With the support of cloud computing techniques, social coding platforms have changed the style of software development. Github is now the most popular social coding platform and project hosting service. Software developers of various levels keep entering Github, and use Github to save their public and private software projects. The large amounts of software developers and software repositories on Github are posing new challenges to the world of software engineering. This paper tries to tackle one of the important problems: analyzing the importance and influence of Github repositories. We proposed a HITS based influence analysis on graphs that represent the star relationship between Github users and repositories. A weighted version of HITS is applied to the overall star graph, and generates a different set of top influential repositories other than the results from standard version of HITS algorithm. We also conduct the influential analysis on per-month star graph, and study the monthly influence ranking of top repositories.

In this paper, we propose a new ID-based threshold signature scheme from the bilinear pairings, which is provably secure in the random oracle model under the bilinear Diffie-Hellman assumption. Our scheme adopts the approach that the private key associated with an identity rather than the master key of PKG is shared. Comparing to the-state-of-art work by Baek and Zheng, our scheme has the following advantages. (1) The round-complexity of the threshold signing protocol is optimal. Namely, during the signing procedure, each party broadcasts only one message. (2) The communication channel is optimal. Namely, during the threshold signing procedure, the broadcast channel among signers is enough. No private channel between any two signing parties is needed.(3) Our scheme is much more efficient than the Baek and Zheng scheme in term of computation, since we try our best to avoid using bilinear pairings. Indeed, the private key of an identity is indirectly distributed by sharing a number xID ∈ Z * q , which is much more efficient than directly sharing the element in the bilinear group. And the major computationally expensive operation called distributed key generation protocol based on the bilinear map is avoided. (4) At last, the proactive security can be easily added to our scheme.

Web site navigability refers to the degree to which a visitor can follow a Web site's hyperlink structure to successfully find information with efficiency and ease. In this study, we take a data-driven approach to measure Web site navigability using Web data readily available in organizations. Guided by information foraging and information-processing theories, we identify fundamental navigability dimensions that should be emphasized in metric development. Accordingly, we propose three data-driven metrics-namely, power, efficiency, and directness-that consider Web structure, usage, and content data to measure a Web site's navigability. We also develop a Web mining-based method that processes Web data to enable the calculation of the proposed metrics. We further implement a prototype system based on the Web miningbased method and use it to assess the navigability of two sizable, real-world Web sites with the metrics. To examine the analysis results by the metrics, we perform an evaluation study that involves these two sites and 248 voluntary participants. The evaluation results show that user performance and assessments are consistent with the analysis results revealed by our metrics. Our study demonstrates the viability and practical value of data-driven metrics for measuring Web site navigability, which can be used for evaluative, diagnostic, or predictive purposes.

In this paper, a system reliability model subject to Dependent Competing Failure Processes (DCFP) with phase-type (PH) distribution considering changing degradation rate is proposed. When the sum of continuous degradation and sudden degradation exceeds the soft failure threshold, soft failure occurs. The interarrival time between two successive shocks and total number of shocks before hard failure occurring follow the continuous PH distribution and discrete PH distribution, respectively. The hard failure reliability is calculated using the PH distribution survival function. Due to the shock on soft failure process, the degradation rate of soft failure will increase. When the number of shocks reaches a specific value, degradation rate changes. The hard failure is calculated by the extreme shock model, cumulative shock model, and run shock model, respectively. The closed-form reliability function is derived combining with the hard and soft failure reliability model. Finally, a Micro-Electro-Mechanical System (MEMS) demonstrates the effectiveness of the proposed model.

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