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You searched for +publisher:"University of Texas – Austin" +contributor:("Gligoric, Milos"). Showing records 1 – 13 of 13 total matches.

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University of Texas – Austin

1. -4269-9273. Regression test selection for C++ based on call graph analysis.

Degree: MSin Engineering, Electrical and Computer Engineering, 2018, University of Texas – Austin

 Regression testing  – running available tests after each project change  – is widely practiced in industry to check that a project change does not break… (more)

Subjects/Keywords: Regression test selection; Ekstazi++; C; C++; LLVM; Google Test; Call graph analysis

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APA (6th Edition):

-4269-9273. (2018). Regression test selection for C++ based on call graph analysis. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/69028

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-4269-9273. “Regression test selection for C++ based on call graph analysis.” 2018. Masters Thesis, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/69028.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-4269-9273. “Regression test selection for C++ based on call graph analysis.” 2018. Web. 03 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-4269-9273. Regression test selection for C++ based on call graph analysis. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/69028.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-4269-9273. Regression test selection for C++ based on call graph analysis. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/69028

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

2. Loyola, Jose Luis. Eksen : regression test selection for VHDL.

Degree: MSin Engineering, Electrical and Computer Engineering, 2018, University of Texas – Austin

 Regression testing - running tests after a change - has become a critical component of software development, but as projects grow bigger it becomes a… (more)

Subjects/Keywords: Regression; Test; Selection; VHDL; RTS

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APA (6th Edition):

Loyola, J. L. (2018). Eksen : regression test selection for VHDL. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63753

Chicago Manual of Style (16th Edition):

Loyola, Jose Luis. “Eksen : regression test selection for VHDL.” 2018. Masters Thesis, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/63753.

MLA Handbook (7th Edition):

Loyola, Jose Luis. “Eksen : regression test selection for VHDL.” 2018. Web. 03 Mar 2021.

Vancouver:

Loyola JL. Eksen : regression test selection for VHDL. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/63753.

Council of Science Editors:

Loyola JL. Eksen : regression test selection for VHDL. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63753


University of Texas – Austin

3. Dini, Nima. MKorat : a novel approach for memorizing the Korat search and some potential applications.

Degree: MSin Engineering, Electrical and Computer engineering, 2016, University of Texas – Austin

 Writing logical constraints that describe properties of desired inputs enables an effective approach for systematic software testing, which can find many bugs. The key problem… (more)

Subjects/Keywords: Software testing; Test input generation

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APA (6th Edition):

Dini, N. (2016). MKorat : a novel approach for memorizing the Korat search and some potential applications. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/38682

Chicago Manual of Style (16th Edition):

Dini, Nima. “MKorat : a novel approach for memorizing the Korat search and some potential applications.” 2016. Masters Thesis, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/38682.

MLA Handbook (7th Edition):

Dini, Nima. “MKorat : a novel approach for memorizing the Korat search and some potential applications.” 2016. Web. 03 Mar 2021.

Vancouver:

Dini N. MKorat : a novel approach for memorizing the Korat search and some potential applications. [Internet] [Masters thesis]. University of Texas – Austin; 2016. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/38682.

Council of Science Editors:

Dini N. MKorat : a novel approach for memorizing the Korat search and some potential applications. [Masters Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/38682


University of Texas – Austin

4. Chaurasia, Shobhit. Dialog for natural language to code.

Degree: MSin Computer Sciences, Computer Science, 2017, University of Texas – Austin

 Generating computer code from natural language descriptions has been a long-standing problem in computational linguistics. Prior work in this domain has restricted itself to generating… (more)

Subjects/Keywords: Dialog; Interactive systems; Neural network; Deep learning; Semantic parsing; Computer code; Software engineering

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APA (6th Edition):

Chaurasia, S. (2017). Dialog for natural language to code. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62886

Chicago Manual of Style (16th Edition):

Chaurasia, Shobhit. “Dialog for natural language to code.” 2017. Masters Thesis, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/62886.

MLA Handbook (7th Edition):

Chaurasia, Shobhit. “Dialog for natural language to code.” 2017. Web. 03 Mar 2021.

Vancouver:

Chaurasia S. Dialog for natural language to code. [Internet] [Masters thesis]. University of Texas – Austin; 2017. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/62886.

