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The Latest Research in Software Engineering and Cybersecurity

The adoption of new practices, such as agile or any new practice for that matter, is a task that is best undertaken with both eyes open. There are often disconnects between the adopting organization's current practice and culture and the new practices being adopted. This posting is the second installment in a series on Readiness & Fit Analysis (RFA), which is a model and method for understanding risks when contemplating or embarking on the adoption of new practices, in this case agile methods.

When a system fails, engineers too often focus on the physical components, but pay scant attention to the software. In software-reliant systems ignoring or deemphasizing the importance of software failures can be a recipe for disaster. This blog post is the first in a series on recent developments with the Architecture Analysis Design Language (AADL) standard. Future posts will explore recent tools and projects associated with AADL, which provides formal modeling concepts for the description and analysis of application systems architecture in terms of distinct components and their interactions. As this series will demonstrate, the use of AADL helps alleviate mismatched assumptions between the hardware, software, and their interactions that can lead to system failures.

In 2011, Col. Timothy Hill, director of the Futures Directorate within the Army Intelligence and Security Command, urged industry to take a more open-standards approach to cloud computing. "Interoperability between clouds, as well as the portability of files from one cloud to another, has been a sticking point in general adoption of cloud computing," Hill said during a panel at the AFCEA International 2011 Joint Warfighting Conference. Hill's view has been echoed by many in the cloud computing community, who believe that the absence of interoperability has become a barrier to adoption. This posting reports on recent research exploring the role of standards in cloud computing and offers recommendations for future standardization efforts.

Some of the principal challenges faced by developers, managers, and researchers in software engineering and cybersecurity involve measurement and evaluation. In two previous blog posts, I summarized some features of the overall SEI Technology Strategy. This post focuses on how the SEI measures and evaluates its research program to help ensure these activities address the most significant and pervasive problems for the Department of Defense (DoD). Our goal is to conduct projects that are technically challenging and whose solution will make a significant difference in the development and operation of software-reliant systems. In this post we'll describe the process used to measure and evaluate the progress of initiated projects at the SEI to help maximum their potential for success.

Knowing what assets are on a network, particularly which assets are visible to outsiders, is an important step in achieving network situational awareness. This awareness is particularly important for large, enterprise-class networks, such as those of telephone, mobile, and internet providers. These providers find it hard to track hosts, servers, data sets, and other vulnerable assets in the network.

As part of an ongoing effort to keep you informed about our latest work, I'd like to let you know about some recently published SEI technical reports and notes. These reports highlight the latest work of SEI technologists in and systems engineering, resilience, and insider threat. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.

The Department of Defense (DoD) has become deeply reliant on software. As a federally funded research and development center (FFRDC), the SEI is chartered to work with the DoD to meet the challenges of designing, producing, assuring, and evolving software-reliant systems in an affordable and dependable manner. This blog post is the second in a multi-part series that describes key elements of our forthcoming Strategic Research Plan that address these challenges through research, acquisition support, and collaboration with the DoD, other federal agencies, industry, and academia.

An autonomous system is a computational system that performs a desired task, often without human guidance. We use varying degrees of autonomy in robotic systems for manufacturing, exploration of planets and space debris, water treatment, ambient sensing, and even cleaning floors. This blog post discusses practical autonomous systems that we are actively developing at the SEI. Specifically, this post focuses on a new research effort at the SEI called Self-governing Mobile Adhocs with Sensors and Handhelds (SMASH) that is forging collaborations with researchers, professors, and students with the goal of enabling more effective search-and-rescue crews.