Software Birthmark Usability for Source Code Transformation Using Machine Learning Algorithms

Source code transformation is a way in which source code of a program is transformed by observing any operation for generating another or nearly the same program. This is mostly performed in situations of piracy where the pirates want the ownership of the software program. Various approaches are being practiced for source code transformation and code obfuscation. Researchers tried to overcome the issue of modifying the source code and prevent it from the people who want to change the source code. Among the existing approaches, software birthmark was one of the approaches developed with the aim to detect software piracy that exists in the software. Various features are extracted from software which are collectively termed as “software birthmark.” Based on these extracted features, the piracy that exists in the software can be detected. Birthmarks are considered to insist on the source code and executable of certain programming languages. The usability of software birthmark can protect software by any modification or changes and ultimately preserve the ownership of software. The proposed study has used machine learning algorithms for classification of the usability of existing software birthmarks in terms of source code transformation. The K-nearest neighbors (K-NN) algorithm was used for classification of the software birthmarks. For cross-validation, the algorithms of decision rules, decomposition tree, and LTF-C were used. The experimental results show the effectiveness of the proposed research.

A Review on Multicriteria Decision Support System and Industrial Internet of Things for Source Code Transformation

The large scale increase of communication and number of devices in the Industrial Internet of Things (IIoT) has rapidly enabled practitioners to make decisions based on multicriteria. Multicriteria decision support systems (MCDSSs) play an important role in decision-making for a particular situation based on several criteria. Making of decision based on multicriteria is the main issues for research community and practitioners of the IIoT. Several decision support systems (DSSs) are offered for making decisions which have the potentiality to support the activities of the decision-making process. The suggested study shows a review on the existing decision support systems for the IIoT for source code transformation which will enable research community and practitioners of the industry to use the existing methods, tools, approaches, and techniques and to provide novel solutions for the smooth industry of Internet of Things.

Algorithmic differentiation improves the computational efficiency of OpenSim-based optimal control simulations of movement

Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. The primarily aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based optimal control simulations. The secondary aim was to evaluate computational choices including different AD tools, different linear solvers, and the use of first- or second-order derivatives. First, we enabled the use of AD in OpenSim through a custom source code transformation tool and through the operator overloading tool ADOL-C. Second, we developed an interface between OpenSim and CasADi to perform optimal control simulations. Third, we evaluated computational choices through simulations of perturbed balance, two-dimensional predictive simulations of walking, and three-dimensional tracking simulations of walking. We performed all simulations using direct collocation and implicit differential equations. Using AD through our custom tool was between 1.8 ± 0.1 and 17.8 ± 4.9 times faster than using FD, and between 3.6 ± 0.3 and 12.3 ± 1.3 times faster than using AD through ADOL-C. The linear solver efficiency was problem-dependent and no solver was consistently more efficient. Using second-order derivatives was more efficient for balance simulations but less efficient for walking simulations. The walking simulations were physiologically realistic. These results highlight how the use of AD drastically decreases computational time of optimal control simulations as compared to more common FD. Overall, combining AD with direct collocation and implicit differential equations decreases the computational burden of optimal control simulations, which will facilitate their use for biomechanical applications.

A new code transformation technique for nested loops

For good performance of every computer program, good cache utilization is crucial. In numerical linear algebra libraries, good cache utilization is achieved by explicit loop restructuring (mainly loop blocking), but it requires a complicated memory pattern behavior analysis. In this paper, we describe a new source code transformation called dynamic loop reversal that can increase temporal and spatial locality. We also describe a formal method for predicting cache behavior and evaluate results of the model accuracy by the measurements on a cache monitor. The comparisons of the numbers of measured cache misses and the numbers of cache misses estimated by the model indicate that the model is relatively accurate and can be used in practice.