Council of Science Editors:

Chaurasia S. Dialog for natural language to code. [Masters Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62886

5. Celik, Ahmet. Proof engineering for large-scale verification projects.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Software controls many aspects of our daily lives, thus, software correctness is of utmost importance. One way to develop correct-by-construction software is by using proof… (more)

Subjects/Keywords: Proof assistants; Verification; Parallelism; Proof engineering; Proof selection; Regression testing; Mutation testing; Coq

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Celik, A. (2019). Proof engineering for large-scale verification projects. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5348

Chicago Manual of Style (16th Edition):

Celik, Ahmet. “Proof engineering for large-scale verification projects.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://dx.doi.org/10.26153/tsw/5348.

MLA Handbook (7th Edition):

Celik, Ahmet. “Proof engineering for large-scale verification projects.” 2019. Web. 03 Mar 2021.

Vancouver:

Celik A. Proof engineering for large-scale verification projects. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Mar 03]. Available from: http://dx.doi.org/10.26153/tsw/5348.

Council of Science Editors:

Celik A. Proof engineering for large-scale verification projects. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5348


University of Texas – Austin

6. Qiu, Rui, active 21st century. Scaling and certifying symbolic execution.

Degree: PhD, Electrical and Computer engineering, 2016, University of Texas – Austin

 Symbolic execution is a powerful, systematic program analysis approach that has received much visibility in the last decade. The key idea in symbolic execution is… (more)

Subjects/Keywords: Symbolic execution; Composition; Certification; Distribution; Symbolic PathFinder

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APA (6th Edition):

Qiu, Rui, a. 2. c. (2016). Scaling and certifying symbolic execution. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46495

Chicago Manual of Style (16th Edition):

Qiu, Rui, active 21st century. “Scaling and certifying symbolic execution.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/46495.

MLA Handbook (7th Edition):

Qiu, Rui, active 21st century. “Scaling and certifying symbolic execution.” 2016. Web. 03 Mar 2021.

Vancouver:

Qiu, Rui a2c. Scaling and certifying symbolic execution. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/46495.

Council of Science Editors:

Qiu, Rui a2c. Scaling and certifying symbolic execution. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46495

7. -3839-4626. A framework for device-to-device communication between mobile devices using heterogeneous channels.

Degree: PhD, Electrical and Computer Engineering, 2019, University of Texas – Austin

 Device-to-device (D2D) communication technologies are growing in availability and popularity and are commonly used to facilitate applications in the Internet of Things (IoT) environments. Such… (more)

Subjects/Keywords: Computer science; Embedded systems; Smart environments; Middleware; Access control; Internet of Things; Device to device communication

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APA (6th Edition):

-3839-4626. (2019). A framework for device-to-device communication between mobile devices using heterogeneous channels. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/3198

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-3839-4626. “A framework for device-to-device communication between mobile devices using heterogeneous channels.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://dx.doi.org/10.26153/tsw/3198.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-3839-4626. “A framework for device-to-device communication between mobile devices using heterogeneous channels.” 2019. Web. 03 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3839-4626. A framework for device-to-device communication between mobile devices using heterogeneous channels. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Mar 03]. Available from: http://dx.doi.org/10.26153/tsw/3198.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-3839-4626. A framework for device-to-device communication between mobile devices using heterogeneous channels. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/3198

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

8. Zhang, Yuqun. Modeling and predicting data for business intelligence.

Degree: PhD, Electrical and Computer engineering, 2016, University of Texas – Austin

 Business intelligence is an area where data and actionable information can be analyzed and provided to make more informed business actions. In general, any technique… (more)

Subjects/Keywords: Business intelligence; Data modeling; Data prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, Y. (2016). Modeling and predicting data for business intelligence. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46572

Chicago Manual of Style (16th Edition):

Zhang, Yuqun. “Modeling and predicting data for business intelligence.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/46572.

MLA Handbook (7th Edition):

Zhang, Yuqun. “Modeling and predicting data for business intelligence.” 2016. Web. 03 Mar 2021.

Vancouver:

Zhang Y. Modeling and predicting data for business intelligence. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/46572.

Council of Science Editors:

Zhang Y. Modeling and predicting data for business intelligence. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46572


University of Texas – Austin

9. -1790-0721. Automated synthesis and debugging of declarative models in alloy.

