In aiming for correctness and security of product, as well as for development speed, software development teams often face tension in their objectives. During a recent customer engagement that involved the development of a continuous-integration (CI) pipeline, developers wanted to develop features and deploy to production, deferring non-critical bugs as technical debt, whereas cyber engineers wanted compliant software by having the pipeline fail on any security requirement that was not met. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Alejandro Gomez, a researcher in the SEI’s CERT Division who worked on the customer project, talked with principal researcher Suzanne Miller about how the team explored—and eventually resolved—the two competing forces of developer velocity and cybersecurity enforcement by implementing DevSecOps practices.

In aiming for correctness and security of product, as well as for development speed, software development teams often face tension in their objectives. During a recent customer engagement that involved the development of a continuous-integration (CI) pipeline, developers wanted to develop features and deploy to production, deferring non-critical bugs as technical debt, whereas cyber engineers wanted compliant software by having the pipeline fail on any security requirement that was not met. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Alejandro Gomez, a researcher in the SEI’s CERT Division who worked on the customer project, talked with principal researcher Suzanne Miller about how the team explored—and eventually resolved—the two competing forces of developer velocity and cybersecurity enforcement by implementing DevSecOps practices.

The shift to a cloud environment provides significant benefits. Cloud resources can be scaled quickly, updated frequently, and widely accessed without geographic limitations. Realizing these benefits, however, requires organizations to manage associated organizational and technical risks. In this podcast from the Carnegie Mellon University Software Engineering Institute, Chris Alberts, principal cybersecurity analyst in the SEI’s CERT Division, discusses with principal researcher Suzanne Miller a prototype set of cloud adoption risk factors and describes a method that managers can employ to assess their cloud initiatives against these risk factors.

Competitive pressures in many domains, as well as development paradigms such as Agile and DevSecOps, have led to the increasingly common practice of continuous delivery or continuous deployment where frequent updates to software systems are rapidly and reliably fielded. In today’s systems, releases can occur at any time—possibly hundreds of releases per day—and each can be instigated by a different team within an organization. Being able to release frequently means that bug fixes and security patches do not have to wait until the next scheduled release, but rather can be made and released as soon as a bug is discovered and fixed. It also means that new features can be put into production at any time and don’t have to wait to be bundled into a release. In this podcast, Rick Kazman, an SEI visiting scientist and coauthor of Software Architecture in Practice, talks with principal researcher Suzanne Miller about using patterns for software deployability. These patterns fall into two broad categories: complete replacement of services and canary testing.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Thomas Podnar and Dustin Updyke, both senior cybersecurity engineers with the SEI’s CERT Division, discuss their work to apply machine learning to increase the realism of non-player characters (NPCs) in cyber training exercises.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Douglass Post and Richard Kendall, authors of "Creating and Using Virtual Prototyping Software: Principles and Practices" discuss with principal researcher Suzanne Miller experiences and insights that they gleaned from applying virtual prototyping in CREATE (Computational Research and Engineering Acquisition Tools and Environments), a multiyear DoD program to develop and deploy software for systems like ships, air vehicles, ground vehicles, and radio-frequency antennas. CREATE enabled engineers and scientists to design these complex systems and to accurately predict their performance.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Douglass Post and Richard Kendall, authors of Creating and Using Virtual Prototyping Software: Principles, and Practices, discuss with SEI principal researcher Suzanne Miller experiences and insights that they gleaned from applying virtual prototyping in CREATE (Computational Research and Engineering Acquisition Tools and Environments), a multiyear Department of Defense program to develop and deploy software for systems like ships, air vehicles, ground vehicles, and radio-frequency antennas. CREATE enabled engineers and scientists to design these complex systems and to accurately predict their performance.

In this podcast from the Carnegie Mellon University Software Engineering Institute, visiting scientist Rick Kazman and principal researcher Suzanne Miller discuss software architecture patterns and the effect that certain architectural patterns have on quality attributes, such as availability and robustness. Kazman also provides examples of mechanisms—such as architectural tactics and patterns—and the effects they have on availability and robustness, especially in cloud-based systems.

DevSecOps encompasses all the best software engineering principles known today with an emphasis on faster delivery through increased collaboration of all stakeholders resulting in more secure, useable, and higher-quality software systems. In this podcast from the Carnegie Mellon University Software Engineering Institute, researchers Tim Chick and Joe Yankel present a DevSecOps Platform-Independent Model (PIM), which uses model based systems engineering (MBSE) to formalize the practices of DevSecOps pipelines and organize relevant guidance. This first-of-its-kind model gives software development enterprises the structure and articulation needed for creating, maintaining, securing, and improving DevSecOps pipelines.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Jason Larkin and Daniel Justice, researchers in the SEI’s AI Division, discuss a paper outlining their efforts to simulate the performance of Quantum Approximate Optimization Algorithm (QAOA) for the Max-Cut problem and compare it with some of the best classical alternatives, for exact, approximate, and heuristic solutions.