development

Dealing with a single system is challenging enough, but the game changes dramatically on a multi-system, distributed platform. MASSIVE platforms can consist of more than fifty distributed systems and components, integrated to process millions of transactions per day-from millions of users-while processing hundreds of terabytes of data. The ramifications of one component or system not scaling to support this load might cost hundreds of thousands or millions of dollars in lost revenue for a single system disruption. Mark Lustig explains how to integrate performance engineering across the entire development lifecycle. The world of MASSIVE platforms requires a disciplined approach to building, measuring, and ensuring system scalability, performance, and throughput.

Overly complex code? Duplicate code? Inherent coupling? Been there, done that. Beyond these specific code issues, you may believe that something is inherently wrong with your project-increased pressure, decreased velocity, those broken functions that just never get fixed. Although there are no magic bullets to fix these problems, Emad Georgy shares how he has applied a novel, technical debt model as a predictor of overall product value. Emad has used this model at strategic and business levels to bring focus to the issue of technical debt and to obtain resources and prioritization to address debt. You also can use the technical debt model to identify anti-patterns-architecture, process, and project perspectives-in your organization.

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.