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Combining Learning and Engagement Strategies in a Software Testing Learning Environment
There continues to be an increase in enrollments in various computing programs at academic institutions due to many job opportunities available in the information, communication, and technology sectors. This enrollment surge has presented several challenges in many Computer Science (CS), Information Technology (IT), and Software Engineering (SE) programs at universities and colleges. One such challenge is that many instructors in CS/IT/SE programs continue to use learning approaches that are not learner centered and therefore are not adequately preparing students to be proficient in the ever-changing computing industry. To mitigate this challenge, instructors need to use evidence-based pedagogical approaches, e.g., active learning, to improve student learning and engagement in the classroom and equip students with the skills necessary to be lifelong learners. This article presents an approach that combines learning and engagement strategies (LESs) in learning environments using different teaching modalities to improve student learning and engagement. We describe how LESs are integrated into face-to-face (F2F) and online class activities. The LESs currently used are collaborative learning , gamification , problem-based learning , and social interaction . We describe an approach used to quantify each LES used during class activities based on a set of characteristics for LESs and the traditional lecture-style pedagogical approaches. To demonstrate the impact of using LESs in F2F class activities, we report on a study conducted over seven semesters in a software testing class at a large urban minority serving institution. The study uses a posttest-only study design, the scores of two midterm exams, and approximate class times dedicated to each LES and traditional lecture style to quantify their usage in a face-to-face software testing class. The study results showed that increasing the time dedicated to collaborative learning, gamification, and social interaction and decreasing the traditional lecture-style approach resulted in a statistically significant improvement in student learning, as reflected in the exam scores.
Enhancing Search-based Testing with Testability Transformations for Existing APIs
Search-based software testing (SBST) has been shown to be an effective technique to generate test cases automatically. Its effectiveness strongly depends on the guidance of the fitness function. Unfortunately, a common issue in SBST is the so-called flag problem , where the fitness landscape presents a plateau that provides no guidance to the search. In this article, we provide a series of novel testability transformations aimed at providing guidance in the context of commonly used API calls (e.g., strings that need to be converted into valid date/time objects). We also provide specific transformations aimed at helping the testing of REST Web Services. We implemented our novel techniques as an extension to EvoMaster , an SBST tool that generates system-level test cases. Experiments on nine open-source REST web services, as well as an industrial web service, show that our novel techniques improve performance significantly.
A Survey of Flaky Tests
Tests that fail inconsistently, without changes to the code under test, are described as flaky . Flaky tests do not give a clear indication of the presence of software bugs and thus limit the reliability of the test suites that contain them. A recent survey of software developers found that 59% claimed to deal with flaky tests on a monthly, weekly, or daily basis. As well as being detrimental to developers, flaky tests have also been shown to limit the applicability of useful techniques in software testing research. In general, one can think of flaky tests as being a threat to the validity of any methodology that assumes the outcome of a test only depends on the source code it covers. In this article, we systematically survey the body of literature relevant to flaky test research, amounting to 76 papers. We split our analysis into four parts: addressing the causes of flaky tests, their costs and consequences, detection strategies, and approaches for their mitigation and repair. Our findings and their implications have consequences for how the software-testing community deals with test flakiness, pertinent to practitioners and of interest to those wanting to familiarize themselves with the research area.
Test Suite Optimization Using Firefly and Genetic Algorithm
Software testing is essential for providing error-free software. It is a well-known fact that software testing is responsible for at least 50% of the total development cost. Therefore, it is necessary to automate and optimize the testing processes. Search-based software engineering is a discipline mainly focussed on automation and optimization of various software engineering processes including software testing. In this article, a novel approach of hybrid firefly and a genetic algorithm is applied for test data generation and selection in regression testing environment. A case study is used along with an empirical evaluation for the proposed approach. Results show that the hybrid approach performs well on various parameters that have been selected in the experiments.
Machine Learning Model to Predict Automated Testing Adoption
Software testing is an activity conducted to test the software under test. It has two approaches: manual testing and automation testing. Automation testing is an approach of software testing in which programming scripts are written to automate the process of testing. There are some software development projects under development phase for which automated testing is suitable to use and other requires manual testing. It depends on factors like project requirements nature, team which is working on the project, technology on which software is developing and intended audience that may influence the suitability of automated testing for certain software development project. In this paper we have developed machine learning model for prediction of automated testing adoption. We have used chi-square test for finding factors’ correlation and PART classifier for model development. Accuracy of our proposed model is 93.1624%.