Degree: PhD, Electrical and Computer Engineering, 2018, University of Texas – Austin

 In theory, formal specifications offer numerous benefits in developing more reliable software. In practice however, the use of specifications is rather limited, and practitioners often… (more)

Subjects/Keywords: Expression generation; Sketching; Fault localization; Automated program repair; Alloy

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APA (6th Edition):

-1790-0721. (2018). Automated synthesis and debugging of declarative models in alloy. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/71511

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-1790-0721. “Automated synthesis and debugging of declarative models in alloy.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/71511.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-1790-0721. “Automated synthesis and debugging of declarative models in alloy.” 2018. Web. 03 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-1790-0721. Automated synthesis and debugging of declarative models in alloy. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/71511.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-1790-0721. Automated synthesis and debugging of declarative models in alloy. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/71511

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

10. Sullivan, Allison. Automated testing and sketching of alloy models.

Degree: PhD, Electrical and Computer Engineering, 2017, University of Texas – Austin

 Models of software systems, e.g., designs, play an important role in the development of reliable and dependable systems. However, writing correct designs is hard. What… (more)

Subjects/Keywords: Alloy; AUnit; Testing; Specifications; Program synthesis; Program sketching; Automated test generation; Coverage; Test framework; Unit tests; Declarative model; SAT

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APA (6th Edition):

Sullivan, A. (2017). Automated testing and sketching of alloy models. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47299

Chicago Manual of Style (16th Edition):

Sullivan, Allison. “Automated testing and sketching of alloy models.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/47299.

MLA Handbook (7th Edition):

Sullivan, Allison. “Automated testing and sketching of alloy models.” 2017. Web. 03 Mar 2021.

Vancouver:

Sullivan A. Automated testing and sketching of alloy models. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/47299.

Council of Science Editors:

Sullivan A. Automated testing and sketching of alloy models. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/47299


University of Texas – Austin

11. -4326-5362. Robust behavioral malware detection.

Degree: PhD, Electrical and Computer Engineering, 2018, University of Texas – Austin

 Computer security attacks evolve to evade deployed defenses. Recent attacks have ranged from exploiting generic software vulnerabilities in memory-unsafe languages such as buffer overflows and… (more)

Subjects/Keywords: Computer security; Malware detection; Behavioral malware detection; Intrusion detection; Machine learning; Artificial intelligence

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APA (6th Edition):

-4326-5362. (2018). Robust behavioral malware detection. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/67580

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-4326-5362. “Robust behavioral malware detection.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/67580.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-4326-5362. “Robust behavioral malware detection.” 2018. Web. 03 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-4326-5362. Robust behavioral malware detection. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/67580.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-4326-5362. Robust behavioral malware detection. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/67580

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

12. Kim, Jongwook. Reflective and relativistic refactoring with feature-awareness.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 Refactoring is a core technology in modern software development. It is central to popular software design movements, such as Extreme Programming [23] and Agile software… (more)

Subjects/Keywords: Refactoring; Design pattern; Software product line; Software development; Feature-awareness; Refactoring speed; Refactoring expressiveness; Refactoring engines; Scripting performance; Feature-aware refactoring

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kim, J. (2017). Reflective and relativistic refactoring with feature-awareness. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47286

Chicago Manual of Style (16th Edition):

Kim, Jongwook. “Reflective and relativistic refactoring with feature-awareness.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/47286.

MLA Handbook (7th Edition):

Kim, Jongwook. “Reflective and relativistic refactoring with feature-awareness.” 2017. Web. 03 Mar 2021.

Vancouver:

Kim J. Reflective and relativistic refactoring with feature-awareness. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/47286.

Council of Science Editors:

Kim J. Reflective and relativistic refactoring with feature-awareness. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/47286


University of Texas – Austin

13. -8333-9656. Effective bug detection and localization using information retrieval.

Degree: PhD, Electrical and Computer engineering, 2016, University of Texas – Austin

 Software bugs pose a fundamental threat to the reliability of software systems, even in systems designed with the best software engineering (SE) teams using the… (more)

Subjects/Keywords: Software testing; Automatic bug localization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-8333-9656. (2016). Effective bug detection and localization using information retrieval. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/40245

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-8333-9656. “Effective bug detection and localization using information retrieval.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 03, 2021. http://hdl.handle.net/2152/40245.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-8333-9656. “Effective bug detection and localization using information retrieval.” 2016. Web. 03 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-8333-9656. Effective bug detection and localization using information retrieval. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 03]. Available from: http://hdl.handle.net/2152/40245.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-8333-9656. Effective bug detection and localization using information retrieval. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/40245

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

.