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Metric-centered and technology-independent architectural views for software comprehension

The maintenance of applications is a crucial activity in the software industry. The high cost of this process is due to the effort invested on software comprehension since, in most of cases, there is no up-to-...

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Back to the future: origins and directions of the “Agile Manifesto” – views of the originators

In 2001, seventeen professionals set up the manifesto for agile software development. They wanted to define values and basic principles for better software development. On top of being brought into focus, the ...

Investigating the effectiveness of peer code review in distributed software development based on objective and subjective data

Code review is a potential means of improving software quality. To be effective, it depends on different factors, and many have been investigated in the literature to identify the scenarios in which it adds qu...

On the benefits and challenges of using kanban in software engineering: a structured synthesis study

Kanban is increasingly being used in diverse software organizations. There is extensive research regarding its benefits and challenges in Software Engineering, reported in both primary and secondary studies. H...

Challenges on applying genetic improvement in JavaScript using a high-performance computer

Genetic Improvement is an area of Search Based Software Engineering that aims to apply evolutionary computing operators to the software source code to improve it according to one or more quality metrics. This ...

Actor’s social complexity: a proposal for managing the iStar model

Complex systems are inherent to modern society, in which individuals, organizations, and computational elements relate with each other to achieve a predefined purpose, which transcends individual goals. In thi...

Investigating measures for applying statistical process control in software organizations

The growing interest in improving software processes has led organizations to aim for high maturity, where statistical process control (SPC) is required. SPC makes it possible to analyze process behavior, pred...

An approach for applying Test-Driven Development (TDD) in the development of randomized algorithms

TDD is a technique traditionally applied in applications with deterministic algorithms, in which the input and the expected result are known. However, the application of TDD with randomized algorithms have bee...

Supporting governance of mobile application developers from mining and analyzing technical questions in stack overflow

There is a need to improve the direct communication between large organizations that maintain mobile platforms (e.g. Apple, Google, and Microsoft) and third-party developers to solve technical questions that e...

Working software over comprehensive documentation – Rationales of agile teams for artefacts usage

Agile software development (ASD) promotes working software over comprehensive documentation. Still, recent research has shown agile teams to use quite a number of artefacts. Whereas some artefacts may be adopt...

Development as a journey: factors supporting the adoption and use of software frameworks

From the point of view of the software framework owner, attracting new and supporting existing application developers is crucial for the long-term success of the framework. This mixed-methods study explores th...

Applying user-centered techniques to analyze and design a mobile application

Techniques that help in understanding and designing user needs are increasingly being used in Software Engineering to improve the acceptance of applications. Among these techniques we can cite personas, scenar...

A measurement model to analyze the effect of agile enterprise architecture on geographically distributed agile development

Efficient and effective communication (active communication) among stakeholders is thought to be central to agile development. However, in geographically distributed agile development (GDAD) environments, it c...

A survey of search-based refactoring for software maintenance

This survey reviews published materials related to the specific area of Search-Based Software Engineering that concerns software maintenance and, in particular, refactoring. The survey aims to give a comprehen...

Guest editorial foreword for the special issue on automated software testing: trends and evidence

Similarity testing for role-based access control systems.

Access control systems demand rigorous verification and validation approaches, otherwise, they can end up with security breaches. Finite state machines based testing has been successfully applied to RBAC syste...

An algorithm for combinatorial interaction testing: definitions and rigorous evaluations

Combinatorial Interaction Testing (CIT) approaches have drawn attention of the software testing community to generate sets of smaller, efficient, and effective test cases where they have been successful in det...

How diverse is your team? Investigating gender and nationality diversity in GitHub teams

Building an effective team of developers is a complex task faced by both software companies and open source communities. The problem of forming a “dream”

Investigating factors that affect the human perception on god class detection: an analysis based on a family of four controlled experiments

Evaluation of design problems in object oriented systems, which we call code smells, is mostly a human-based task. Several studies have investigated the impact of code smells in practice. Studies focusing on h...

On the evaluation of code smells and detection tools

Code smells refer to any symptom in the source code of a program that possibly indicates a deeper problem, hindering software maintenance and evolution. Detection of code smells is challenging for developers a...

On the influence of program constructs on bug localization effectiveness

Software projects often reach hundreds or thousands of files. Therefore, manually searching for code elements that should be changed to fix a failure is a difficult task. Static bug localization techniques pro...

DyeVC: an approach for monitoring and visualizing distributed repositories

Software development using distributed version control systems has become more frequent recently. Such systems bring more flexibility, but also greater complexity to manage and monitor multiple existing reposi...

A genetic algorithm based framework for software effort prediction

Several prediction models have been proposed in the literature using different techniques obtaining different results in different contexts. The need for accurate effort predictions for projects is one of the ...

