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)
In recent years, there has been increasing interest in exploring clustering as a technique to recover the architecture of software systems. The efficacy of clustering depends not only on the clustering algorithm, but also on the choice of entities, features and similarity measures used during clustering. It is also important to understand characteristics of(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)
Sentiment analysis is the process to study of people opinion, emotion and way of considering a matter and take decision into different categorizes like positive, negative and neutral in data mining. The sentiment analysis is used to find out negation within the text using Natural Language Processing rules. Our aim is to detect negation affect on consumer(More)
Various binary similarity measures have been employed in clustering approaches to make homogeneous groups of similar entities in the data. These similarity measures are mostly based only on the presence or absence of features. Binary similarity measures have also been explored with different clustering approaches (e.g., agglomerative hierarchical(More)
In the digital forensic, recovery of deleted and damaged video files play an important role in searching for the evidences. In this paper, MP4-Karver tool is proposed to recover and repair the corrupted videos. Moreover, MP4-Karver extracts frames from video for automatically screen-video to detect illegal cases instead of targeting or watching complete(More)