Project Grant 2338287
- This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to enable developers to perform fine-grained software testing, thereby increasing software quality. The research project will: (1) develop a language and framework for expressing and using fine-grained tests; (2) automatically generate fine-grained tests from code or existing tests; (3) adapt fine-grained tests to software evolution and...
- This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to enable developers to perform fine-grained software testing, thereby increasing software quality. The key objectives are to: (1) develop a language and framework for expressing and using fine-grained tests; (2) automatically generate fine-grained tests from code or existing tests; (3) adapt fine-grained tests to software evolution and...
- This three-year, $600,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop scalable concolic testing techniques for parallel applications with shared dynamic data structures. Specifically, the awardee, the Regents of the University of California at Riverside, will pursue two key objectives. First, the researchers will generalize concolic testing to automatically test parallel programs running on heterogeneous, massively...
- This Project Grant award of $300,000.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at Carnegie Mellon University to develop techniques and tools for reliable, efficient, and reproducible testing of concurrent software applications. The project aims to create a controlled concurrency testing solution for multi-threaded programs running on managed runtime systems like the Java Virtual Machine. Key objectives...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports a research initiative titled "A General Framework for Automated Test Transfer." The $143,333 grant, awarded to the University of Georgia Research Foundation on July 1, 2025, aims to develop automated techniques for reusing software testing cases across similar applications. Key goals include enabling the transfer of user interface (UI) test...
- This $300,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program supports the development of a new testing methodology to enhance the detection of internal defects in state-of-the-art integrated circuits. The research project aims to generate compact and efficient tests that can comprehensively cover a wide range of resistive defects within individual circuit cells, as well as capture the timing impact of a...
- This Project Grant from the National Science Foundation Division of Computer and Network Systems, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $517,545 in funding to the University of Utah from January 1, 2022 to September 30, 2024. The award supports research to advance software vulnerability detection techniques. Specifically, the university researchers will develop new approaches to fuzz testing, a method for identifying software...
- The University of Washington was awarded a $500,000 Project Grant from the National Science Foundation Division of Computer and Network Systems under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support the University's efforts to evolve the Defects4J benchmark and infrastructure to enable sustained innovation and reproducibility in software engineering research. Specifically, the University will work to enhance Defects4J, an...
- The National Science Foundation (NSF) has awarded a $175,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Cincinnati. The funding will support the development of novel techniques and tools to substantially improve automated bug report reproduction for Android mobile applications. Key objectives include: (1) extracting observation/expectation and environment information from bug reports; (2) generating oracle assertion codes...
- The University of Florida was awarded a three-year, $300,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070) to conduct research towards variability-aware software analysis and testing. The university will extend software analysis techniques to automatically extract feature constraints from program code and check them against requirements specifications. Researchers will leverage variability-aware symbolic...
CAREER: ENHANCED RELIABILITY AND EFFICIENCY OF SOFTWARE REGRESSION TESTING IN THE PRESENCE OF FLAKY TESTS -SOFTWARE IS USUALLY DEVELOPED IN A CONTINUOUS DEVELOPMENT AND INTEGRATION PROCESS THAT INCORPORATES INCREMENTAL CHANGES LEADING TO SUCCESSIVE RELEASES OF THE SOFTWARE, WHERE EACH RELEASE UNDERGOES RIGOROUS SOFTWARE TESTING TO CHECK WHETHER RECENT CODE CHANGES HAD BROKEN EXISTING FUNCTIONALITIES. THIS PROCESS, KNOWN AS REGRESSION TESTING, IS WIDELY USED IN SOFTWARE DEVELOPMENT PRACTICE. A MAJOR PROBLEM IN THE GENERATION OF TEST CASES IS THE PRESENCE OF FLAKY TESTS: TESTS THAT NON-DETERMINISTICALLY PASS OR FAIL ON THE SAME VERSION OF THE CODE. FAILURES FROM FLAKY TESTS CAN MISLEAD DEVELOPERS ABOUT THEIR RECENT CHANGES, WASTE DEVELOPERS? TIME, AND REDUCE DEVELOPERS? TRUST IN SOFTWARE TESTING. MANY SOFTWARE DEVELOPMENT ORGANIZATIONS HAVE REPORTED THAT FLAKY TESTS ARE ONE OF THEIR BIGGEST PROBLEMS, BECAUSE THEY CONFOUND ASSURANCE GOALS. THIS PROJECT AIMS TO IMPROVE THE RELIABILITY AND EFFICIENCY OF REGRESSION TESTING IN THE PRESENCE OF FLAKY TESTS. IT WILL PRODUCE TOOLS THAT AIM TO BE EFFICIENT AND EFFECTIVE AT RESOLVING THE INHERENT NONDETERMINISM. THE WORK FOCUSES ON (1) REDUCING THE COST OF FLAKY-TEST DETECTION AND DEBUGGING TECHNIQUES BY PREDICTING IMPORTANT TEST PROPERTIES, (2) DEVELOPING NEW TECHNIQUES TO PREDICT FLAKINESS-RELATED PROPERTIES, (3) SPEEDING UP AND REDUCING THE RESOURCES NEEDED BY REGRESSION TESTING, (4) DEVELOPING NEW TECHNIQUES TO SYSTEMATICALLY DETECT FLAKY TESTS, AND (5) REDUCING THE FLAKINESS IN ANDROID USER INTERFACE TESTING. THE PROJECT WILL ALSO PRODUCE CURRICULUM FOR EDUCATION AND TRAINING ON THE TOPIC OF PROGRAMMING IN THE FACE OF NONDETERMINISM, AND WILL WORK WITH INDUSTRY TO TRANSFER TECHNOLOGY. THE RESEARCH ON FLAKINESS WILL MOVE FROM THE TYPICAL, BLACK-BOX APPROACHES TO A NEW LEVEL FOR DETECTING, DEBUGGING, AND FIXING THROUGH NOVEL, WHITE-BOX AND LEARNING-BASED APPROACHES. THE APPROACH WILL USE STATIC AND DYNAMIC ANALYSES TO COMPUTE STATE POLLUTION, WHICH MAY AFFECT TEST FLAKINESS BASED ON THE TEST EXECUTION ORDER. THE WORK INVOLVES COMBINATORIAL DESIGN THEORY TO IMPROVE THE EFFICIENCY OF ORDER-DEPENDENT TEST DETECTION. SPECIAL ATTENTION WILL BE PAID TO FLAKY TESTS IN GRAPHICAL USER INTERFACES USING RECORD-AND-REPLAY AND TEST INPUT GENERATION. TEST COVERAGE COMPUTATIONS, WHICH CAN BE USED TO PREDICT WHETHER A CODE CHANGE WILL AFFECT THE TEST'S OUTPUT, WILL USE A MACHINE LEARNING APPROACH. THE WORK WILL RESULT IN TOOL IMPLEMENTATIONS AND LARGE-SCALE EVALUATIONS IN OPEN SOURCE AND PROPRIETARY ENVIRONMENTS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $247.4k | 8/22/25 | ||
| Not listed | $117.5k | 8/5/25 | ||
| Not listed | $0 | 7/30/24 | ||
| Not listed | $123.5k | 3/11/24 |