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Component‐based development has emerged as a system engineering approach that promises rapid software development with fewer resources. Yet, improved reuse and reduced cost benefits from software components can only be achieved in practice if the components provide reliable services, thereby rendering component analysis and testing a key activity. This paper discusses various issues that can arise in component testing by the component user at the stage of its integration within the target system. The crucial problem is the lack of information for analysis and testing of externally developed components. Several testing techniques for component integration have recently been proposed. These techniques are surveyed here and classified according to a proposed set of relevant attributes. The paper thus provides a comprehensive overview which can be useful as introductory reading for newcomers in this research field, as well as to stimulate further investigation. Copyright © 2006 John Wiley & Sons, Ltd.

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Active noise control algorithms undergo stability problems in the presence of impulsive noise. This paper investigates such algorithms with online secondary path modeling for impulsive noise and varying acoustic paths. The paper presents three methods for active noise control, along with improved online secondary path modeling. Firstly, the filtered x recursive least square algorithm is applied for both active noise control and online secondary path modeling. This method gave faster convergence, improved stability, and modeling accuracy as compared to existing ones. The filtered x recursive least square algorithm is not robust for abruptly changing acoustic paths. To overcome this problem another method that uses modified gain filtered x recursive least square algorithm for active noise control is presented. Furthermore, it is observed that modified gain filtered x recursive least square achieves the desired performance with overheads of increased complexity. Thus, a hybrid method is proposed which has less computational complexity than the rest methods with no compromise on active noise control system performance.

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