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Ishtiaque Hussain
Researcher at Pennsylvania State University
Publications - 12
Citations - 111
Ishtiaque Hussain is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Computer science & Benchmark (computing). The author has an hindex of 4, co-authored 9 publications receiving 98 citations. Previous affiliations of Ishtiaque Hussain include Penn State Abington & University of Texas at Arlington.
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Proceedings ArticleDOI
CarFast: achieving higher statement coverage faster
Sangmin Park,B M Mainul Hossain,Ishtiaque Hussain,Christoph Csallner,Mark Grechanik,Kunal Taneja,Chen Fu,Qing Xie +7 more
TL;DR: The results indicate with strong statistical significance that when execution time is measured in terms of the number of runs of the application on different input test data, CarFast outperforms the evaluated competitive approaches on most subject applications.
Journal ArticleDOI
RUGRAT: Evaluating program analysis and testing tools and compilers with large generated random benchmark applications
Ishtiaque Hussain,Christoph Csallner,Mark Grechanik,Qing Xie,Sangmin Park,Kunal Taneja,B M Mainul Hossain +6 more
TL;DR: This work proposes a novel approach for generating random benchmarks for evaluating program analysis and testing tools and compilers that uses stochastic parse trees, where language grammar production rules are assigned probabilities that specify the frequencies with which instantiations of these rules will appear in the generated programs.
Proceedings ArticleDOI
Dynamic symbolic data structure repair
TL;DR: It is motivated how dynamic symbolic techniques enable generic repair to support a wider range of correctness conditions and DSDSR, a novel repair algorithm based on dynamic symbolic execution is presented.
Proceedings ArticleDOI
Evaluating program analysis and testing tools with the RUGRAT random benchmark application generator
Ishtiaque Hussain,Christoph Csallner,Mark Grechanik,Chen Fu,Qing Xie,Sangmin Park,Kunal Taneja,B M Mainul Hossain +7 more
TL;DR: This work proposes a novel approach for generating random benchmarks for evaluating program analysis and testing tools that uses stochastic parse trees, where language grammar production rules are assigned probabilities that specify the frequencies with which instantiations of these rules will appear in the generated benchmarks.
Proceedings ArticleDOI
An empirical study of teaching qualities of popular computer science and software engineering instructors using RateMyProfessor.com data
TL;DR: The paper captured and analyzed more than 9,000 students' comments for over 300 CS instructors for the top 20 universities in the U.S. and Canada and mined and analyzed the RMP data for some research questions, e.g., What are the common characteristics of the popular CS instructors?