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Symbolic execution is a well-studied method that has a number of useful applications, including generation of high-quality test suites that find many bugs. However, scaling it to real-world applications is a significant challenge, as it depends on the often expensive process of solving constraints on program inputs. Our insight is that when the goal of symbolic execution is test generation, non-semantics-preserving...
This paper introduces two complementary techniques, memoization-based and dependency-based incremental symbolic execution, that aim to optimize the analysis of state machine models that undergo change. We implement the two proposed techniques on IBM Rhapsody Statecharts and present some evaluation results.
Recently code transformations or tailored fitness functions are adopted to achieve coverage (structural or logical criterion) driven testing to ensure software reliability. However, some internal threats like negative impacts on underlying search strategies or local maximum exist. So we propose a dynamic symbolic execution (DSE) based framework combined with a path filtering algorithm and a new heuristic...
Complex Event Processing (CEP) is a powerful technology for implementing real time applications. It offers efficient processing of occurring information pieces, so called events, based on an architecture that provides strong decoupling of its components: event producer, event processors and event consumer [4]. For this CEP is seen as an important contribution in future information systems. CEP applications...
Test coverage such as branch coverage is commonly measured to assess the sufficiency of test inputs. To reduce tedious manual efforts in generating high-covering test inputs, various automated techniques have been proposed. Some recent effective techniques include Dynamic Symbolic Execution (DSE) based on path exploration. However, these existing DSE techniques cannot generate high-covering test inputs...
To deal with any possible cases for training anti-spam machine learning models, it is crucial to design a safe way to shrink the size of training sample set via reducing redundancies with minimal information loss for classification as well as make distribution of samples balanced. Presently, there is no such solution to do so. In this paper, we propose a safe approach to address these problems and...
In this paper a BISR architecture for embedded memories is presented. The proposed scheme utilises a multiple bank cache-like memory for repairs. Statistical analysis is used for minimisation of the total resources required to achieve a very high fault coverage. Simulation results show that the proposed BISR scheme is characterised by high efficiency and low area overhead, even for high defect densities...
In a real world, it is often in a group setting that sensitive information has to be stored in databases of a server. Although personal information does not need to be stored in a server, the secret information shared by group members is likely to be stored there. The shared sensitive information requires more security and privacy protection. To our best knowledge, there is no paper which deals with...
Texture is an important property of fire smoke, which is a significant signal for early fire detection. This paper describes a method of analyzing the texture of fire smoke combining two innovative texture analysis tools, Wavelet Analysis and Gray Level Cooccurrence Matrices (GLCM). Tree-Structured Wavelet transform is used to represent the textural images and GLCM are used to compute the different...
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