Mining and Understanding Software Enclaves (MUSE) | Apply Online

Opportunity Summary:

The Mining and Understanding Software Enclaves (MUSE) opportunity (Funding Opportunity Number DARPA BAA 14-22) is a DARPA research solicitation focused on pushing the boundaries of how complex software systems can be analyzed, verified, and understood at scale. The core aim is to fund work that can specify and uncover meaningful properties of real-world software, including behaviors, invariants, security-relevant characteristics, and other system-level traits that are often difficult to observe directly. The solicitation emphasizes that proposed efforts should combine or advance program analysis, formal verification, and big data analytics in ways that produce genuinely new capabilities for reasoning about software that is large, complicated, and messy in the way production software tends to be.

A central theme in MUSE is moving beyond incremental, routine improvements and instead developing approaches that could produce step-change advances in science, methods, or systems for software understanding. DARPA is explicitly not looking for proposals that mainly deliver evolutionary progress on existing tools or standard practices. In practical terms, that means the work should not read like a modest extension of a current static analyzer, a straightforward scaling of an existing verification method, or a conventional machine learning pipeline applied to code. The intended outcomes are more along the lines of new analysis paradigms, new forms of specification discovery, new data-driven methods that can extract deep structure from code and execution artifacts, or novel system designs that make previously intractable software reasoning problems feasible.

The announcement is issued as a Broad Agency Announcement (BAA), with selections conducted under Federal Acquisition Regulation (FAR) 35.016, which is commonly used for applied research and advanced technology development. The funding instruments listed for this opportunity include cooperative agreements and other procurement contracts, which signals that DARPA may support performers under different contractual arrangements depending on the nature of the work and the government’s planned level of involvement. The activity category is Science and Technology and other Research and Development, and the CFDA listing given is 12.910 (Research and Technology Development). There is no stated cost sharing or matching requirement, lowering barriers for academic groups, nonprofits, and commercial entities that want to propose high-risk, high-reward research without needing to bring committed matching funds.

Eligibility is described as unrestricted, meaning the solicitation is open to a broad range of applicant types (for example, universities, companies, nonprofits, federally funded research and development centers, and other organizations), subject to any clarifications that would have appeared in the full text of the BAA under the eligibility section. The timeline information provided indicates the opportunity was posted on February 25, 2014, with an original and current closing date of April 15, 2014, and an archive date of May 15, 2014, which reflects that this is a historical opportunity rather than an active, open call today.

The notice also references Amendment 0001. The stated purpose of that amendment was administrative rather than substantive: it removed template language that had been mistakenly left in the Executive Summary section. In other words, the amendment was meant to correct the solicitation document for clarity and accuracy, not to reframe the technical problem set or change the fundamental scope of the research being sought.

For applicants needing help accessing the full announcement or related materials, the point of contact listed is Dr. Suresh Jagannathan, Program Manager, with coordination through DARPA’s I2O BAA process. Overall, MUSE is best understood as a DARPA-driven push to develop groundbreaking techniques that can mine, characterize, and reason about the behavior and properties of complex software systems using a combination of advanced program analysis, verification ideas, and large-scale data analytics, with a clear preference for research that changes what is possible rather than marginally improving what already exists.

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