Metaheuristic Techniques for Test Case Generation
The primary objective of software testing is to locate bugs as many as possible in software by using an optimum set of test cases. Optimum set of test cases are obtained by selection procedure which can be viewed as an optimization problem. So metaheuristic optimizing (searching) techniques have been immensely used to automate software testing task. The application of metaheuristic searching techniques in software testing is termed as Search Based Testing. Non-redundant, reliable and optimized test cases can be generated by the search based testing with less effort and time. This article presents a systematic review on several meta heuristic techniques like Genetic Algorithms, Particle Swarm optimization, Ant Colony Optimization, Bee Colony optimization, Cuckoo Searches, Tabu Searches and some modified version of these algorithms used for test case generation. The authors also provide one framework, showing the advantages, limitations and future scope or gap of these research works which will help in further research on these works.
Software Testing Under Agile, Scrum, and DevOps
The adoption of agility at a large scale often requires the integration of agile and non-agile development practices into hybrid software development and delivery environment. This chapter addresses software testing related issues for Agile software application development. Currently, the umbrella of Agile methodologies (e.g. Scrum, Extreme Programming, Development and Operations – i.e., DevOps) have become the preferred tools for modern software development. These methodologies emphasize iterative and incremental development, where both the requirements and solutions evolve through the collaboration between cross-functional teams. The success of such practices relies on the quality result of each stage of development, obtained through rigorous testing. This chapter introduces the principles of software testing within the context of Scrum/DevOps based software development lifecycle.
Quality Assurance Issues for Big Data Applications in Supply Chain Management
Heterogeneous data types, widely distributed data sources, huge data volumes, and large-scale business-alliance partners describe typical global supply chain operational environments. Mobile and wireless technologies are putting an extra layer of data source in this technology-enriched supply chain operation. This environment also needs to provide access to data anywhere, anytime to its end-users. This new type of data set originating from the global retail supply chain is commonly known as big data because of its huge volume, resulting from the velocity with which it arrives in the global retail business environment. Such environments empower and necessitate decision makers to act or react quicker to all decision tasks. Academics and practitioners are researching and building the next generation of big-data-based application software systems. This new generation of software applications is based on complex data analysis algorithms (i.e., on data that does not adhere to standard relational data models). The traditional software testing methods are insufficient for big-data-based applications. Testing big-data-based applications is one of the biggest challenges faced by modern software design and development communities because of lack of knowledge on what to test and how much data to test. Big-data-based applications developers have been facing a daunting task in defining the best strategies for structured and unstructured data validation, setting up an optimal test environment, and working with non-relational databases testing approaches. This chapter focuses on big-data-based software testing and quality-assurance-related issues in the context of Hadoop, an open source framework. It includes discussion about several challenges with respect to massively parallel data generation from multiple sources, testing methods for validation of pre-Hadoop processing, software application quality factors, and some of the software testing mechanisms for this new breed of applications
Use of Qualitative Research to Generate a Function for Finding the Unit Cost of Software Test Cases
In this article, we demonstrate a novel use of case research to generate an empirical function through qualitative generalization. This innovative technique applies interpretive case analysis to the problem of defining and generalizing an empirical cost function for test cases through qualitative interaction with an industry cohort of subject matter experts involved in software testing at leading technology companies. While the technique is fully generalizable, this article demonstrates this technique with an example taken from the important field of software testing. The huge amount of software development conducted in today's world makes taking its cost into account imperative. While software testing is a critical aspect of the software development process, little attention has been paid to the cost of testing code, and specifically to the cost of test cases, in comparison to the cost of developing code. Our research fills the gap by providing a function for estimating the cost of test cases.
