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Program slicing is a popular but imprecise technique for identifying which parts of a program affect or are affected by a particular value. A major reason for this imprecision is that slicing reports all program statements possibly affected by a value, regardless of how relevant to that value they really are. In this paper, we introduce quantitative slicing (q-slicing), a novel approach that quantifies the relevance of each statement in a slice. Q-slicing helps users and tools focus their attention first on the parts of slices that matter the most. We present two methods for quantifying slices and we show the promise of q-slicing for a particular application: predicting the impacts of changes. [ABSTRACT FROM AUTHOR]

Combined with Frequency-Modulated Continuous-Wave (FMCW) technology, airborne forward-looking array synthetic aperture radar (SAR) can obtain the image in front of the aircraft and also have the advantages of FMCW radar such as small size and lightweight. Moreover, it is suitable to be installed on platforms like helicopter and small unmanned aerial vehicle. To reduce the complexity of the hardware system, it is sensible to make the linear array antennas work in the time division multiplexing receiving mode. Motion compensation for forward-looking array SAR in this mode is one of the key problems to obtain the image in front of the aircraft in practice. This paper analyses the influence of motion error in aircraft on echo model based on the geometry of forward looking array SAR and proposes a motion compensation scheme. Moreover, the compensation scheme is applicable to an improved frequency scaling algorithm (FSA) for FMCW forward looking array SAR. Finally, the compensation scheme is verified with the simulation. [ABSTRACT FROM PUBLISHER]

In this paper, a cooperative particle swarm optimization algorithm using the immune clonal selection(ICS) is proposed, named CPSO-ICS. The proposed algorithm coupled with a memory scheme and multiple population. The best individual of each normal subpopulation will be selected into the memory, during the search process. The improved immune clonal selection operator is employed for optimizing the memory population while the migration scheme is employed for the communication between memory population and normal subpopulations. The performance of the proposed algorithm is tested on some standard benchmark functions, which shows a faster convergence and global search ability. Finally, the CPSO-ICS is applied to the parameter estimation of permanent magnet synchronous machines, which shows that its performance is significantly outperforms other PSOs. [ABSTRACT FROM PUBLISHER]