The Department of Defense (DoD) and other government agencies increasingly rely on software and networked software systems. As one of over 40 federally funded research and development centers sponsored by the United States government, Carnegie Mellon University's Software Engineering Institute (SEI) is working to help the government acquire, design, produce, and evolve software-reliant systems in an affordable and secure manner. The quality, safety, reliability, and security of software and the cyberspace it creates are major concerns for both embedded systems and enterprise systems employed for information processing tasks in health care, homeland security, intelligence, logistics, etc. Cybersecurity risks, a primary focus area of the SEI's CERT Division, regularly appear in news media and have resulted in policy action at the highest levels of the US government (See Report to the President: Immediate Opportunities for Strengthening the Nation's Cybersecurity ).
This blog post was co-authored by Eric Werner.
Graph algorithms are in wide use in Department of Defense (DoD) software applications, including intelligence analysis, autonomous systems, cyber intelligence and security, and logistics optimizations. In late 2013, several luminaries from the graph analytics community released a position paper calling for an open effort, now referred to as GraphBLAS, to define a standard for graph algorithms in terms of linear algebraic operations. BLAS stands for Basic Linear Algebra Subprograms and is a common library specification used in scientific computation. The authors of the position paper propose extending the National Institute of Standards and Technology's Sparse Basic Linear Algebra Subprograms (spBLAS) library to perform graph computations. The position paper served as the latest catalyst for the ongoing research by the SEI's Emerging Technology Center in the field of graph algorithms and heterogeneous high-performance computing (HHPC). This blog post, the second in our series, describes our efforts to create a software library of graph algorithms for heterogeneous architectures that will be released via open source.
As software continues to grow in size and complexity, software programmers continue to make mistakes during development. These mistakes can result in defects in software products and can cause severe damage when the software goes into production. Through the Personal Software Process (PSP), the Carnegie Mellon University Software Engineering Institute has long advocated incorporating discipline and quantitative measurement into the software engineer's initial development work to detect and eliminate defects before the product is delivered to users. This blog post presents an approach for incorporating formal methods with PSP, in particular, Verified Design by Contract, to reduce the number of defects earlier in the software development lifecycle while preserving or improving productivity.
As part of an ongoing effort to keep you informed about our latest work, I would like to let you know about some recently published SEI technical reports and notes. These reports highlight the latest work of SEI technologists in software assurance, social networking tools, insider threat, and the Security Engineering Risk Analysis Framework (SERA). This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.
This blog post is the sixth in a series on Agile adoption in regulated settings, such as the Department of Defense, Internal Revenue Service, and Food and Drug Administration.
"Across the government, we've decreased the time it takes across our high-impact investments to deliver functionality by 20 days over the past year alone. That is a big indicator that agencies across the board are adopting agile or agile-like practices," Lisa Schlosser, acting federal chief information officer, said in a November 2014 interview with Federal News Radio. Schlosser based her remarks on data collected by the Office of Management and Budget (OMB) over the last year. In 2010, the OMB issued guidance calling on federal agencies to employ "shorter delivery time frames, an approach consistent with Agile" when developing or acquiring IT. As evidenced by the OMB data, Agile practices can help federal agencies and other organizations design and acquire software more effectively, but they need to understand the risks involved when contemplating the use of Agile. This ongoing series on Readiness & Fit Analysis (RFA) focuses on helping federal agencies and other organizations in regulated settings understand the risks involved when contemplating or embarking on a new approach to developing or acquiring software. Specifically, this blog post, the sixth in a series, explores issues related to system attributes organizations should consider when adopting Agile.
Attacks and disruptions to complex supply chains for information and communications technology (ICT) and services are increasingly gaining attention. Recent incidents, such as the Target breach, the HAVEX series of attacks on the energy infrastructure, and the recently disclosed series of intrusions affecting DoD TRANSCOM contractors, highlight supply chain risk management as a cross-cutting cybersecurity problem. This risk management problem goes by different names, for example, Supply Chain Risk Management (SCRM) or Risk Management for Third Party Relationships. The common challenge, however, is having confidence in the security practices and processes of entities on which an organization relies, when the relationship with those entities may be, at best, an arms-length agreement. This blog post highlights supply chain risks faced by the Department of Defense (DoD), federal civilian agencies, and industry; argues that these problems are more alike than different across these sectors; and introduces practices to help organizations better manage these risks.
In 2014, the SEI blog has experienced unprecedented growth, with visitors in record numbers learning more about our work in big data, secure coding for Android, malware analysis, Heartbleed, and V Models for Testing. In 2014 (through December 21), the SEI blog logged 129,000 visits, nearly double the entire 2013 yearly total of 66,757 visits.
Over the years, software architects and developers have designed many methods and metrics to evaluate software complexity and its impact on quality attributes, such as maintainability, quality, and performance. Existing studies and experiences have shown that highly complex systems are harder to understand, maintain, and upgrade. Managing software complexity is therefore useful, especially for software that must be maintained for many years.