Abstract Stability is the capability of a software artifact to stay intact while adapting to new changes and requirements. Software architecture demonstrates the structure of a software system which can be presented as software components and their inter connections. Measuring the stability of software architecture is an important endeavor that can help developers or project managers to make them aware about the situation of... Stability is the capability of a software artifact to stay intact while adapting to new changes and requirements. Software architecture demonstrates the structure of a software system which can be presented as software components and their inter connections. Measuring the stability of software architecture is an important endeavor that can help developers or project managers to make them aware about the situation of the software being developed. Many software metrics have been introduced to measure the stability of the software architecture. Some of these metrics measure software architecture at package-level while other ones measure it at class-level. The principal goal of this paper is to come up with a new easy mechanism to measure the stability evolution in open source Java systems. Five different systems with ten versions are analyzed with respect to the new suggested mechanism of measuring stability evolution. Read More Read Less

Abstract Minimizing the spread of influence, a dual problem to influence maximization, is to find top-k links from a social network such that by blocking them the spread of influence is minimized. Kimura etal. [4] first proposed the problem and presented a greedy algorithm in order to solve this problem. But the greedy algorithm is too expensive and cannot scale to large scale social... Minimizing the spread of influence, a dual problem to influence maximization, is to find top-k links from a social network such that by blocking them the spread of influence is minimized. Kimura etal. [4] first proposed the problem and presented a greedy algorithm in order to solve this problem. But the greedy algorithm is too expensive and cannot scale to large scale social networks. In this paper, we design an efficient algorithm called SA-min based on Simulated Annealing (SA) for the problem. This is the first SA-based algorithm for the problem. Experimental results on real networks show that our algorithm can outperform the greedy algorithm by more than an order of magnitude while achieving comparable spread minimization. Read More Read Less

Abstract The objective of the study was to assess the students’ continuance intention toward multimedia online learning such as their perceived usefulness, ease-of-use, and flow experience. The samples were 523 students who used off-campus/ online learning resources and examined the content online learning resources and its multimedia aspects. An Extended of Technology Acceptance Model (TAM) was used to predict the students continuance intention. The... The objective of the study was to assess the students’ continuance intention toward multimedia online learning such as their perceived usefulness, ease-of-use, and flow experience. The samples were 523 students who used off-campus/ online learning resources and examined the content online learning resources and its multimedia aspects. An Extended of Technology Acceptance Model (TAM) was used to predict the students continuance intention. The results indicate that students’ intention is influenced positively by their perceived usefulness, ease-of-use, and their flow experience. It is recommended that multimedia online learning designers should be more specific in determining target users to receive and foster more positive continuance intention. Read More Read Less