Framework for Reusable Test Case Generation in Software Systems Testing
Agile methodologies have become the preferred choice for modern software development. These methods focus on iterative and incremental development, where both requirements and solutions develop through collaboration among cross-functional software development teams. The success of a software system is based on the quality result of each stage of development with proper test practice. A software test ontology should represent the required software test knowledge in the context of the software tester. Reusing test cases is an effective way to improve the testing of software. The workload of a software tester for test-case generation can be improved, previous software testing experience can be shared, and test efficiency can be increased by automating software testing. In this chapter, the authors introduce a software testing framework (STF) that uses rule-based reasoning (RBR), case-based reasoning (CBR), and ontology-based semantic similarity assessment to retrieve the test cases from the case library. Finally, experimental results are used to illustrate some of the features of the framework.
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March 8th, 2023.
Software testing is the most significant part of the Software Development Lifecycle (SDLC) as it is something upon which the final delivery of the product is dependent. It is time consuming and an intensive process, therefore, enhanced techniques and innovative methodologies are requisite.
We provide introductory information about the well as the source of the research papers for software testing, which is either free or paid.
There are very few libraries in the research area where research papers are accessible; some papers are protected by their authors; we can access the research paper by requesting or paying the appropriate amount. The impact of technology on our businesses is exciting and the opportunities for us are unlimited.
Here are some major trends for research parameters that are changing the face of software testing
1. springer nature:.
Our very first platform that is useful for researchers is “Springer Nature”. Springer Nature is a publishing , educational, and research-based company. The company looks to provide resources primarily for researchers and scientists.
Springer Nature advances discovery by publishing trusted research, supporting the development of new ideas and championing open science. We are committed to playing our part in accelerating solutions to address the world’s urgent challenges.
There are some journals published by Springer that are specifically designed for software testers’ research. “ Software Quality Journal “ and “ Automated Software Engineering ” are the journals where researchers can publish their research as well as some past researchers’ papers for reference. These journals are generally free to readers, but some papers are protected by the author; users can access the references after requesting access or paying access fees. For access to the Springer Nature Library, follow the link https://www.springernature.com/gp
Read Also: Personality Analysis of Software Testers A Scientific Approach
Web of Science is the world’s most powerful research engine, which is a subscription platform that gives access to many databases including reference and citation data from academic journals, conference proceedings, and other materials in a variety of academic subjects.
It was created by the Institute for Scientific Information. It is utilized for searching of a subject and cited references; for instance, it retrieves the articles that are cited by a reference article and also helps in the viewing of the references that are already cited in a relevant article.
Clarivate is the current owner which helps you collect and analyze information for insights you can easily act on. Under this, we can get the papers based on title or keywords. Based on software testing, the platform almost covers the majority of research for access to the Web of Science Library by using this link https://mjl.clarivate.com/search-results.
“Mendeley” is a reference management programme that was established in 2007 by PhD students Paul Foeckler, Victor Henning, and Jan Reichelt and was purchased by Elsevier in 2013. It is used to organise and distribute research papers, as well as to produce bibliographies for scholarly works. Following the purchase, the Mendeley team expanded its product portfolio while iterating on its core reference management application. Mendeley can track reader numbers, which have been shown to predict citation impact, although journal-level metrics are poor indicators of dependability.
It covers a large dataset about software tester research publication for more explosions Login in Mendeley and access the trending subject as references. Mendeley is a free reference manager that can help you collect references, organize your citations, and create bibliographies which manage the software that helps to manage your research data in systematic way. Below is the link which helps the researcher easily to enter in mendeley https://www.mendeley.com/?interaction_required=true
Read Also: History of Software Testing Estimation Models for Cost Analysis
“ResearchGate” is a commercial social networking service for academics and researchers around the world that allows them to exchange papers, ask and answer questions, and locate partners i. e. it discover scientific knowledge and stay connected to the world of science While viewing articles does not necessitate registration, site members must have an email address from a recognised university or be personally certified as published researchers.
The research gate shows the result based on the title and the keywords under the banner of ResearchGate, no specific journal is designed for software testing. For reference purposes, it covers a wide range of papers in the software testing domain and getting the papers based on the title and keywords do follow the following link https://www.researchgate.net/.
5. Institute of Electrical and Electronics Engineers (IEEE)
The “Institute of Electrical and Electronics Engineers (IEEE)” is a professional society for electronic and electrical engineering, which is an organization dedicated to advancing innovation and technological excellence for the benefit of humanity, is the world’s largest technical professional society. It is designed to serve professionals involved in all aspects of the electrical, electronic, and computing fields and related areas of science and technology that underlie modern civilization. The IEEE’s aim is to advance technology for the benefit of humanity.
