Agile software design and development methodologies have been gaining rigorous attention in the software engineering research community since their early introduction in the mid-nineties in addition to being highly adopted by the software development industry. In the last 15 years, an excessive number of research studies have been conducted on agile methods, a great number of notable methods have been proposed and various surveys have been presented by many researchers. In this study, the authors intend to conduct a literature survey study of the surveys of the different agile methodologies ranging from January 2000 to December 2015 using an intuitive research methodology called "Compare and Review" (CR). Furthermore, these survey papers were classified into four major categories according to their area of study. Additionally, the newly proposed agile methodologies that have not been addressed yet in any other literature review were reviewed and compared in terms of where the changes that they proposed lay on the SDLC.

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With the advent of online data, sentiment analysis has received growing attention in recent years. Sentiment analysis aims to determine the overall sentiment orientation of a speaker or writer towards a specific entity or towards a specific feature of a specific entity. A fundamental task of sentiment analysis is sentiment classification, which aims to automatically classify opinionated text as being positive, negative, or neutral. Although the literature on sentiment classification is quite extensive, only a few endeavors to classify opinionated text written in the Arabic language can be found. This paper provides a comprehensive survey of existing lexicon, machine learning, and hybrid sentiment classification techniques for Arabic language.

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