the concepts of software error pattern (SEP) and software requirements error pattern (SREP) based on the ODC. Then, according to an error generation mechanism, four types of software-hardware integrated error pattern (SHIEP) in the requirement stage, which is a sub-category of SREP, and corresponding ontology representation are given, focusing on “scenario”, “error manifestation” and “solution”. Finally, this paper takes a certain type of airborne radar software system as an example, uses protégé to edit the SHIEPs and instances, and further introduces the application of software FMEA based on the above work. The results show that the prior information based on the SHIEPs is helpful to discover potential failures and failure modes that may adversely affect the function or performance of SISs. Therefore, the proposed SHIEP is of great significance for improving the quality of software development and verification.

Avionics systems software usually has the characteristics of complex structure, wide function coverage, high reliability, and high safety. These characteristics have led to the increasing scale and complexity of software systems, and the increasing variety of research & development (R&D) personnel. This further intensify the knowledge-intensive trend of software development, and make the software requirements elicitation activities more complicated. In the knowledge engineering community, an ontology is an explicit specification of a conceptualization. This paper uses the ontology method to construct a requirement knowledge framework and requirement knowledge is expressed as a clear, complete, and consistent hierarchical ontology concept and association, which is more conducive to knowledge sharing and reuse as well as reflects multiple viewpoints of stakeholders. This paper builds a requirements knowledge multi-ontology framework which is divided into GO (generalization ontology), TO (task ontology), DO (domain ontology), and AO (application ontology). And it decomposes the GO into structure ontology and action ontology in the framework. It makes up for the deficiency of undifferentiated knowledge representation of the GO. Then, this paper proposes and integrates the concept of software requirement error pattern into the multi-ontology framework in a consistent form. In addition, this paper evaluates the quality of the constructed ontology and the evaluation results show that the constructed ontology in this paper has a high quality. Finally, this paper facilitates the requirements elicitation based on the multi-ontology framework to avoid errors and improve the quality and reliability of software products.

Failure Mode and Effect Analysis (FMEA) is a method for identifying and analyzing potential failures in systems and has been widely used for reliability and safety analysis of hardware and software systems. However, there are some shortcomings when the traditional method is applied to the system-level software FMEA, e.g., the relevant domain knowledge is scattered and not systematic, which makes the analysis result greatly depend on the experience and the familiarity of the domain to be analyzed of the analyst. Moreover, traditional methods are usually based on textual descriptions and have no tool support. These shortcomings greatly hinder the sharing and reuse of system-level software FMEA knowledge. Besides, the traditional method uses the risk priority number (RPN) to determine the priority of the failure mode, ignoring the objective attributes of the system itself, which is not reasonable enough. This paper presents a multi ontology-based system-level software fuzzy FMEA method. This method realizes the sharing and reuse of domain knowledge through the ontology. In addition, the failure mode rating method based on entropy weight and fuzzy TOPSIS overcomes the shortcoming of the traditional method and can improve the rationality of failure mode rating.

Orthogonal defect classification is a multi-dimensional measurement system with both qualitative and quantitative features, which is widely used in the software industry. However, the level of abstraction is high, which leads to limited semantic information. Therefore, it has a limited effect in the process of software engineering of complex software systems. To solve this problem, this paper first analyses the software error lifetime from the perspective of knowledge-based software engineering. Furthermore, based on the orthogonal defect classification, the concept of software error pattern is proposed, and its constituent elements and value sets are given. Moreover construct the software error pattern ontology in the requirements analysis phase, focusing on the elements such as “scenario”, “error-manifestation” and “solution”. The example verification part takes unmanned aerial vehicle flight control and management system software as an example to carry out the software requirements error pattern ontology representation and conducts software verification activities based on this and measures the development quality. The results show that the software error pattern can effectively guide the verification of complex software systems and measure the development quality. Therefore, the proposal of software error pattern is of great significance to improve the quality of software development and verification.

