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Two UT Dallas CS Professors Given Most Influential Paper Awards for Their Work in Software Engineering

Since its inception, groundbreaking research within the UT Dallas Computer Science Department has consistently been seen as influential and has been in the national and international spotlight. The UT Dallas Computer Science Department has frequently found itself at the top of university rankings across diverse subject areas: ranked UT Dallas at eighth place for natural language processingfifth place for software engineering11th place for artificial intelligence, and sixth place for embedded & real-time systems during 2010-2020.  In the past few years, many UT Dallas Computer Science faculty members have been recognized for their excellence in research. This spring, the work of Drs. Andrian Marcus and W. Eric Wong, both UT Dallas CS Professors and experts in the field of software engineering, received Most Influential Paper (MIP) awards (a.k.a., Test of Time awards) for papers they published in 2010.

The paper “Using Mutation to Automatically Suggest Fixes for Faulty Programs” published in 2010 by UT Dallas computer science professor and software engineering expert,  Dr. Wong,  received the Most Influential Paper Award from the 13th IEEE International Conference on Software Testing, Verification, and Validation (ICST 2020) – a premier conference on software testing. It was co-authored with Dr. Vidroha Debroy, a former Ph.D. student of Dr. Wong at UT Dallas, and now a Principal Software Engineer at AT&T.

“Many problems in software engineering may not have analytical solutions. Instead, various methodologies and tool support, based on experiences or heuristics, are proposed. In general, they need to be verified by empirical data collected from case studies on different systems in diversified environments.” noted Dr. Wong. He further explained, “Unlike hardware that can be mass-produced with the same quality once its specification is fixed, software implemented by different programmers even using the same requirements may have very different quality.”

These two dilemmas make research on software quality very challenging. How can researchers find real-life applications with a sufficient number of bugs that actually happened during development for their experiments? One solution is to inject mutation-based bugs into programs. Studies have shown that these mutants can represent realistic bugs and can yield reliable results when used in experiments.

An interesting question arises. Instead of muting mutating a program to generate its faulty versions, can we do it in the reverse opposite direction? Can we mutate a faulty program to generate its correct version? In order to improve the efficiency, this paper also proposed to use fault localization techniques to prioritize program segments that are likely to contain bugs. Experimental results show that mutation, along with fault localization, can indeed suggest fixes for faulty programs and take a step towards automatic debugging, a time consuming and labor-intensive task for software developers.

Dr. Wong also pointed out a very important question in program repairing that still needs to be answered. While the coupling effect in mutation testing assumes, supported by empirical data, assumes that test cases capable of catching simple bugs are also likely to help programmers catch more complex bugs, do we have a similar hypothesis for bug fixing? Will more complex bugs be automatically fixed by repairing simple bugs?

Dr. Wong is the Editor-in-Chief of IEEE Transactions on Reliability (TRel or TR) and the Founding Director of the UT Dallas Advanced Research Center for Software Testing and Quality Assurance, which is an NSF-sponsored Industry/University Cooperative Research site affiliated with the nationwide Security and Software Engineering Research Center (S2ERC).

A paper published in 2010 by Dr. Andrian Marcus and his co-authors Drs. Sonia Haiduc, Jairo Aponte, Laura Moreno, was recently recognized as the Most Influential Paper from the 17th IEEE Working Conference on Reverse Engineering (WCRE 2010). They will be receiving the Most Influential Paper Award for their paper titled “On the Use of Automated Text Summarization Techniques for Summarizing Source Code.” The award was presented at the 27th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2020) in London, Ontario, in February this year.

“The paper is among the ones that laid the foundations of a new field of research in program comprehension: automated source code summarization. It investigates the use of automated text summarization techniques, applied for the generation of natural language source code summaries. This area of research has grown significantly in the past few years, fueled by recent advances in machine learning and natural language processing.”, noted Dr. Marcus.

Drs. Haiduc, Aponte, and Moreno are former doctoral students of Dr. Marcus. Dr. Aponte (Ph.D. 2012) is an associate professor at the National University of Colombia – Bogota; Dr. Haiduc (Ph.D. 2013) is an associate professor at Florida State University, and Dr. Moreno (Ph.D. 2016) is an assistant professor at Colorado State University. This is the sixth MIP award received by Dr. Marcus and he noted that “it is special because with this award, all my former doctoral students (who were publishing ten years ago or before) received at least one MIP award for papers we co-authored,” noted Dr. Marcus.

Dr. Marcus’ previous MIP awards are for the following papers:

  • On the Use of Relevance Feedback in IR-Based Concept Location“, by Gay, G., Haiduc, S., Marcus, A., Menzies, T., published at the 25th IEEE International Conference on Software Maintenance and Evolution (ICME 2009).
  • Combining Formal Concept Analysis with Information Retrieval for Concept Location in Source Code“, by Poshyvanyk, D., Marcus, A., published at the 15th IEEE International Conference on Program Comprehension (ICPC 2007).
  • A Task-Oriented View of Software Visualization“, by Maletic, J.I., Marcus, A., Collard, M., published at the 1st IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT 2002).
  • The Conceptual Coupling Metrics for Object-Oriented Systems“, by Poshyvanyk, D., Marcus, A., published at the 22nd IEEE International Conference on Software Maintenance (ICSM 2006).
  • An Information Retrieval Approach to Concept Location in Source Code.”, by Marcus, A., Sergeyev, A., Rajlich, V., Maletic, J., published at the 11th IEEE Working Conference on Reverse Engineering (WCRE 2004).

Dr. Marcus’ current research focuses on software evolution and program comprehension. He is best known for his work on using information retrieval and text mining techniques for software analysis to support comprehension during software evolution.


The UT Dallas Computer Science program is one of the largest Computer Science departments in the United States with over 3,315 bachelors-degree students, more than 1,110 master’s students, 165 Ph.D. students,  52 tenure-track faculty members, and 44 full-time senior lecturers, as of Fall 2019. With The University of Texas at Dallas’ unique history of starting as a graduate institution first, the CS Department is built on a legacy of valuing innovative research and providing advanced training for software engineers and computer scientists.

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