Richard W. Selby

Analytics-Driven Dashboards Enable Leading Indicators for Requirements and Designs of Large-Scale Systems

Mining software repositories using analytics-driven dashboards provides a unifying mechanism for understanding, evaluating, and predicting the development, management, and economics of large-scale systems and processes. Dashboards enable measurement and interactive graphical displays of complex information and support flexible analytic capabilities for user customizability and extensibility. Dashboards commonly include system requirements and design metrics because they provide leading indicators for project size, growth, and volatility. This article focuses on dashboards that have been used on actual large-scale software projects as well as example empirical relationships revealed by the dashboards. The empirical results focus on leading indicators for requirements and designs of large-scale software systems based on insights from two sets of software projects containing 14 systems and 23 systems.

Synthesis, Analysis, and Modeling of Large-Scale Mission-Critical Embedded Software Systems

Mission-critical embedded software performs the core processing logic for pervasive systems that affect people and enterprises everyday, ranging from aerospace systems to financial markets to automotive systems. In order to function properly, these embedded software systems rely on and are highly interdependent with other hardware and software systems. This research identifies design principles for large-scale mission-critical embedded software and investigates their application in development strategies, architectures, and techniques. We have examined actual embedded software systems from two different problem domains, advanced robotic spacecraft and financial market systems, and these analyses established the foundations for these design principles. Both system types embody solutions that respond to detailed specifications defined and modeled with heavy user involvement. Both system types possess mission-critical logic represented using state machines and other structured techniques. They both use a layered architecture approach with a foundation that provides infrastructure services, a layer with a simple set of foreground and background tasks, a layer with deterministic synchronous processing steps, and a layer with event-driven monitoring, commanding, and sequencing capabilities. The architectural approach supports a domain-specific command sequencing macro language that defines table-driven executable specifications and enables developers to work at higher abstraction levels throughout the lifecycle. The architectural approach also facilitates extensibility, reuse, and portability across multi-processor execution environments. The systems rely on extensive built-in self-tests, invariants, and redundant calculations that assess states and detect faults. From a development standpoint, both systems use risk-driven incremental lifecycles, system modeling, end-to-end prototyping, and statistical analysis of development processes. Based on insights gained from embedded software design principles and their application on these as well as other systems, improvement opportunities and research directions will be identified.

Software Engineering: The Legacy of Barry W. Boehm

We are convening a symposium to honor Barry W. Boehm¿s lifetime contributions to the Software Engineering community and co-locating this event with the 29th International Conference on Software Engineering.

Software Process: Emerging Extensions

This chapter contains sections titled: Using the WinWin Spiral Model: A Case Study Making RAD Work for Your Project Requirements that Handle IKIWISI, COTS, and Rapid Change Get Ready for Agile Methods, with Care Some Future Trends and Implications for Systems and Software Engineering Processes

Software Risk Management

This chapter contains sections titled: Software Risk Management: Principles and Practices Software Risk Management

Software Process: Early Spiral Model

This chapter contains sections titled: Prototyping Versus Specifying: A Multiproject Experiment A Spiral Model of Software Development and Enhancement Anchoring the Software Process