Resources

White Papers

Software productivity must be measured as more than just output divided by input. This guide describes a method for adjusting productivity with quality results to gain greater visibility into the impact that software quality has on the productivity of future releases. After identifying the various measures and their associated methods, we present 11 best practices that can be integrated into a productivity measurement and analysis process and provide recommendations for implementing an effective measurement-driven improvement program.

Despite the fact that enterprise IT departments have invested heavily in dynamic testing tools to verify and validate application performance and scalability before releasing business applications into production, performance issues and response time latency continue to negatively impact the business. By supplementing dynamic performance testing with automated structural quality analysis, development teams have the ability to detect, diagnose, and analyze performance and scalability issues more effectively. This white paper presents a six-step Performance Modeling Process using automated structural quality analysis to identify these potential performance issues earlier in the development lifecycle

Successful planning replaces gut feel with objective, fact based analysis.

CAST HIGHLIGHT transforms IT budgeting and planning by automating the technical discovery process and creating insight needed to make better decisions. Using code analysis, CAST HIGHLIGHT derives application measures (size and complexity) as well as maintainability and the potential for production failures. When combined with your company’s subject matter expertise, this data forms the insight needed to develop and implement an effective IT plan and budget.

Learn how advanced Software Analysis and Measurement (SAM) can help improve application security by analyzing source code to identify vulnerabilities and architectural patterns in the application, and enable development teams to prevent these vulnerabilities right at the development stage with sophisticated Threat Modeling that takes into account cross-tier and cross-technology interactions.

When a mission-critical application fails, the loss of business revenue is large and swift. Poor application quality causes highly-visible major outages, as well as ongoing lapses in business performance that are less visible, but steadily add up to substantial revenue loss. Even minor quality improvements can result in significant gain. Yet, executives struggle to build a business case to justify proactive investments in application quality. This paper presents a quantitative framework for measuring the immediate and positive revenue impact of improving application quality.

Learn how Software Analysis & Measurement (SAM) can objectively evaluate the reliability, security, efficiency, maintainability, and size of software deliverables. Forward-looking organizations and SIs are leveraging this measurement to greatly improve the maturity in vendor-client relationships, by incorporating SAM throughout the outsourcing lifecycle—from RFP preparation to contract development, team transition and benchmarking.

Critical applications developed by organizations to service their clients frequently face app killers like major outages, malfunctions, and security breaches that disrupt business and damage reputations. As organizations increasingly face the devastating impact of Architecturally Complex Violations, read this e-book to learn how CAST AIP can help to eliminate these issues before they kill your app.

To avoid landing on the rocks, you need to aggressively eliminate application risk by identifying issues that can lead to high-profile production failures and cyber attacks. Whether you need a macro-view of your portfolio risks or a micro-view of a specific application, CAST’s suite of assessment solutions can help create the visibility needed to navigate through these troubled waters.

If you already have some knowledge of Technical Debt, this ebook provides a 7-step Technical Debt Management Cycle that provides a clear process that can over time reduce the risk of failure of critical applications---and ultimately pay down the interest of the overall liability inherent in your application portfolio.

Paying Down the TD Interest Bill-CurtisIn this just-released white paper, Dr. Bill Curtis – SVP and Chief Scientist at – examines the Technical Debt metaphor to explain how it can be used to help executives think about software quality in business terms while governing software changeability and maintainability of their application portfolios.

 For those with responsibility to govern the costs and risks of application portfolios, the financial metaphor “Technical Debt” helps us think about software quality in business terms.  This paper includes a formula to benchmark your Technical Debt against industry data, or adjust the parameters to best fit your organization’s own maintenance and structural quality objectives, experiences, and costs.  It also details the “Technical Debt Management Cycle” for analyzing and measuring Technical Debt so you can relate executive business priorities to strategic quality priorities for reducing business risk and IT cost.

How to monetize application technical debtThis is a Gartner-CAST paper which shows the data-driven approach to balancing delivery agility with business risk. The paper features exclusive analysis from Andy Ktye, Gartner VP and Fellow who eloquently illustrates the systemic risk in the application portfolio caused by the accumulation of Technical Debt over the last decade.

Technical Debt has been growing exponentially as maintenance is starved and development teams are forced to cut corners to meet increasingly unrealistic delivery schedules. CAST clearly defines Technical Debt so it can be measured and then juxtaposed with the business value of applications to inform critical tradeoffs between delivery agility and business risk.

Learn how the Lean practices pioneered in the Toyota Production System apply to the Application Development and Maintenance (ADM) of business software.  Applying Lean to ADM decreases total cost of ownership and improves business responsiveness and operational dependability.

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