| title | layout | description | image |
|---|---|---|---|
Research |
defaults |
Gregory M. Kapfhammer conducts research in fields such as software engineering and software testing. |
/download/images/7029911579_0ddd6e8352_z.jpg |
{% capture page_title %} {{page.title}} {% endcapture %} {% include _jumbotrons/head_jumbotron.html title=page_title subtitle="implementing innovation in" highlight="software engineering" %}
As an experimental computer scientist, the goal of my research is to design, implement, and rigorously evaluate techniques and tools that support the creation of useful, dependable, and efficient software. My research addresses the challenges in fields such as software engineering, software testing, and computer systems. I conduct this research with undergraduates at Allegheny College, graduate students and professors at several universities, and colleagues in industry.
My research is empirical in nature because it involves the application of the scientific method to formulate problem statements, carry out experiments, take observations, statistically analyze and visualize the data sets, and draw conclusions based on the results. Each project focuses on the development and evaluation of software artifacts that can be used in both empirical studies and real-world practice by undergraduate and graduate students, software engineers, and computer scientists in both academia and industry. In addition to supporting my professional service, my research also results in award-winning and frequently cited research papers, oft-complimented presentations, and useful free and open-source software.
My research has concentrated on several areas in software engineering and software testing, examples of which are summarized in the following list that references key papers.
-
Flaky Tests: Since flaky tests can pass or fail without any changes to the test code or the code under test, they are an unreliable indicator of software correctness and a major problem for software developers. To address this challenge, my research has developed an automated method that uses machine learning to predict which tests are most likely to be flaky {% include_cached _popovers/paper_reference.html cite="Parry2022a" trailing="." %} Along with proposing a methodology for automatically determining which tests have latent flakiness {% include _popovers/paper_reference.html cite="Parry2020" trailing="," %} my colleagues and I also published a survey of the literature relevant to flaky test research {% include_cached _popovers/paper_reference.html cite="Parry2022" %} and a multi-source investigation into how developers experience the impacts and causes of flaky tests {% include_cached _popovers/paper_reference.html cite="Parry2022b" trailing="." %}
-
Database Testing: Given the importance of verifying the behavior of a database application, my PhD dissertation {% include_cached _popovers/paper_reference.html cite="Kapfhammer2007d" %} presented an approach for testing this type of software; a notable paper derived from my dissertation is {% include_cached _popovers/paper_reference.html cite="Kapfhammer2003" trailing="." %} Since the relational schema preserves the correctness of the database's state, my research has also focused on testing this complex artifact, with {% include_cached _popovers/paper_reference.html cite="McMinn2015" %} and {% include_cached _popovers/paper_reference.html cite="McMinn2019" %} being examples of papers. Recent papers such as {% include_cached _popovers/paper_reference.html cite="Alsharif2020" %} and {% include_cached _popovers/paper_reference.html cite="Alsharif2020a" %} present techniques for improving the efficiency of regression testing for database schemas.
-
Web Testing: In response to the prevalence and complexity of mobile-ready web sites, my research has developed automated tools for checking the pages in these sites. Some examples of papers describing methods for automatically detecting defects in web pages include {% include_cached _popovers/paper_reference.html cite="Walsh2017" %} and {% include_cached _popovers/paper_reference.html cite="Walsh2017a" trailing="." %} The automated approach introduced in {% include_cached _popovers/paper_reference.html cite="Althomali2019" %} can visually confirm and classify the reported responsive layout failures in a web page. The method described in {% include_cached _popovers/paper_reference.html cite="Walsh2020" %} can automatically identify potential regressions from the correct responsive layout of a web page. Finally, recent work introduced a method to automatically repair a layout failure in a responsive web page {% include_cached _popovers/paper_reference.html cite="Althomali2022" trailing="." %}
-
Mutation Testing: Given the challenges associated with accurately judging the quality of a test suite, my research has designed efficient and useful ways to perform test assessment through mutation analysis. Presenting and evaluating automated techniques that efficiently insert synthetic faults into both real-world Java programs and relational database schemas, some examples of papers include {% include _popovers/paper_reference.html cite="Just2012b" trailing="," %} {% include_cached _popovers/paper_reference.html cite="Wright2014" trailing="," %} and {% include_cached _popovers/paper_reference.html cite="McMinn2019" trailing="." %}
-
Regression Testing: Since software is often incrementally developed, my research on regression testing has created research automated ways to efficiently and effectively run test suites for complex programs. Some examples of papers that present and evaluate regression testing techniques include {% include _popovers/paper_reference.html cite="Walcott2006" trailing="," %} {% include_cached _popovers/paper_reference.html cite="Lin2014" trailing="," %} and {% include_cached _popovers/paper_reference.html cite="Lin2017" trailing="." %} Leading the way in the realistic assessment of regression testing, papers such as {% include _popovers/paper_reference.html cite="Paterson2018" %} and {% include _popovers/paper_reference.html cite="Paterson2019" %} show how to conduct rigorous experiments with real program faults.
-
Search-Based Testing: Using a fitness function as a guide to a suitable solution, search-based methods have shown promise in supporting many software engineering tasks. My work has focused on creating and maintaining frameworks that support the development of search-based tools, with {% include_cached _popovers/paper_reference.html cite="McMinn2016b" %} being one example. Other papers such as {% include_cached _popovers/paper_reference.html cite="Conrad2010a" %} and {% include_cached _popovers/paper_reference.html cite="Kukunas2010a" %} describe search-based solutions to key software engineering challenges. Recent papers like {% include_cached _popovers/paper_reference.html cite="Alsharif2019" %} present ways to involve humans when studying the usefulness of tests that were automatically generated by search-based techniques.
-
Performance Evaluation: Given the importance of equipping software engineers with the insights and tools they need to create efficient software, my work has concentrated on developing and studying tools that automatically assess program performance. Focusing on the empirical evaluation of real-world software components like databases, papers in this area include {% include_cached _popovers/paper_reference.html cite="Jones2011" trailing="," %} {% include_cached _popovers/paper_reference.html cite="Burdette2012" trailing="," %} and {% include_cached _popovers/paper_reference.html cite="Kinneer2015" trailing="." %} Papers such as {% include_cached _popovers/paper_reference.html cite="Kotelyanskii2014a" %} highlight how my research has also characterized the influence that the parameters of a search-based algorithm have on its efficiency and effectiveness.
-
Research Methods: My surveys of software testing techniques provide a starting point for people exploring this field, with {% include_cached _popovers/paper_reference.html cite="Kapfhammer2004" %} and {% include_cached _popovers/paper_reference.html cite="Kapfhammer2010" %} being examples of such articles. Papers like {% include_cached _popovers/paper_reference.html cite="Kapfhammer2016" %} and {% include_cached _popovers/paper_reference.html cite="McMinn2016" %} show how I have articulated a research agenda for the field of software engineering that stresses, for instance, the need for well-tested statistical methods. I have also written papers, like {% include_cached _popovers/paper_reference.html cite="Alsharif2018a" %} and {% include_cached _popovers/paper_reference.html cite="Alsharif2018b" trailing="," %} that explain how to replicate my research.
Do you work on these topics and are you interested in collaborating with me on a project in the fields of software engineering and software testing? If so, then please contact me with your ideas.