Biological research has become dependent on computational tools to help guide hypothesis generation and experimentation. However, many tools may be difficult to use, and their results may be hard to reproduce, explain, or validate. This project proposes to build a bridge between state-of-the-art software testing techniques, biologists, and bioinformaticists within the 
context of a widely used, DOE-supported open software platform, the Department of Energy Systems Biology Knowledgebase (KBase). We are designing meta-computational approaches that are accessible to different types of users. Our goals are to (1) enable and empower biologists to explore tools that expose reasoning and parameter settings, increasing confidence and trust in their results; (2) build embedded software testing techniques that help identify faults in predictive biological programs to improve their reliability and prediction accuracy; (3) provide tools to help automatically repair faulty code for the tool developer; and (4) design families of scientific workflows as reusable building blocks.
The Office of Biological and Environmental Research (BER) in the U.S. Department of Energy (DOE) Office of Science award DE-SC0025510
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