Software Engineering Institute | Carnegie Mellon University

SEI Insights

SEI Blog

The Latest Research in Software Engineering and Cybersecurity

By Kevin Fall
Deputy Director, Research, and CTO

This is the second installment in a series on the SEI's technical strategic plan.

Department of Defense (DoD) systems are becoming increasingly software reliant, at a time when concerns about cybersecurity are at an all-time high. Consequently, the DoD, and the government more broadly, is expending significantly more time, effort, and money in creating, securing, and maintaining software-reliant systems and networks. Our first post in this series provided an overview of the SEI's five-year technical strategic plan, which aims to equip the government with the best combination of thinking, technology, and methods to address its software and cybersecurity challenges. This blog post, the second in the series, looks at ongoing and new research we are undertaking to address key cybersecurity, software engineering and related acquisition issues faced by the government and DoD.

Object-oriented programs present considerable challenges to reverse engineers. For example, C++ classes are high-level structures that lead to complex arrangements of assembly instructions when compiled. These complexities are exacerbated for malware analysts because malware rarely has source code available; thus, analysts must grapple with sophisticated data structures exclusively at the machine code level. As more and more object-oriented malware is written in C++, analysts are increasingly faced with the challenges of reverse engineering C++ data structures. This blog post is the first in a series that discusses tools developed by the Software Engineering Institute's CERT Division to support reverse engineering and malware analysis tasks on object-oriented C++ programs.

This is the second installment of two blog posts highlighting recommended practices for achieving Agile at Scale that was originally published on the Cyber Security & Information Systems Information Analysis Center (CSIAC) website. The first post in the series by Ipek Ozkaya and Robert Nord explored challenges to achieving Agile at Scale and presented the first five recommended practices:

1. Team coordination
2. Architectural runway
3. Align development and decomposition.
4. Quality-attribute scenarios
5. Test-driven development

This post presents the remaining five technical best practices, as well as three conditions that will help organizations achieve the most value from these recommended practices. This post was originally published in its entirety on the SPRUCE website.

We are writing to let our SEI Blog readers know about some changes to SEI blogs that make our content areas more accessible and easier to navigate. On August 6, 2015, the SEI will unveil a new website, SEI Insights, that will give you access to all SEI blogs--the CERT/CC, Insider Threat, DevOps and SATURN, and SEI--in one mobile-friendly location. At SEI Insights, readers can quickly review the most recent posts from all SEI blogs and navigate to each blog.

The biweekly DevOps series that was part of the SEI Blog will now have its own blog page accessible from the Insights homepage. The SEI and DevOps blogs, as well as the other blogs on the site, will maintain individual RSS feeds.

To access SEI Insights, please visit

Your links to the former blog sites will temporarily redirect to SEI Insights, but we encourage you to update existing links and bookmarks.

Thank you for your continued support of the SEI blogs.

This post is the first in a two-part series highlighting 10 recommended practices for achieving agile at scale.

Software and acquisition professionals often have questions about recommended practices related to modern software development methods, techniques, and tools, such as how to apply agile methods in government acquisition frameworks, systematic verification and validation of safety-critical systems, and operational risk management. In the Department of Defense (DoD), these techniques are just a few of the options available to face the myriad challenges in producing large, secure software-reliant systems on schedule and within budget.

In their haste to deliver software capabilities, developers sometimes engage in less-than-optimal coding practices. If not addressed, these shortcuts can ultimately yield unexpected rework costs that offset the benefits of rapid delivery. Technical debt conceptualizes the tradeoff between the short-term benefits of rapid delivery and long-term value. Taking shortcuts to expedite the delivery of features in the short term incurs technical debt, analogous to financial debt, that must be paid off later to optimize long-term success. Managing technical debt is an increasingly critical aspect of producing cost-effective, timely, and high-quality software products, especially in projects that apply agile methods.

In their current state, wearable computing devices, such as glasses, watches, or sensors embedded into your clothing, are obtrusive. Jason Hong, associate professor of computer science at Carnegie Mellon University, wrote in a 2014 co-authored article in Pervasive Computing that while wearables gather input from sensors placed optimally on our bodies, they can also be "harder to accommodate due to our social context and requirements to keep them small and lightweight."

The SEI Blog continues to attract an ever-increasing number of readers interested in learning more about our work in agile metrics, high-performance computing, malware analysis, testing, and other topics. As we reach the mid-year point, this blog posting highlights our 10 most popular posts, and links to additional related resources you might find of interest (Many of our posts cover related research areas, so we grouped them together for ease of reference.)

Before we take a deeper dive into the posts, let's take a look at the top 10 posts (ordered by number of visits, with #1 being the highest number of visits):