(IS(50)), Schmidt hammer rebound number (SRn), p-wave velocity test (Vp) and dry density The results of laboratory tests including point load index test The experimental program consists of direct and indirectĮstimation of UCS of rocks.
Program was conducted on 66 granite and limestone sample sets taken from different For this reason, a comprehensive experimental The objective of this paper is toĭevelop a PSO-based ANN predictive model of UCS. Performance of ANNs is recently underlined in literature. Utilization of particle swarm optimization (PSO) algorithm as a mechanism to improve the However, BP-ANN suffersįrom some disadvantages such as slow rate of learning and getting trapped in local minima.
Using back-propagation (BP) artificial neural network (ANN). Many attempts have been made to predict unconfined compressive strength (UCS) of rocks © Copyright 2015 The Institute of Electronics, Information and Communication Engineers. The empirical results show the following two findings: (1) morecommented methods (the methods having more comments than the amount estimated by size and complexity of the methods) are about 1.6-2.8 times more likely to be faulty than the others, and (2) LCM can be a useful factor in fault-prone method prediction models along with the method size and the method complexity.
This paper conducts an empirical analysis to examine whether Lines of Comments (LCM) written inside a method's body is a noteworthy metric for analyzing fault-proneness in Java methods.
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However, comments may also be used to mask the lack of readability in the program, therefore well-written comments are referred to as "deodorant to mask code smells" in the field of code refactoring. In general, comments along with executable statements enhance the understandability of programs. This paper focuses on the power of comments to predict fault-prone programs. In this paper, we begin with a discussion of our infrastructure (including a novel use of Scientific Workflow software) and then discuss our approach to mining the email archives and finally we present some preliminary results from our data analysis. These include questions relating to participation in the email the social status of different types of OSS participants the relationship of email activity and commit activity (in the CVS repositories) and the relationship of social status with commit activity. Once this is done, we can construct social networks of email correspondents, and begin to address some interesting questions. However, there are various challenges that must be addressed before this data can be effectively mined. As a result, the email archives of OSS projects provide a useful trace of the communication and co-ordination activities of the participants. OSS projects, on the other hand, use the internet as the communication medium,and typically conduct discussions in an open, public manner.
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Communication & Co-ordination activities are central to large software projects, but are difficult to observe and study in traditional (closed-source, commercial) settings because of the prevalence of informal, direct communication modes.
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