The role of software within systems has fundamentally changed over the past 50 years. Software's role has changed both on mission-critical DoD systems, such as fighter aircraft and surveillance equipment, and on commercial products, such as telephones and cars. Software has become not only the brain of most systems, but the backbone of their functionality. Acquisition processes must acknowledge this new reality and adapt. This blog posting, the second in a series about the relationship of software engineering (SwE) and systems engineering (SysE), shows how software technologies have come to dominate what formerly were hardware-based systems. This posting describes a case study: the story of software on satellites, whose lessons can be applied to many other kinds of software-reliant systems.
Many warfighters and first responders operate at what we call "the tactical edge," where users are constrained by limited communication connectivity, storage availability, processing power, and battery life. In these environments, onboard sensors are used to capture data on behalf of mobile applications to perform tasks such as face recognition, speech recognition, natural language translation, and situational awareness. These applications then rely on network interfaces to send the data to nearby servers or the cloud if local processing resources are inadequate. While software developers have traditionally used native mobile technologies to develop these applications, the approach has some drawbacks, such as limited portability. In contrast, HTML5 has been touted for its portability across mobile device platforms, as well an ability to access functionality without having to download and install applications. This blog post describes research aimed at evaluating the feasibility of using HTML5 to develop applications that can meet tactical edge requirements.
In earlier posts on big data, I have written about how long-held design approaches for software systems simply don't work as we build larger, scalable big data systems. Examples of design factors that must be addressed for success at scale include the need to handle the ever-present failures that occur at scale, assure the necessary levels of availability and responsiveness, and devise optimizations that drive down costs. Of course, the required application functionality and engineering constraints, such as schedule and budgets, directly impact the manner in which these factors manifest themselves in any specific big data system. In this post, the latest in my ongoing series on big data, I step back from specifics and describe four general principles that hold for any scalable, big data system. These principles can help architects continually validate major design decisions across development iterations, and hence provide a guide through the complex collection of design trade-offs all big data systems require.
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 secure coding, CERT Resilience Management Model, malicious-code reverse engineering, systems engineering, and incident management. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.
In the first half of this year, 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 the first six months of 2014 (through June 20), the SEI blog has logged 60,240 visits, which is nearly comparable with the entire 2013 yearly total of 66,757 visits. As we reach the mid-year point, this blog posting takes a look back at our most popular areas of work (at least according to you, our readers) and highlights our most popular blog posts for the first half of 2014, as well as links to additional related resources that readers might find of interest.
Federal agencies depend on IT to support their missions and spent at least $76 billion on IT in fiscal year 2011, according to a report from the Government Accountability Office (GAO). The catalyst for the study was congressional concern over prior IT expenditures that produced disappointing results, including multimillion dollar cost overruns and schedule delays measured in years, with questionable mission-related achievements. The Office of Management and Budget (OMB) in 2010 issued guidance that advocates federal agencies employ "shorter delivery time frames, an approach consistent with Agile." This ongoing series on the Readiness & Fit Analysis (RFA) approach focuses on helping federal agencies and other organizations understand the risks involved when contemplating or embarking on the adoption of new practices, such as Agile methods. This blog posting, the fifth in this series, explores the Practices category, which helps organizations understand which Agile practices are already in use to formulate a more effective adoption strategy.
Introducing new software languages, tools, and methods in industrial and production environments incurs a number of challenges. Among other necessary changes, practices must be updated, and engineers must learn new methods and tools. These updates incur additional costs, so transitioning to a new technology must be carefully evaluated and discussed. Also, the impact and associated costs for introducing a new technology vary significantly by type of project, team size, engineers' backgrounds, and other factors, so that it is hard to estimate the real acquisition costs. A previous post in our ongoing series on the Architecture Analysis and Design Language (AADL) described the use of AADL in research projects (such as System Architectural Virtual Integration (SAVI)) in which experienced researchers explored the language capabilities to capture and analyze safety-critical systems from different perspectives. These successful projects have demonstrated the accuracy of AADL as a modeling notation. This blog post presents research conducted independently of the SEI that aims to evaluate the safety concerns of several unmanned aerial vehicle (UAV) systems using AADL and the SEI safety analysis tools implemented in OSATE.
The Wireless Emergency Alerts (WEA) service went online in April 2012, giving emergency management agencies such as the National Weather Service or a city's hazardous materials team a way to send messages to mobile phone users located in a geographic area in the event of an emergency. Since the launch of the WEA service, the newest addition to the Federal Emergency Management Agency (FEMA) Integrated Public Alert and Warning System (IPAWS),"trust" has emerged as a key issue for all involved. Alert originators at emergency management agencies must trust WEA to deliver alerts to the public in an accurate and timely manner. The public must also trust the WEA service before it will act on the alerts. Managing trust in WEA is a responsibility shared among many stakeholders who are engaged with WEA. This blog post, the first in a series, highlights recent research aimed at enhancing both the trust of alert originators in the WEA service and the public's trust in the alerts it receives.