Software-engineering challenges of building and deploying reusable problem solvers

Abstract

Problem solving methods (PSMs) are software components that represent and encode reusable algorithms. They can be combined with representations of domain knowledge to produce intelligent application systems. A goal of research on PSMs is to provide principled methods and tools for composing and reusing algorithms in knowledge-based systems. The ultimate objective is to produce libraries of methods that can be easily adapted for use in these systems. Despite the intuitive appeal of PSMs as conceptual building blocks, in practice, these goals are largely unmet. There are no widely available tools for building applications using PSMs and no public libraries of PSMs available for reuse. This paper analyzes some of the reasons for the lack of widespread adoptions of PSM techniques and illustrate our analysis by describing our experiences developing a complex, high-throughput software system based on PSM principles. We conclude that many fundamental principles in PSM research are useful for building knowledge-based systems. In particular, the task–method decomposition process, which provides a means for structuring knowledge-based tasks, is a powerful abstraction for building systems of analytic methods. However, despite the power of PSMs in the conceptual modeling of knowledge-based systems, software engineering challenges have been seriously underestimated. The complexity of integrating control knowledge modeled by developers using PSMs with the domain knowledge that they model using ontologies creates a barrier to widespread use of PSM-based systems. Nevertheless, the surge of recent interest in ontologies has led to the production of comprehensive domain ontologies and of robust ontology-authoring tools. These developments present new opportunities to leverage the PSM approach.

Reuse of constraint knowledge bases and problem solvers explored in engineering design

“…The paper in the Special Issue on PSMs that is closest to our activity is that by O'Connor et al (2009). This paper discusses the (software engineering) challenges of implementing systems to process complex and diverse data sets that relate to the detection of outbreaks of infectious diseases.…”

Biomedical Informatics – A Confluence of Disciplines?

“…Because an algorithm may entail a set of subtasks, our procedural models often reflect task decomposition [21], where an overall task may be construed using a model of problem solving that specifies subtasks that in turn may be addressed by yet other models of problem solving, recursively. Developers often create quite complex task-decomposition models to describe intricate problem-solving behaviour in biomedicine [22].…”