Release Management

You are probably familiar with maturity models for software development such as CMMI. In this thought-provoking session, Default.aspx Pope and Ellen Hill describe a corresponding five-stage maturity model for software quality engineering-not just testing-which addresses the challenges organizations face when attempting to improve the their software’s quality. Default.aspx and Ellen introduce their model for software quality maturity and discuss how you can use this model to baseline your organizations' current level and map out a path for improvement. You'll learn how to assess where you are now on the ladder: (1) do nothing, (2) write documents and create forms, (3) measure the process, (4) improve based on metrics, or (5) automate tools and process.

As software development teams seek greater efficiency and effectiveness, they often find that they are held back by old IT architecture for development and test. They wrestle with low-powered servers, difficult-to-scale static environments, and a slow IT provisioning and change processes. Today, software leaders at Calypso, Centric Group, Serena Software, and others have radically changed the way they build, test, and deploy software-almost exclusively using cloud computing to power their development processes. Some teams report benefits of 75% faster development cycles with 70% lower operating costs. Brian White describes the techniques and practices employed and success factors you can follow to achieve similar results. Brian provides specifics on which application workloads are ideal for the cloud model and how the use of cloud computing supports Agile development practices.

Have you heard any of these from your development staff or said them yourself? "Our software and systems are too fragile." "Technical debt is killing us." "We need more time to refactor." Having quality code is great, but we should understand why it matters and specifically what is important to your situation. Joel Tosi begins by defining and discussing some common code metrics-code complexity, coverage, object distance, afferent/efferent coupling, and cohesion. From there, Joel takes you through an application with poor code metrics and shows how this application would be difficult to enhance and extend in the future. Joel wraps up with a discussion about what metrics are applicable for specific situations such as legacy applications, prototypes, and startups. You'll come away from this class with a better understanding of code metrics and how to apply them pragmatically.

The question of how much design to do up-front on a project is an engaging one. Too much design often results in overkill, complexity, and wasted work. Too little design results in insufficient system structures that require rework, additional complexity, and wasted effort. How can we know what the right balance is? Alan Shalloway shows how to use the advice from Design Patterns coupled with the attitude of not building what you don't need from Agile. The trick is in discovering what you don't know, how it may affect you, and then how to isolate these risks in your code in a simple manner. Alan describes the essence of emergent design–that is, starting with a simple design and letting it evolve as the requirements evolve. He also demonstrates how to refactor to better designs and how this is different from refactoring bad code.