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Over the last two decades, Agile software development methodology has garnered significant interest in both software industry and research with several studies investigating the level of awareness, perception and use of Agile in software engineering practice. However, most of these studies have focused on Agile practice in developed countries, with only a handful having been conducted in developing countries, especially in the Middle East. This is problematic given the strategic and economic importance of software industry in countries such as Saudi Arabia. This paper aims to start addressing this research gap with an empirical investigation of the awareness and perceptions of Agile among software practitioners in Saudi Arabia and the extent to which they are adopting Agile methods. To this end, we conduct four semi-structured interviews with expert software practitioners and a survey with 31 respondents, all from the mobile development software industry. Our findings indicate that there it seems to be a low level of awareness and usage of Agile in the country. However, we also find that those who use Agile, are appreciative of its benefits which include project management flexibility, rapid response to change, and a positive effect on team morale and communication.

This paper makes the case for the study of human values in Software Engineering (SE) as a highly important emerging area of research with significant societal implications. We offer two key principles in order to advance this research agenda: firstly, the significance of values as distinguished from, though connected to, ethics; and secondly, the need for clear theoretical frameworks for values study. We provide the emerging findings from an initial study (N=12 participants) using a Values Q-Sort tool that was designed in accordance with these two principles. We conclude with discussion around lessons learnt, ongoing challenges, and future directions.

This paper reports on the development of ongoing research into the systematic study of human values in software engineering (SE). Firstly, we outline the rationale for this work, highlighting the significance of human values in SE and the need for both a more structured approach to their study and tools to support their articulation in the SE domain. We then explain our theoretical framework, which draws on social psychology research on values. Secondly, we introduce tools designed in line with this framework and the context of their use so far. Our tools adopt a variety of research methods, including structured mixed-method techniques, such as the 'Values Q-Sort' (V-QS), and more open design-based methods, such as the 'Values Probes'. Given the multi-faceted nature of the topic, we argue that a combination of qualitative, quantitative and design thinking techniques is a necessary step for the study of human values in SE; and that these methods should be both a) robust and replicable, and b) creative and provocative. Finally, we highlight the potential applications of our tools in SE industry and education.

Much has been documented in the literature on sentiment analysis and document summarisation. Much of this applies to long structured text in the form of documents and blog posts. With a shift in social media towards short commentary (see Facebook status updates and twitter tweets), the difference in comment structure may affect the accuracy of sentiment analysis techniques. From our VoiceYourView trial, we collected over 2000 individual short comments on the topic of library refurbishment, many of which are transcribed spoken comments. We have shown success in determining the theme of comments by looking for the first noun and using a semantic tag set to categorise this noun and hence the comment for short comments. Sentiment is a measure of how positive or negative a comment is, and the actionability metric is a measure of how actionable the comment is, i.e. how useful it is. This paper looks towards applying methods from the literature to our dataset with the aim of evaluating methods of automatic sentiment and actionability analysis for our VoiceyourView application data and has relevance to data from other applications, e.g. those from the social media. With many social media commentary applications moving to add speech platforms, VoiceYourView data may be representative of the type of free-form spoken text input to be expected in such platforms.