The software quality can be enhanced with the awareness and compassionate about the software faults. We acknowledge the impact of threshold of the object-oriented metrics on fault-proneness. The prediction of fault-prone classes in early stage of the life-cycle assures you to allocate the resources effectively. In this paper, we proposed the logistic regression based statistical method and metric threshold to reduce the false alarm for projects that fall outside the risk range. We presented the threshold effects on public datasets collected from the NASA repository and validated the use of threshold on ivy and jedit datasets. The results concluded that proposed methodology achieves the speculative results with projects having similar characteristic.

Pixel value differencing is a steganographic technique for gray scaled images. In this paper, we propose a modified pixel value differencing image steganographic scheme with least significant bit substitution method. Our method divides the cover image into the blocks of two consecutive pixels and calculates the absolute difference between the pixels of a block similar to [1, 2]. If the difference is less than a particular threshold, i.e. 15 (in this paper) than 4 bits of secret data are taken and these bits are embedded onto the LSBs of the block's pixels through least significant bit substitution method otherwise the number of bits to be hidden are selected based on some characteristics of the block and hidden. The experimental results show that our method significantly improves the quality of stego image as compared to the [1, 3] and have sufficient payload.