Welcome to the home page of the 12th International Workshop on Dynamic Analysis, WODA 2014. This year, WODA 2014 is a community building event. We have merged WODA and PERTEA workshop to encourage more participation, and exchange of ideas.
WODA+PERTEA will be held on Tuesday, July 22nd, 2014, in San Jose, Bay Area, California co-located with the International Symposium on Software Testing and Analysis ( ISSTA 2014 ).
The goal of WODA is to bridge software engineering, PL, and OS communities working in dynamic analysis and related research activities to meet and discuss current research, issues, and trends in the field.
Shaz Qadeer is Principal Researcher at Microsoft. He received his Ph.D. from the University of California at Berkeley. He has worked at Microsoft Research for most of his professional life, except for a short period at Compaq Systems Research Center and an even shorter period at HP Labs. Shaz develops tools and techniques for making programming better and easier; in particular, he is trying to simplify the construction of asynchronous, concurrent, and parallel programs.
Corina Pasareanu is a researcher in software engineering at NASA Ames, in the Robust Software Engineering group. She is employed by Carnegie Mellon University, at the Silicon Valley campus. She is best known for her work on symbolic execution and the application of automated learning techniques to assume-guarantee reasoning. Most recently, she has worked on scalable probabilistic analysis of software, through compositional, abstraction and symbolic techniques More information about her work can be found at: http://ti.arc.nasa.gov/profile/pcorina/.
Caitlin Sadowski's mission is to make program analysis usable for developers. She is a software engineer at Google in the Developer Infrastructure group, where she leads a team with this focus. She created Google's internal static analysis platform and integrated it into the developer workflow. She also works on compiler-level static analysis tools. Before Google, she worked on dynamic analysis tools for detecting concurrency errors, such as data races.
Manu Sridharan is a researcher at Samsung Research America in the area of programming languages and software engineering. He received his PhD from the University of California, Berkeley in 2007 and worked at IBM Research from 2008 to 2013. His dissertation focused on refinement-based program analysis tools. Since then, he has done research on a variety of topics in static analysis, dynamic analysis, and software engineering. His most recent work focuses on static and dynamic analysis of web applications. For more information on his work, see http://manu.sridharan.net.
Qing Xie is a Researcher at the Accenture Technology Labs. She received her BS in Computer Science in 1996 from the South China University of Technology, her MS and PhD in Computer Science in 2002 and 2006 respectively from the University of Maryland, College Park. She is a recipient of best paper awards from the International Conference of Software Testing, Verification and validation (ICST'09) and International Symposium on Software Reliability and Engineering (ISSRE'10). Her research interests include program testing, software engineering, software maintenance, cloud computing and empirical studies. She is a member of the ACM Sigsoft and the IEEE Computer Society and has served on program committees of several international conferences and as the reviewers of reputable journals.
Xusheng Xiao is a researcher at NEC Laboratories America. He received his Ph. D. degree in the Department of Computer Science at North Carolina State University, and was a visiting student in the Department of Computer Science at the University of Illinois at Urbana-Champaign. His research in software engineering focuses on improving cooperation between tool users and software testing/analysis tools. He has been awarded the ICSE SRC Best Project Representing an Innovative Use of Microsoft Technology at ACM SRC Grand Final 2012. His work on mobile security is integrated into TouchDevelop developed by Microsoft Research and is granted a U.S. patent. His work appears in venues such as ICSE, FSE, ISSTA, ASE, and USENIX Security. He has completed several industrial research internships at Microsoft Research, IBM Research, and NEC Labs.
Adrian Nistor will start as an Assistant Professor in Fall 2014 at Chapman University. He received his Ph.D from the Computer Science Department at the University of Illinois at Urbana-Champaign in May 2014. His research interests are in software engineering, with a focus on detecting, repairing, and preventing bugs in real-world applications. His current current projects investigate performance bugs. His techniques found previously unknown bugs that developers fixed in widely used software, e.g., PARSEC, GCC, Google Chrome, Mozilla, MySQL, Ant, Lucene, Google Core Libraries, Groovy, Tomcat, JUnit, JMeter, Log4J, Struts, etc.
Yu David Liu is an assistant professor from State University of New York at Binghamton. His current research focuses on improving software energy efficiency through innovations of programming languages, compilers, and software engineering. David received his Ph.D. from the Johns Hopkins University. He was a recipient of an NSF CAREER Award and a Google Faculty Research Award.
Harry Xu has been an assistant professor of computer science with University of California, Irvine since 2011. He has broad interests in software, languages, compilers, and systems. His past work includes development of program analysis and systems techniques to find and fix inefficiencies (a.k.a, runtime bloat) in large-scale, real-world software systems. He is currently focusing on designing and implementing techniques to improve both performance and reliability of Big Data applications.
Dynamic-analysis techniques are increasingly used to complement more traditional static analysis. Approaches based on static analysis operate on a static representation of the program, consider all possible (and some infeasible) behaviors, and are thus complete, but often imprecise. Dynamic-analysis techniques, conversely, reason over a set of program executions and analyze only observed behaviors. Dynamic analysis includes both offline techniques, which operate on some captured representation of the program's behavior (e.g., a trace), and run-time techniques, which analyze the behavior on the fly, while the system is executing. Although inherently incomplete, dynamic analyses can be more precise than their static counterparts and show promise in aiding the understanding, development, and maintenance of robust and reliable large scale systems. Moreover, the data they provide enable statistical inferences to be made about program behavior. In recent years, both practitioners and researchers are realizing that the limitations of static analysis can be overcome by integrating static and dynamic analysis, and that the performance of dynamic analyses can in turn be improved by leveraging static analysis.
The overall goal of WODA is to bring together researchers and practitioners working in all areas of dynamic analysis to discuss new issues, share results and ongoing work, and foster collaborations.
Submissions to WODA should be in one of the following categories:
All submissions will be peer-reviewed by at least three members of the program committee.
Each submission by a PC member will be reviewed by at least four members of the program committee. The organizers cannot submit papers.
During the workshop, extended abstracts will receive a shorter presentation and discussion period.
WODA welcomes any submission that strongly relates to dynamic analysis; typical areas of interest that WODA covers are:
The workshop will be structured to encourage discussion and develop research collaborations.
Submit your papers here. All papers must be in English and must be prepared in ACM conference format and should use Option 2(example: "Latex users, please use the Option-2 style"). All accepted submissions will be published in the ACM Digital Library.