There is an ever-increasing demand for software engineers and teams to write and ship code. Whether you are a startup that prioritizes deadlines over quality, or an established company trying to manage legacy code, the quality of code directly impacts the security, scalability, and maintainability of your products and services. Join our panelists and gain a better understanding of how code quality is impacting you and your unique circumstance.
Adam Barr has over 30 years of experience in the software industry, with 23+ years at Microsoft as a developer and manager on projects including Windows and Office. He has written three books, including “The Problem with Software” (MIT Press, 2018) about the gap between what programmers learn in school and what they need to succeed in industry, and “Find the Bug” (Addison-Wesley, 2004) on how to read code. He currently works as a consultant at Crosslake Technologies, performing technical due diligence and organizational/architectural assessments on software companies.
Ben Held has 20+ years’ experience in development, test, and support of commercially successful electromagnetic simulation software products. His roles have included developer, code architect, R&D management, and customer engagement for large scale software systems that include scientific visualization, geometric and CAD modeling, scripting, and cloud computing. He is a firm believer in software quality and passionate about related topics such as software debt and refactoring.
Roger Scott is a recently retired software engineer in Boulder, Colorado. In his career he both developed commercial software, primarily in the Electronic Design Automation industry, and worked on various software development tools, particularly static analysis tools. He authored several of the checkers in Synopsys/Coverity’s tool. Two projects at GrammaTech, Inc. developing novel analysis techniques resulted in conference papers. He is particularly interested in applications of statistical techniques, machine learning, and “Big Code” to software analysis.