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The Latest Research in Software Engineering and Cybersecurity

Engineering the architecture for a large and complex system is a hard, lengthy, and complex undertaking. System architects must perform many tasks and use many techniques if they are to create a sufficient set of architectural models and related documents that are complete, consistent, correct, unambiguous, verifiable, usable, and useful to the architecture's many stakeholders. This blog posting, the second in a two-part series, takes a deeper dive into the Method Framework for Engineering System Architectures (MFESA), which is a situational process engineeringframework for developing system-specific methods to engineer system architectures.

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 workforce competency and readiness, cyber forensics, exploratory research, acquisition, and software-reliant systems. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.

This post is the third and final installment in a three-part series that explains how Nedbank, one of the largest banks in South Africa, is rolling out the SEI's Team Software Process (TSP) throughout its IT organization. In the first post of this series, I examined how Nedbank addressed issues of quality and productivity among its software engineering teams using TSP at the individual and team level. In the second post, I discussed how the SEI worked with Nedbank to address challenges with expanding and scaling the use of TSP at an organizational level. In this post, I first explore challenges common to many organizations seeking to improve performance and become more agile and conclude by demonstrating how SEI researchers addressed these challenges in the TSP rollout at Nedbank.

This post is the second installment in a three-part series that explains how Nedbank, one of the largest banks in South Africa, is rolling out the SEI's Team Software Process (TSP)--a disciplined and agile software process improvement method--throughout its IT organization. In the first postof this series, I examined how Nedbank addressed issues of quality and productivity among its software engineering teams using TSP at the individual and team level. In this post, I will discuss how the SEI worked with Nedbank to address challenges with expanding and scaling the use of TSP at an organizational level.

Major acquisition programs increasingly rely on software to provide substantial portions of system capabilities. All too often, however, software is not considered when the early, most constraining program decisions are made. SEI researchers have identified misalignments between software architecture and system acquisition strategies that lead to program restarts, cancellations, and failures to meet important missions or business goals. This blog posting--the second installment in a two-part series--builds on the discussions in part one by introducing several patterns of misalignment--known as anti-patterns--that we've identified in our research and discussing how these anti-patternsare helping us create a new method for aligning software architecture and system acquisition strategies to reduce project failure.

Engineering the architecture for a large and complex system is a hard, lengthy, and complex undertaking. System architects must perform many tasks and use many techniques if they are to create a sufficient set of architectural models and related documents that are complete, consistent, correct, unambiguous, verifiable, and both usable by and useful to the architecture's many stakeholders. This blog posting, the first in a two-part series, presents the Method Framework for Engineering System Architectures (MFESA), which is a situational process engineeringframework for developing system-specific methods to engineer system architectures. This posting provides a brief historical description of situational method engineering, explains why no single system architectural engineering method is adequate, and introduces MFESA by providing a top-level overview of its components, describing its applicability, and explaining how it simultaneously provides the benefits of standardization and flexibility.

Major acquisition programs increasingly rely on software to provide substantial portions of system capabilities. Not surprisingly, therefore, software issues are driving system cost and schedule overruns. All too often, however, software is not even a consideration when the early, most constraining program decisions are made. Through analysis of troubled programs, SEI researchers have identified misalignments between software architecture and system acquisition strategies that lead to program restarts, cancellations, and failures to meet important missions or business goals. To address these misalignments, the SEI is conducting new research on enabling organizations to reduce program failures by harmonizing their acquisition strategy with their software architecture.

As part of our research related to early acquisition lifecycle cost estimation for the Department of Defense (DoD), my colleagues in the SEI's Software Engineering Measurement & Analysis initiative and I began envisioning a potential solution that would rely heavily on expert judgment of future possible program execution scenarios. Previous to our work on cost estimation, many parametric cost models required domain expert input, but, in our opinion, they did not address alternative scenarios of execution that might occur from Milestone A onward.