This paper introduces a new Software Process Improvement (SPI) concept called Emergent Agility that extends Agile software development best practices by suggesting that certain meetings, events, and activities may be most efficient when they emerge dynamically from the evolving needs of teams and stakeholders. Emergent Agility is process agnostic, meaning it is not tied to a specific Agile framework or methodology. A software development process called an Emergent Minimum Viable Process (EMVP), resulting from application of Emergent Agility to an existing software process, is also presented and explained. Traditional Agile frameworks often rely on predefined schedules for standups, sprint reviews, retrospectives, and other meetings, which can become rigid and misaligned with real-time project demands. In contrast, our concept of Emergent Agility embraces the natural tensions and conflicts that emerge from any team, leveraging them to continuously iterate towards new layers of efficiency. Emergent Agility advocates the principle of on-demand collaboration, freeing teams to convene only when necessary to address pressing issues or opportunities. We test the Emergent Agility and EMVP concepts with a pilot case study, which has shown promising initial results.

A number of authors have used the Calgary corpus of texts to provide empirical results for lossless compression algorithms. This corpus was collected in 1987, although it was not published until 1990. The advances with compression algorithms have been achieving relatively small improvements in compression, measured using the Calgary corpus. There is a concern that algorithms are being fine-tuned to this corpus, and that small improvements measured in this way may not apply to other files. Furthermore, the corpus is almost ten years old, and over this period there have been changes in the kinds of files that are compressed, particularly with the development of the Internet, and the rapid growth of high-capacity secondary storage for personal computers. We explore the issues raised above, and develop a principled technique for collecting a corpus of test data for compression methods. A corpus, called the Canterbury corpus, is developed using this technique, and we report the performance of a collection of compression methods using the new corpus.