Software developers often work on multiple projects and tasks throughout a work day, which may affect their productivity and quality of work. Knowing how working on several projects at a time affects productivity can improve cost and schedule estimations. It also can provide additional insights for better work scheduling and the development process. We want to achieve a better productivity without losing the benefits of work interruptions and multitasking for developers involved in the process. To understand how the development process can be improved, first, we identify work interruptions that mostly have a negative effect on productivity, second, we need to quantitatively evaluate impact of multitasking (task switching, work context switching) and work interruptions on productivity. In this research we study cross-project multitasking among the developers working on multiple projects in an educational setting. We propose a way to evaluate the number of cross-project interruptions among software developers using self-reported work logs. This paper describes the research that found: a) software developers involved in two or more projects on average spend 17% of their development effort on cross-project interruptions, b) the amount of effort spent on interruptions is overestimated by the G. Weinberg’s heuristic, c) the correlation between the number of projects and effort spent by developers on cross-project interruptions is relatively weak, and d) there is strong correlation between the number of projects and the number of interruptions developers reported.

Systems engineering processes using pull scheduling methods (kanban) are being evaluated with hybrid modeling and simulation. We are assessing integrated systems and software engineering at the enterprise level, where rapid response software development projects incrementally evolve capabilities of existing systems and/or systems of systems. A kanban-based scheduling system was defined and implemented with connected discrete, continuous and agent-based models. We are simulating the process performance vs. traditional methods of sharing systems engineering services across projects, and whether the overall value of the systems of systems over time is increased.

Systems engineering is often ineffective in development environments where large, complex, brownfield systems of systems are evolved through parallel development of new capabilities in response to external, time-sensitive requirements. This paper defines a conceptual framework to improve that effectiveness and better integrate the systems engineering and software engineering processes. The framework is based on a services approach to systems engineering and the use of kanban techniques to schedule scarce enterprise systems engineering resources across multiple related systems and software development projects. The framework also addresses the differing value of work items to multiple stakeholders in the scheduling and coordination processes. Models and simulations are being used to capture, refine and validate the framework prior to in vivo experimentation.

The wide variety of software-intensive systems needed to support the new horizons of evolving technology, system and software complexity, high dependability, global interoperability, emergent requirements, and adaptability to rapid change make traditional and current one-size-fits-all process models infeasible. This tutorial presents the process framework, principles, practices, and case studies for a new model developed and being used to address these challenges. It has a series of risk-driven decision points that enable projects to converge on whatever combination of agile, plan-driven, formal, legacy-oriented, reuse-oriented, or adaptive processes that best fit a project's situation. The tutorial discusses the decision table for common special cases; exit ramps for terminating non-viable projects; support of concurrent engineering of requirements, solutions and plans; and evidence-based commitment milestones for synchronizing the concurrent engineering. The tutorial will include case studies and exercises for participants' practice and discussion.

Today's need for more complex, capable systems in a short timeframe is leading many organizations towards the integration of existing systems into network-centric, knowledge-based system-of-systems (SoS). Software and system cost model tools to date have focused on the software and system development activities of a single system. When viewing the new SoS architectures, one finds that the effort associated with the design and integration of these SoSs is not handled well, if at all, in current cost models. This paper includes (I) a comparison of various SoS definitions and concepts with respect to cost models, (2) a classification of these definitions in terms of product, process, and personnel focus, and (3) the definition of a set of discriminators for defining model boundaries and potential drivers for an SoS cost estimation model. Eleven SoS definitions are synthesized to provide reasonable coverage for different properties of SoS and illustrated in two examples.

In 1986, Science Applications International Corporation (SAIC) was tasked to design, develop, deploy, and maintain a health care system.Over the last ten years, extensive measurement data has been collected and analyzed.By setting goals in terms of a few key indicators, establishing baselines for those indicators, and measuring success in terms of the baseline, management easily monitors development trends and the impacts of process improvement activities.This paper describes the measurement program implemented within SAIC's health care software development organization, illustrates how the measurements are used to influence process improvement, and concludes with general observations and lessons learned.