Rashid Naseem

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—Software clustering is a useful technique to recover architecture of a software system. The results of clustering depend upon choice of entities, features, similarity measures and clustering algorithms. Different similarity measures have been used for determining similarity between entities during the clustering process. In software architecture recovery(More)
Clustering is a useful technique to group data entities. Many different algorithms have been proposed for software clustering. To combine the strengths of various algorithms, researchers have suggested the use of Consensus Based Techniques (CBTs), where more than one actors (e.g. algorithms) work together to achieve a common goal. Although the use of CBTs(More)
This paper proposes a feature selection technique for software clustering which can be used in the architecture recovery of software systems. The recovered architecture can then be used in the subsequent phases of software maintenance, reuse and re-engineering. A number of diverse features could be extracted from the source code of software systems,(More)
Daily large number of bug reports are received in large open and close source bug tracking systems. Dealing with these reports manually utilizes time and resources which leads to delaying the resolution of important bugs. As an important process in software maintenance, bug triaging process carefully analyze these bug reports to determine, for example,(More)
Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Researchers used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based(More)
Many different earning algorithms used for getting high performance in mathematics and statistical tasks. Recently, an Artificial Bee Colony (ABC) developed by Karaboga is a nature inspired algorithm, which has been shown excellent performance with some standard algorithms. The hybridization and improvement strategy made ABC more attractive to researchers.(More)
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