skip to main content

Explore Research Products in the NSF-PAR

Title: JUGE : An infrastructure for benchmarking Java unit test generators
Summary

Researchers and practitioners have designed and implemented various automated test case generators to support effective software testing. Such generators exist for various languages (e.g., Java, C#, or Python) and various platforms (e.g., desktop, web, or mobile applications). The generators exhibit varying effectiveness and efficiency, depending on the testing goals they aim to satisfy (e.g., unit‐testing of libraries versus system‐testing of entire applications) and the underlying techniques they implement. In this context, practitioners need to be able to compare different generators to identify the most suited one for their requirements, while researchers seek to identify future research directions. This can be achieved by systematically executing large‐scale evaluations of different generators. However, executing such empirical evaluations is not trivial and requires substantial effort to select appropriate benchmarks, setup the evaluation infrastructure, and collect and analyse the results. In this Software Note, we present ourJUnit Generation Benchmarking Infrastructure(JUGE) supporting generators (search‐based, random‐based, symbolic execution, etc.) seeking to automate the production of unit tests for various purposes (validation, regression testing, fault localization, etc.). The primary goal is to reduce the overall benchmarking effort, ease the comparison of several generators, and enhance the knowledge transfer between academia and industry by standardizing the evaluation and comparison process. Since 2013, several editions of a unit testing tool competition, co‐located with the Search‐Based Software Testing Workshop, have taken place whereJUGEwas used and evolved. As a result, an increasing amount of tools (over 10) from academia and industry have been evaluated onJUGE, matured over the years, and allowed the identification of future research directions. Based on the experience gained from the competitions, we discuss the expected impact ofJUGEin improving the knowledge transfer on tools and approaches for test generation between academia and industry. Indeed, theJUGEinfrastructure demonstrated an implementation design that is flexible enough to enable the integration of additional unit test generation tools, which is practical for developers and allows researchers to experiment with new and advanced unit testing tools and approaches.

  more » « less
NSF-PAR ID:
10386737
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Software Testing, Verification and Reliability
Volume:
33
Issue:
3
ISSN:
0960-0833
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ( , Information storage and retrieval)
    null (Ed.)
    The first major goal of this project is to build a state-of-the-art information storage, retrieval, and analysis system that utilizes the latest technology and industry methods. This system is leveraged to accomplish another major goal, supporting modern search and browse capabilities for a large collection of tweets from the Twitter social media platform, web pages, and electronic theses and dissertations (ETDs). The backbone of the information system is a Docker container cluster running with Rancher and Kubernetes. Information retrieval and visualization is accomplished with containers in a pipelined fashion, whether in the cluster or on virtual machines, for Elasticsearch and Kibana, respectively. In addition to traditional searching and browsing, the system supports full-text and metadata searching. Search results include facets as a modern means of browsing among related documents. The system supports text analysis and machine learning to reveal new properties of collection data. These new properties assist in the generation of available facets. Recommendations are also presented with search results based on associations among documents and with logged user activity. The information system is co-designed by five teams of Virginia Tech graduate students, all members of the same computer science class, CS 5604. Although the project is an academic exercise, it is the practice of the teams to work and interact as though they are groups within a company developing a product. The teams on this project include three collection management groups -- Electronic Theses and Dissertations (ETD), Tweets (TWT), and Web-Pages (WP) -- as well as the Front-end (FE) group and the Integration (INT) group to help provide the overarching structure for the application. This submission focuses on the work of the Integration (INT) team, which creates and administers Docker containers for each team in addition to administering the cluster infrastructure. Each container is a customized application environment that is specific to the needs of the corresponding team. Each team will have several of these containers set up in a pipeline formation to allow scaling and extension of the current system. The INT team also contributes to a cross-team effort for exploring the use of Elasticsearch and its internally associated database. The INT team administers the integration of the Ceph data storage system into the CS Department Cloud and provides support for interactions between containers and the Ceph filesystem. During formative stages of development, the INT team also has a role in guiding team evaluations of prospective container components and workflows. The INT team is responsible for the overall project architecture and facilitating the tools and tutorials that assist the other teams in deploying containers in a development environment according to mutual specifications agreed upon with each team. The INT team maintains the status of the Kubernetes cluster, deploying new containers and pods as needed by the collection management teams as they expand their workflows. This team is responsible for utilizing a continuous integration process to update existing containers. During the development stage the INT team collaborates specifically with the collection management teams to create the pipeline for the ingestion and processing of new collection documents, crossing services between those teams as needed. The INT team develops a reasoner engine to construct workflows with information goal as input, which are then programmatically authored, scheduled, and monitored using Apache Airflow. The INT team is responsible for the flow, management, and logging of system performance data and making any adjustments necessary based on the analysis of testing results. The INT team has established a Gitlab repository for archival code related to the entire project and has provided the other groups with the documentation to deposit their code in the repository. This repository will be expanded using Gitlab CI in order to provide continuous integration and testing once it is available. Finally, the INT team will provide a production distribution that includes all embedded Docker containers and sub-embedded Git source code repositories. The INT team will archive this distribution on the Virginia Tech Docker Container Registry and deploy it on the Virginia Tech CS Cloud. The INT-2020 team owes a sincere debt of gratitude to the work of the INT-2019 team. This is a very large undertaking and the wrangling of all of the products and processes would not have been possible without their guidance in both direct and written form. We have relied heavily on the foundation they and their predecessors have provided for us. We continue their work with systematic improvements, but also want to acknowledge their efforts Ibid. Without them, our progress to date would not have been possible. 