Because of the increasing complexity of software systems as well as the more various types of R&D personnel of the workers, software development is going to a significant trend of knowledge intensification. In the field of knowledge engineering, an ontology is an explicit specification of a conceptualization. In this paper, the ontology method is used to construct the requirement knowledge framework and the various of requirement knowledge is expressed as a clear, complete and consistent hierarchical ontology concept and association, which is more conducive to knowledge sharing and reuse as well as reflects multiple viewpoints of stakeholders. Furthermore, the relevant content of the decomposition of the generalization ontology is added in the framework, which is divided into the structure ontology and action ontology. It makes up for the deficiency of undifferentiated knowledge composition representation of the generalization ontology. Besides, the concept of software requirement error pattern is proposed and integrated into the multi-ontology framework of requirement knowledge in a consistent form. Based on the framework, the domain requirement model and the application requirement model can be built. It can be adopted as the basis of the requirement elicitation activities to avoid errors and improve the quality and reliability of software products.

The quality of unmanned aerial vehicle flight control and management system (UAV FCMS) software is crucial to guaranteeing the quality of UAVs. Software requirement elicitation (SRE) is an important part of the UAV FCMS software development process. However, this activity suffers from ambiguity, heterogeneity and incompleteness; furthermore, because the use of UAVs is closely related to their geographic environment, geographic environment factors must be fully considered when conducting UAV FCMS SRE activity. In the knowledge engineering community, an ontology is an explicit specification of a conceptualization. Introducing the ontology method into the SRE process is an effective way to solve the above problems. This paper creates a UAV FCMS SRE ontology (SREO) based on domain knowledge and empirical data, as well as a geo-ontology based on geographic information metadata. Then, the paper integrates the above two ontologies into a new ontology. The goal of ontology integration is to analyze ontology concepts by adopting a hybrid ontology mapping method. The specific process analyzes the semantic similarities between the concepts of two ontologies and then decides whether to use a description logic (DL) strategy based on the analysis results. When the corresponding conditions are satisfied, the DL strategy is used to perform both direct and transitive reasoning for the relationships to achieve the ontology mapping, and the ontology integration is eventually implemented. Finally, this paper uses a criteria-based ontology evaluation approach to evaluate the quality of the newly integrated ontology. The evaluation results show that the UAV FCMS SREO considering geographic environment factors exhibits high quality. Further engineering practices also show that the SRE activities and the generated software requirement specifications (SRSs) exhibit a large increase in quality. Through the above activities, improvements to both the quality and reliability of UAV FCMS software can be achieved.

The typical software test models include V model, W model, H model, X model, etc. However each of them has deficiency respectively; especially adopted in complex software systems. This paper presents a brand new software test model called Y model based on W model. Moreover the most prominent characteristic of Y model is that it includes abundant domain knowledge and belongs to the domain knowledge-based software test model. Thus it is necessary to construct various knowledge ontologies of this model before the execution of existing popular software test activities. This paper takes an example of software failure mode effects analysis knowledge ontology of requirements test stage to introduce the multi-ontology framework of software failure mode effects analysis knowledge, the construction process and definition of corresponding knowledge ontology. Finally the experiment takes an example of radar system to edit the software failure mode effects analysis ontology and its instances and introduces the ontology evaluation.

Nowadays the application status of Software-Intensive Systems(SISs) introduces a category of system failure caused by unforeseen operation or environment change. Generally speaking this kind of failure can be observed as system emergent behavior or degraded running. Because it relates to both the running time and state, it is called Time/State(TS)-based SISs failure. Moreover it is one of the significant sources of SISs failure. However the related researches are few. This paper presents the life cycle of software-related failure of SISs firstly. Secondly it analyzes the TS-based SISs failure mechanism and establishes the corresponding model. Moreover it introduces the traditional verification methods of SISs. Furthermore it presents the definition, classification and ontology representation of TS-based SISs failure mode. The instance validation shows the existence of TS-based SISs failure and feasibility of detecting the failure by using combined test method primarily. Finally this paper analyzes the problems and prospects the future researches.