Four Principles of Engineering Scalable, Big Data Software Systems

Architecture , Big Data 1 Comment »

By Ian Gorton
Senior Member of the Technical Staff
Software Solutions Division

Ian Gorton 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.

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The Latest Research from the SEI

Malware , Resilience Management Model (RMM) , Secure Coding , Systems Engineering No Comments »

By Douglas C. Schmidt
Principal Researcher

Douglas C. Schmidt 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 codingCERT Resilience Management Modelmalicious-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. 

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Android, Heartbleed, Testing, and DevOps: An SEI Blog Mid-Year Review

Android , Architecture , Big Data , DevOps , Secure Coding , Testing 1 Comment »

By Douglas C. Schmidt 
Principal Researcher

Douglas C. Schmidt 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 datasecure coding for Androidmalware analysisHeartbleed, 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. 

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Is Your Organization Ready for Agile?

Agile , Readiness & Fit Analysis 1 Comment »

By Suzanne Miller 
Principal Researcher
Software Solutions Division

This blog post is the fifth in a series on Agile adoption. 

Suzanne Miller 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.

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Architecture Analysis Using AADL: A Beginner’s Perspective

Architecture , Architecture Analysis & Design Language (AADL) No Comments »

By Julien Delange
Member of the Technical Staff
Software Solutions Division

Julien Delang

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.

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