We describe a new blackbox complexity testing technique for determining the worst-case asymptotic complexity of a given application. The key idea is to look for an input pattern Ðrather than a concrete inputÐ that maximizes the asymptotic resource usage of the target program. Because input patterns can be described concisely as programs in a restricted language, our method transforms the complexity testing problem to optimal program synthesis. In particular, we express these input patterns using a new model of computation called Recurrent Computation Graph (RCG) and solve the optimal synthesis problem by developing a genetic programming algorithm that operates on RCGs. We have implemented the proposed ideas in a tool called Singularity and evaluate it on a diverse set of benchmarks. Our evaluation shows that Singularity can effectively discover the worst-case complexity of various algorithms and that it is more scalable compared to existing state-of-the-art techniques. Furthermore, our experiments also corroborate that Singularity can discover previously unknown performance bugs and availability vulnerabilities in real-world applications such as Google Guava and JGraphT. CCS CONCEPTS • Software and its engineering → Software performance; Software testing and debugging; • Security and privacy → Denial-ofservice attacks;

In some particular scenes, the shadows need to be given different weights to represent the participants’ status or importance. And during the reconstruction, participants with different weights obtain various quality reconstructed images. However, the existing schemes based on visual secret sharing (VSS) and the Chinese remainder theorem (CRT) have some disadvantages. In this paper, we propose a weighted polynomial-based SIS scheme in the field of GF (257). We use k , k threshold polynomial-based secret image sharing (SIS) to generate k shares and assign them corresponding weights. Then, the remaining n − k shares are randomly filled with invalid value 0 or 255. When the threshold is satisfied, the number and weight of share can affect the reconstructed image’s quality. Our proposed scheme has the property of lossless recovery. And the average light transmission of shares in our scheme is identical. Experiments and theoretical analysis show that the proposed scheme is practical and feasible. Besides, the quality of the reconstructed image is consistent with the theoretical derivation.

A mini program code (also known as sunflower code) comes with WeChat mini program APPs. With the popularization of mini program APPs, mini program codes have become more and more widely used. As a new carrier, the study of information hiding technology based on mini program code is of great significance for the expansion of covert communication carriers and can also deal with security problems in advance. At present, to the best of our knowledge, there is no steganographic research based on mini program codes. In this paper, we propose a scheme to embed secret information into mini program codes for the first time. After studying the construction of mini program codes, a coordinate system is constructed to represent its module coordinates. Then, a binary stream of the secret message is embedded into the encoding region or the edge patch. Experiments show that the proposed data hiding scheme is effective and feasible. The embedded secret message could be extracted while keeping the readability of the mini program code. Moreover, the secret payloads of the encoding region and the edge patch for the V-36 mini program code are 72 bits and 29 bits, respectively.

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