    more » « less
  2. ; ; ; ; ; ; ; ; ; ( , American Society for Engineering Education)
    National Science Foundation (NSF) funded Engineering Research Centers (ERC) must complement their technical research with various education and outreach opportunities to: 1) improve and promote engineering education, both within the center and to the local community; 2) encourage and include the underrepresented populations to participate in Engineering activities; and 3) advocate communication and collaboration between industry and academia. ERCs ought to perform an adequate evaluation of their educational and outreach programs to ensure that beneficial goals are met. Each ERC has complete autonomy in conducting and reporting such evaluation. Evaluation tools used by individual ERCs are quite similar, but each ERC has designed their evaluation processes in isolation, including evaluation tools such as survey instruments, interview protocols, focus group protocols, and/or observation protocols. These isolated efforts resulted in redundant resources spent and lacking outcome comparability across ERCs. Leaders from three different ERCs led and initiated a collaborative effort to address the above issue by building a suite of common evaluation instruments that all current and future ERCs can use. This leading group consists of education directors and external evaluators from all three partners ERCs and engineering education researchers, who have worked together for two years. The project intends to address the four ERC program clusters: Broadening Participation in Engineering, Centers and Networks, Engineering Education, and Engineering Workforce Development. The instruments developed will pay attention to culture of inclusion, outreach activities, mentoring experience, and sustained interest in engineering. The project will deliver best practices in education program evaluation, which will not only support existing ERCs, but will also serve as immediate tools for brand new ERCs and similar large-scale research centers. Expanding the research beyond TEEC and sharing the developed instruments with NSF as well as other ERCs will also promote and encourage continual cross-ERC collaboration and research. Further, the joint evaluation will increase the evaluation consistency across all ERC education programs. Embedded instrumental feedback loops will lead to continual improvement to ERC education performance and support the growth of an inclusive and innovative engineering workforce. Four major deliveries are planned. First, develop a common quantitative assessment instrument, named Multi-ERC Instrument Inventory (MERCII). Second, develop a set of qualitative instruments to complement MERCII. Third, create a web-based evaluation platform for MERCII. Fourth, update the NSF ERC education program evaluation best practice manual. These deliveries together will become part of and supplemented by an ERC evaluator toolbox. This project strives to significantly impact how ERCs evaluate their educational and outreach programs. Single ERC based studies lack the sample size to truly test the validity of any evaluation instruments or measures. A common suite of instruments across ERCs would provide an opportunity for a large scale assessment study. The online platform will further provide an easy-to-use tool for all ERCs to facilitate evaluation, share data, and reporting impacts. 
    more » « less
  3. ; ; ( , ASEE annual conference exposition proceedings)
    In September 2019, the fourth and final workshop on the Future of Mechatronics and Robotics Education (FoMRE) was held at a Lawrence Technological University in Southfield, MI. This workshop was organized by faculty at several universities with financial support from industry partners and the National Science Foundation. The purpose of the workshops was to create a cohesive effort among mechatronics and robotics courses, minors and degree programs. Mechatronics and Robotics Engineering (MRE) is an integration of mechanics, controls, electronics, and software, which provides a unique opportunity for engineering students to function on multidisciplinary teams. Due to its multidisciplinary nature, it attracts diverse and innovative students, and graduates better-prepared professional engineers. In this fast growing field, there is a great need to standardize educational material and make MRE education more widely available and easier to adopt. This can only be accomplished if the community comes together to speak with one clear voice about not only the benefits, but also the best ways to teach it. These efforts would also aid in establishing more of these degree programs and integrating minors or majors into existing computer science, mechanical engineering, or electrical engineering departments. The final workshop was attended by approximately 50 practitioners from industry and academia. Participants identified many practical skills required for students to succeed in an MRE curriculum and as practicing engineers after graduation. These skills were then organized into the following categories: professional, independent learning, controller design, numerical simulation and analysis, electronics, software development, and system design. For example, professional skills include technical reports, presentations, and documentation. Independent learning includes reading data sheets, performing internet searches, doing a literature review, and having a maker mindset. Numerical simulation skills include understanding data, presenting data graphically, solving and simulating in software such as MATLAB, Simulink and Excel. Controller design involves selecting a controller, tuning a controller, designing to meet specifications, and understanding when the results are good enough. Electronics skills include selecting sensors, interfacing sensors, interfacing actuators, creating printed circuit boards, wiring on a breadboard, soldering, installing drivers, using integrated circuits, and using microcontrollers. Software development of embedded systems includes agile program design, state machines, analyzing and evaluating code results, commenting code, troubleshooting, debugging, AI and machine learning. Finally, system design includes prototyping, creating CAD models, design for manufacturing, breaking a system down into subsystems, integrating and interfacing subcomponents, having a multidisciplinary perspective, robustness, evaluating tradeoffs, testing, validation, and verification, failure, effect, and mode analysis. A survey was prepared and sent out to the participants from all four workshops as well as other robotics faculty, researchers and industry personnel in order to elicit a broader community response. Because one of the biggest challenges in mechatronics and robotics education is the absence of standardized curricula, textbooks, platforms, syllabi, assignments, and learning outcomes, this was a vital part of the process to achieve some level of consensus. This paper presents an introduction to MRE education, related work on existing programs, methods, results of the practical skills survey, and then draws conclusions based upon these results. It aims to create the foundation for standardizing the development of student skills in mechatronics and robotics curricula across institutions, disciplines, majors and minors. The survey was completed by 94 participants and it was clear that there is a consensus that the primary skills students should have upon completion of MRE courses or a program is a broader multidisciplinary systems-level perspective, an ability to problem solve, and an ability to design a system to meet specifications. 
