Cloud computing is a promising technology that is expected to transform the healthcare industry. Cloud computing has many benefits like flexibility, cost and energy savings, resource sharing, and fast deployment. In this paper, we study the use of cloud computing in the healthcare industry and different cloud security and privacy challenges. The centralization of data on the cloud raises many security and privacy concerns for individuals and healthcare providers. This centralization of data (1) provides attackers with one-stop honey-pot to steal data and intercept data in-motion and (2) moves data ownership to the cloud service providers; therefore, the individuals and healthcare providers lose control over sensitive data. As a result, security, privacy, efficiency, and scalability concerns are hindering the wide adoption of the cloud technology. In this work, we found that the state-of-the art solutions address only a subset of those concerns. Thus, there is an immediate need for a holistic solution that balances all the contradicting requirements.
To the four pillars of my life: my parents, my wife, and my sisters. Without you, my life would fall apart. I might not know where the life's road will take me, but walking with You, through this journey has given me strength. Mom, you have given me so much, thanks for your faith in me, and for teaching me that I should never surrender. Daddy, you always told me to reach for the stars. I think I got my first one. Thanks for inspiring my love for computer. Salwa, you are everything to me, without your love and understanding I would not be able to make it. Alaa, Hanaa, and Aseel, you are the stars shining my sky and lightening my way to success and without you I would have never made it this far in life. May Allah keep you all safe and happy.
Assigning a bug to the right developer is a key in reducing the cost, time, and efforts for developers in a bug fixing process. This assignment process is often referred to as bug triaging. In this paper, we propose Bugzie, a novel approach for automatic bug triaging based on fuzzy set-based modeling of bug-fixing expertise of developers. Bugzie considers a system to have multiple technical aspects, each is associated with technical terms. Then, it uses a fuzzy set to represent the developers who are capable/competent of fixing the bugs relevant to each term. The membership function of a developer in a fuzzy set is calculated via the terms extracted from the bug reports that (s)he has fixed, and the function is updated as new fixed reports are available. For a new bug report, its terms are extracted and corresponding fuzzy sets are union'ed. Potential fixers will be recommended based on their membership scores in the union'ed fuzzy set. Our preliminary results show that Bugzie achieves higher accuracy and efficiency than other state-of-the-art approaches.
Software tagging has been shown to be an efficient, lightweight social computing mechanism to improve different social and technical aspects of software development. Despite the importance of tags, there exists limited support for automatic tagging for software artifacts, especially during the evolutionary process of software development. We conducted an empirical study on IBM Jazz's repository and found that there are several missing tags in artifacts and more precise tags are desirable. This paper introduces a novel, accurate, automatic tagging recommendation tool that is able to take into account users' feedbacks on tags, and is very efficient in coping with software evolution. The core technique is an automatic tagging algorithm that is based on fuzzy set theory. Our empirical evaluation on the real-world IBM Jazz project shows the usefulness and accuracy of our approach and tool.
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