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Google Play, also known as the Google Play Store and formerly Android Market, is a digital distribution service operated and developed by Google. It serves as the official app store for certified devices running on the Android operating system and its derivatives, as well as ChromeOS, allowing users to browse and download applications developed with the Android software development kit (SDK) and published through Google. Google Play has also served as a digital media store, offering games, music, books, movies, and television programs. Content that has been purchased on Google Play Movies & TV and Google Play Books can be accessed on a web browser and through the Android and iOS apps. Applications are available through Google Play either for free or at a cost. They can be downloaded directly on an Android device through the proprietary Google Play Store mobile app or by deploying the application to a device from the Google Play website. Applications utilizing the hard

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User Expectations of Conversational Chatbots Based on Online Reviews

Alexandru Placinta, Pearl Pu Faltings, Ekaterina Svikhnushina

Open-domain chatbots that can engage in a conversation on any topic received significant attention in the last several years, which opened opportunities for studying user interaction with them. Drawing from reviews of chatbots posted on Google Play, we explore user experience and expectations of these agents in a mixed-method study. Results of statistical analysis reveal which social qualities of chatbots are the most significant for user satisfaction. Further, we employ natural language processing and qualitative methods to identify how users wish their chatbots to evolve in the future. While currently users mostly value the entertaining component of their experience, their expectations call for more human-like behavior of chatbots. The most prominent expectations include chatbots' abilities to treat and express emotions and be more attentive to the user. Based on these findings, we conclude with design implications, discussing the directions for developing social skills of open-domain chatbots.

ASSOC COMPUTING MACHINERY2021

Whodunit: Transactional Profiling for Multi-Tier Applications

Willy Zwaenepoel

This paper is concerned with performance debugging of multi- tier applications, such as commonly found in servers and dynamic-content web sites. Existing tools and techniques for profiling such applications are not general enough to track and profile transactions in a generic multi-tier appli- cation. We propose transactional profiling that provides a general solution to this problem. We provide novel algo- rithms and techniques to track and profile transactions that flow through shared memory, events, stages or via inter- process communication using messages. We also measure interference among concurrent transactions. We describe the design and implementation of Whodunit, our prototype transactional profiler. We demonstrate the correctness of our proposed algorithm for tracking transac- tion flow through shared memory using Apache andMySQL. Using Whodunit we are able to track and profile transac- tions that flow through shared memory, events, stages or via message passing, and measure the interference among concurrent transactions. We illustrate the use of Whodunit in obtaining the transactional profile of web servers, a web proxy cache and a bookstore application.

2007

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Google LLC (ˈɡuːɡəl) is an American multinational technology company focusing on artificial intelligence, online advertising, search engine technology, cloud computing, computer software, quantum co

User Expectations of Conversational Chatbots Based on Online Reviews

Sponsored search, market equilibria, and the Hungarian Method

Whodunit: Transactional Profiling for Multi-Tier Applications

User Expectations of Conversational Chatbots Based on Online Reviews

Sponsored search, market equilibria, and the Hungarian Method

Whodunit: Transactional Profiling for Multi-Tier Applications