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Summary Online judgment (OJ) systems are capable of evaluating program results by automatically executing test cases, significantly improving the efficiency of traditional guidance approaches. Moreover, existing studies attempt to assist novices through automated fault localization techniques to provide feedback to novices, which can help them quickly find the location of faulty statements. Among them, spectrum‐based fault localization (SBFL) techniques have been widely used for their lightweight and efficiency, which only requires coverage information and test results of test cases to conduct fault localization. However, manually constructing high‐quality test cases for a large number of OJ questions is tough work to complete. To solve this problem, we propose the novice program‐oriented Multi‐Objective Optimization‐Based Fault Localization‐Oriented Test Case Generation (MFTCG) for automatically generating test inputs. Specifically, we use multi‐objective optimization algorithms to evolve the test case in terms of both fault localization and faulty code detection capability. We conduct experiments with 8911 programs from the well‐known public OJ platform AtCoder. The results show that our proposed approach MFTCG can achieve the best fault localization performance compared with existing automated test case generation approaches in most cases and can achieve the similar faulty code detection capability compared to manually designed test cases. [ABSTRACT FROM AUTHOR]

The format string vulnerability is a kind of software vulnerability which has high risk and wide impact. Currently, there are many limitations of vulnerability detection method, such as high degree of artificial dependence, high false positive rate, single detection model and failing to consider the characteristics of the format string vulnerability fully. To solve above problems, this paper analyzed the format string vulnerability. Based on symbolic execution, the paper designed and produced a way to detect formatted string vulnerability and generate test cases automatically. This method detected the existence of the format string vulnerability in Linux binary program automatically and determined whether it could lead to harm, which allowed attackers to read or write arbitrary memory. Meanwhile it generated stable and effective test cases. [ABSTRACT FROM AUTHOR]

The generation of multiple‐path test cases can greatly enhance the efficiency of path‐wise testing. Various methods adopting meta‐heuristic algorithm to generate multiple‐path test cases have been proposed, but existing methods focus on improving the meta‐heuristic algorithm to get better test case generation efficiency, and test cases covering each path needs to be generated by meta‐heuristic algorithm searching. To improve efficiency, a test case generation method for multiple‐path coverage is proposed in this study, which combines a particle swarm optimisation (PSO) algorithm with metamorphic relations (MRs). The method first generates a test case using the PSO algorithm, and then generates new test cases by repeatedly using MRs between test cases. This method reduces evolving numbers of PSO algorithm. The experimental results show that the proposed method can significantly enhance the efficiency in terms of fitness evaluations and time consumption. [ABSTRACT FROM AUTHOR]

• We propose a formal approach to model, verify and test avionics systems. • We use intelligent agents to model the components of the landing gear system. • We introduce extended interpreted systems to reason about interactions and actions. • We introduce a testing methodology that follows a test-driven development approach. • We use MCMAS+ to generate traces for test suites achieving new coverage criteria. The paper contributes by introducing a novel, formal and operational approach that addresses the open challenging issues of modeling, verifying, and testing intelligent critical avionics systems. We advance the state-of-the-art by unifying the three challenges and considering the intelligence, autonomy, and accountability of the components as first citizen concepts. The proposed methodology is effectively applied to a real, practical and complex case study of intelligent avionics systems, namely the landing gear system and uses multi-agent systems to model each main component in the system as an intelligent agent. We also introduce the formalism of extended interpreted systems that supports intelligence, autonomy, communication, input and output actions, predicate conditions and post-conditions. The paper adopts the computation tree logic of conditional commitments to model communication among autonomous agents and trace its progress. The symbolic model checker of this logic is used to run the verification of the system model, encoded in an extended input language, against coverage criteria and properties. Furthermore, we introduce a new testing methodology that: 1) Follows a test-driven development approach; 2) performs unit testing, component testing, and system testing in each increment; and 3) uses model checking to generate automatically counterexamples and witness traces interpreted into concrete test suites that achieve new coverage criteria. The experimental results showed the efficiency and scalability of the developed approach against a transformation-based technique. Finally, the computational complexity of the developed approach is analysed. [ABSTRACT FROM AUTHOR]