Title:
Software Testing: And the Challenges (and Opportunities) Keep Coming!

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dc.contributor.author Soffa, Mary Lou
dc.contributor.corporatename Georgia Institute of Technology. School of Computer Science en_US
dc.contributor.corporatename University of Virginia. Dept. of Computer Science en_US
dc.date.accessioned 2019-11-19T20:56:20Z
dc.date.available 2019-11-19T20:56:20Z
dc.date.issued 2019-11-08
dc.description Presented on November 8, 2019 at 2:00 p.m. in the Klaus Advanced Computing Building, Room 1116. en_US
dc.description Mary Lou Soffa is the Owen R. Cheatham Professor of Sciences in the Computer Science Department at the University of Virginia, serving as the department chair from 2004 to 2012. Her research interests include software testing, program analysis, warehouse scale computing, software systems for multi-core architectures, and optimizing compilers. en_US
dc.description Mary Jean Harrold Memorial Distinguished Lecture en_US
dc.description Runtime: 58:16 minutes
dc.description.abstract Disruptive shifts in software application types and software development environments create challenges to software testing that need to be addressed to ensure software quality and reduce the cost of software development time. Over the years, the size and complexity of software have grown as well as the need for fast-changing codebases, fault detection strategies, and test case generation and selection. To meet these challenges, techniques such as regression testing, selection/prioritization, and fault localization have been developed as well as specialized testing techniques for GUIs, object-oriented software, mobile computing, and continuous evolution of software to name a few. This talk presents an overview of these challenges and solutions and references Mary Jean Harrold’s achievements in these areas. The talk then explores current challenges and opportunities that bring problems that cannot be solved by state of art techniques, including applications that are machine learning applications or use machine learning as part of a system where components interact and evolve. Other challenges that need to be explored involve autonomous systems, cloud applications, and data churn. As software becomes more autonomous, its operations and outputs become less predictable at test writing time; hence, the traditional nature of assert (Actual, Expected) test oracles does not work and needs to be addressed. en_US
dc.format.extent 58:16 minutes
dc.identifier.uri http://hdl.handle.net/1853/62039
dc.language.iso en_US en_US
dc.relation.ispartofseries School of Computer Science Lectures
dc.subject Machine learning en_US
dc.subject Software testing en_US
dc.subject Strategy en_US
dc.title Software Testing: And the Challenges (and Opportunities) Keep Coming! en_US
dc.type Moving Image
dc.type.genre Lecture
dspace.entity.type Publication
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Computer Science
local.relation.ispartofseries School of Computer Science Colloquium
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 6b42174a-e0e1-40e3-a581-47bed0470a1e
relation.isSeriesOfPublication 63de5985-0c5c-405a-a8cc-20cbcb51c285
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