The IEEE has some journals that are very useful for the domain of software testing. The journals are as follows: “IEEE Access”, “IEEE Transactions on Software Engineering,” and “IEEE Software” are the three most popular journals that are useful for software tester research aspirants and there is IEEE Standard for Software Test Documentation which is a set of basic test documents that are associated with the dynamic aspects of software testing that is, the execution of procedures and code.
The role of IEEE in current technology is to advance computer and information processing science and technology; promote professional interaction; and keep members up-to-date on the latest developments. If you want to publish your article or need some standard papers for reference, go to IEEE and access them; some are free and some are subscription-based. We are providing the link for easy access https://ieeexplore.ieee.org/Xplore/home.jsp
“Elsevier” is a scientific, technical, and medical Publishing Corporation which takes a hand in shaping the future of knowledge with roles dedicated to delivering innovations and improvements to our platforms. Elsevier has Agile work flows embedded within the company which utilizes cutting-edge technological practices and focused on improving your technical skills, and they provide access to resources to help you progress.
Electronic and print editions of periodicals, text books, and reference works covering the health, life, physical, and social sciences are among the products and services offered. Academic and government research institutions, corporate research labs, booksellers, librarians, scientific researchers, authors, editors, physicians, nurses, allied health professionals, medical and nursing students and schools, medical researchers, pharmaceutical companies, hospitals, and research establishments are among the target markets. Following are the some standard Elsevier journals in the software testing domain:
1. “Security Controls Evaluation, Testing, and Assessment Handbook.” 2. “SDL ’97: Time for Testing” 3. “Practical Model-Based Testing” 4. “Usability Testing Essentials”: For direct access to the Elsevier go through the link https://www.elsevier.com/en-in
Read Also: Software Testing Latest Trends & Technology in 2023
7. semantic scholar.
“Semantic Scholar” is an artificial intelligence-powered scientific literature research tool created at the Allen Institute for AI and made public in November 2015. It makes use of improvements in natural language processing to produce scientific article summaries. Semantic Scholar is examined to locate primary papers of selected secondary studies and identify missing venues.
The proposed search strategy is used to check the ability to retrieve primary papers of each secondary study. The Semantic Scholar team is investigating the application of artificial intelligence in natural language processing, machine learning, human-computer interaction, software testing, and information retrieval.
Semantic Scholar summarises scientific literature in one statement. One of its goals was to overcome the difficulty of reading multiple titles and long abstracts on mobile devices. It also aims to guarantee that the three million scientific articles published each year reach readers. Basically, it is the collection of databases of all the types of research libraries available here; basically, it is domain-independent. We can search the article on this platform by applying some filters such as subject, domain, title, keywords, etc. We provide a link to Semantic Scholar for research aspirants to easily search any research article in any domain. https://www.semanticscholar.org/
“Science Direct” is a website that gives access to Elsevier’s enormous bibliographic collection of scientific and medical publications. It emphasizes developing a strategy for testing and validation and show how to design a testing and validation program that deliver information in a timely and cost effective manner.
Researchers, teachers, students, healthcare and information professionals use ScienceDirect to improve the way they search, discover, read, understand and share scholarly research.
ScienceDirect combines authoritative, full-text scientific, technical and health publications with smart, intuitive functionality so that users can stay informed in their fields and can work more effectively and efficiently. Article abstracts are freely available, but full text access usually needs a membership or pay-per-view payment, unless the material is freely available via open access.
The following journals are relevant to the software testing domain:
1. Advances in Computers 2. Perspectives on Data Science for Software Engineering 3. Journal of Systems and Software 4. Applied Soft Computing 5. Information and Software Technology 6. Information Sciences.
These journals are very useful for researchers in terms of publication and reference purposes; however, some articles in these journals are author-restricted and require access permission. We’ve included a link to ScienceDirect home page for your convenience https://www.sciencedirect.com/.
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The software development industry has devolved into a front line. Every company wants its product to be the greatest and in order to make your product the greatest on the market; you must ensure that it is of the highest quality.
The primary goal of this blog is to provide a research sources used for references and to help aspiring researchers in their search for researchers.
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