    more » « less
  4. ; ; ( , ASEE Conferences)
    The development of inclusive leaders is essential for the success of future engineering and our nation. Equipping students with vital leadership-enabling competencies is necessary to develop a workforce that is prepared to act ethically, and responsibly, and tackle unforeseen challenges in the future. Inclusive leaders, or leaders that are self-aware, empathetic, and prioritize diversity, equity, and inclusion in their decision-making, are essential for the forward progress of engineering. A growing body of literature highlights the numerous ways in which students may develop leadership skills outside of the classroom through involvement in out-of-class activities (e.g., internships, clubs, sports, and research experiences). Research Experiences for Undergraduates (REUs) may provide students with a unique opportunity to develop leadership-enabling competencies that will prepare them for leadership in graduate school, the engineering industry, or academia. The goal of this research was to identify how students’ engagement in an engineering education virtual REU site contributed to their development of essential leadership-enabling competencies. The research question guiding this study was ‘What inclusive leadership-enabling competencies and skills did engineering students learn and develop during an engineering education Summer REU program?’ Qualitative data was collected via weekly open-ended surveys from 9 students (7 women, 2 men) participating in an REU over 9 weeks. Participants in this study consisted of students from underrepresented groups in engineering (e.g., Black, Latinx, women, students from low SES backgrounds, or first-generation students), attending large public research universities across the United States. This study implemented mixed methods to understand what leadership competencies were occurring most frequently and how students were learning and developing these competencies. A combination of text mining for frequency (quantitative analysis) and deductive and inductive coding (qualitative analysis) was used to analyze the data. A codebook was developed based on the leadership-coupled professional competencies that engineering industry leaders identified as essential for engineers entering the workforce. Researchers also allowed for other competencies and leadership-enabling skills to emerge from the data. Findings from this work indicate that students were developing a vast amount of inclusive leadership knowledge and skills from participating in the virtual REU site. This paper highlights, through the use of word clouds and text mining software, the many leadership-enabling competencies that participants developed throughout the summer research experience (e.g., learning, communication, adaptability, self-awareness, balance, networking, etc.). Further, students were able to develop digital literacy, increased communication skills, knowledge of career pathways, intrapersonal growth, and interpersonal relations. This work offers a novel contribution to the literature in understanding how students can develop technical engineering and research skills as well as professional and leadership skills in the same space. Findings from this work help to illuminate the benefits of this virtual REU site focused on engineering education research resulting in terms of developing inclusive leadership skills. Implications for future REU programs, students interested in developing leadership skills, engineering graduate programs, academia, and industry employers are outlined. 
    more » « less
  5. ; ; ; ( , Proceedings of the ACM on Programming Languages)
    Bounded-exhaustive testing (BET), which exercises a program under test for all inputs up to some bounds, is an effective method for detecting software bugs. Systematic property-based testing is a BET approach where developers write test generation programs that describe properties of test inputs. Hybrid test generation programs offer the most expressive way to write desired properties by freely combining declarative filters and imperative generators. However, exploring hybrid test generation programs, to obtain test inputs, is both computationally demanding and challenging to parallelize. We present the first programming and execution models, dubbed Tempo, for parallel exploration of hybrid test generation programs. We describe two different strategies for mapping the computation to parallel hardware and implement them both for GPUs and CPUs. We evaluated Tempo by generating instances of various data structures commonly used for benchmarking in the BET domain. Additionally, we generated CUDA programs to stress test CUDA compilers, finding four bugs confirmed by the developers. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email