With a large number of web services offering the same functionality, the Quality of Service (QoS) rendered by a web service becomes a key differentiator. WS-BPEL has emerged as the de facto industry standard for composing web services. Thus, determining the QoS of a composite web service expressed in BPEL can be extremely beneficial. While there has been much work on QoS computation of structured workflows, there exists no tool to ascertain QoS for BPEL processes, which are semantically richer than conventional workflows. We propose a model for estimating three key QoS parameters -Response Time, Cost and Reliability -of an executable BPEL process from the QoS information of its partner services and certain control flow parameters. We have built a tool to compute QoS of a WS-BPEL process that accounts for most workflow patterns that may be expressed by standard WS-BPEL. Another feature of our QoS approach and the tool is that it allows a designer to explore the impact on QoS of using different software fault tolerance techniques like Recovery blocks, N-version programming etc., thereby provisioning QoS computation of mission critical applications that may employ these techniques to achieve high reliability and/or performance.

We propose a friend recommendation system (an application of link prediction) using edge embedding on social networks. Most real world social networks are multi-graphs, where different kinds of relationships (e.g., chat, friendship) are possible between a pair of users. Existing network embedding techniques do not leverage signals from different edge types and thus perform inadequately on link prediction in such networks. We propose a method to mine network representation that effectively exploits edge heterogeneity in multi-graphs. We evaluate our model on a real-world, active social network where this system is deployed for friend recommendation for millions of users. Our method outperforms various state-of-theart baselines on Hike's social network in terms of accuracy metrics as well as user

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