In this article, we present an approach for systematically improving complex processes, especially those involving human agents, hardware devices, and software systems. We illustrate the utility of this approach by applying it to part of an election process and show how it can improve the security and correctness of that subprocess. We use the Little-JIL process definition language to create a precise and detailed definition of the process. Given this process definition, we use two forms of automated analysis to explore whether specified key properties, such as security and safety policies, can be undermined. First, we use model checking to identify process execution sequences that fail to conform to event-sequence properties. After these are addressed, we apply fault tree analysis to identify when the misperformance of steps might allow undesirable outcomes, such as security breaches. The results of these analyses can provide assurance about the process; suggest areas for improvement; and, when applied to a modified process definition, evaluate proposed changes.

Software products are rarely developed without providing different sets of features to better meet varying user needs, whether through tiered products as part of a product line or different subscription levels for software as a service (SaaS). Software product line approaches for generating and maintaining a family of different variants of software products address such needs for variation quite well. Real-world human-intensive systems (HISs) display similar needs for families of variants. A key contribution of this paper is to show how many of these needs can be rigorously and systematically addressed by adapting established techniques from system and software product line engineering (SPLE).

A process model, namely a formal definition of the coordination of agents performing activities using resources and artifacts, can aid understanding of the real-world process it models. Moreover, analysis of the model can suggest improvements to the real-world process. Complex real-world processes, however, exhibit considerable amounts of variation that can be difficult or impossible to represent with a single process model. Such processes can often be modeled better, within the restrictions of a given modeling notation, by a family of models. This paper presents an approach to the formal characterization of some of these process families. A variety of needs for process variation are identified, and suggestions are made about how to meet some of these needs using different approaches. Some mappings of different needs for variability to approaches for meeting them are presented as case studies.