Elaboration of software requirements documents by means of patterns instantiation

Studies show that problems associated with the requirements specifications are widely recognized for affecting software quality and impacting effectiveness of its development process. The reuse of knowledge ob...

ArchReco: a software tool to assist software design based on context aware recommendations of design patterns

This work describes the design, development and evaluation of a software Prototype, named ArchReco, an educational tool that employs two types of Context-aware Recommendations of Design Patterns, to support us...

On multi-language software development, cross-language links and accompanying tools: a survey of professional software developers

Non-trivial software systems are written using multiple (programming) languages, which are connected by cross-language links. The existence of such links may lead to various problems during software developmen...

SoftCoDeR approach: promoting Software Engineering Academia-Industry partnership using CMD, DSR and ESE

The Academia-Industry partnership has been increasingly encouraged in the software development field. The main focus of the initiatives is driven by the collaborative work where the scientific research work me...

Issues on developing interoperable cloud applications: definitions, concepts, approaches, requirements, characteristics and evaluation models

Among research opportunities in software engineering for cloud computing model, interoperability stands out. We found that the dynamic nature of cloud technologies and the battle for market domination make clo...

Game development software engineering process life cycle: a systematic review

Software game is a kind of application that is used not only for entertainment, but also for serious purposes that can be applicable to different domains such as education, business, and health care. Multidisc...

Correlating automatic static analysis and mutation testing: towards incremental strategies

Traditionally, mutation testing is used as test set generation and/or test evaluation criteria once it is considered a good fault model. This paper uses mutation testing for evaluating an automated static anal...

A multi-objective test data generation approach for mutation testing of feature models

Mutation approaches have been recently applied for feature testing of Software Product Lines (SPLs). The idea is to select products, associated to mutation operators that describe possible faults in the Featur...

An extended global software engineering taxonomy

In Global Software Engineering (GSE), the need for a common terminology and knowledge classification has been identified to facilitate the sharing and combination of knowledge by GSE researchers and practition...

A systematic process for obtaining the behavior of context-sensitive systems

Context-sensitive systems use contextual information in order to adapt to the user’s current needs or requirements failure. Therefore, they need to dynamically adapt their behavior. It is of paramount importan...

Distinguishing extended finite state machine configurations using predicate abstraction

Extended Finite State Machines (EFSMs) provide a powerful model for the derivation of functional tests for software systems and protocols. Many EFSM based testing problems, such as mutation testing, fault diag...

Extending statecharts to model system interactions

Statecharts are diagrams comprised of visual elements that can improve the modeling of reactive system behaviors. They extend conventional state diagrams with the notions of hierarchy, concurrency and communic...

On the relationship of code-anomaly agglomerations and architectural problems

Several projects have been discontinued in the history of the software industry due to the presence of software architecture problems. The identification of such problems in source code is often required in re...

An approach based on feature models and quality criteria for adapting component-based systems

Feature modeling has been widely used in domain engineering for the development and configuration of software product lines. A feature model represents the set of possible products or configurations to apply i...

Patch rejection in Firefox: negative reviews, backouts, and issue reopening

Writing patches to fix bugs or implement new features is an important software development task, as it contributes to raise the quality of a software system. Not all patches are accepted in the first attempt, ...

Investigating probabilistic sampling approaches for large-scale surveys in software engineering

Establishing representative samples for Software Engineering surveys is still considered a challenge. Specialized literature often presents limitations on interpreting surveys’ results, mainly due to the use o...

Characterising the state of the practice in software testing through a TMMi-based process

The software testing phase, despite its importance, is usually compromised by the lack of planning and resources in industry. This can risk the quality of the derived products. The identification of mandatory ...

Self-adaptation by coordination-targeted reconfigurations

A software system is self-adaptive when it is able to dynamically and autonomously respond to changes detected either in its internal components or in its deployment environment. This response is expected to ensu...

Templates for textual use cases of software product lines: results from a systematic mapping study and a controlled experiment

Use case templates can be used to describe functional requirements of a Software Product Line. However, to the best of our knowledge, no efforts have been made to collect and summarize these existing templates...

F3T: a tool to support the F3 approach on the development and reuse of frameworks

Frameworks are used to enhance the quality of applications and the productivity of the development process, since applications may be designed and implemented by reusing framework classes. However, frameworks ...

NextBug: a Bugzilla extension for recommending similar bugs

Due to the characteristics of the maintenance process followed in open source systems, developers are usually overwhelmed with a great amount of bugs. For instance, in 2012, approximately 7,600 bugs/month were...

Assessing the benefits of search-based approaches when designing self-adaptive systems: a controlled experiment

The well-orchestrated use of distilled experience, domain-specific knowledge, and well-informed trade-off decisions is imperative if we are to design effective architectures for complex software-intensive syst...

Revealing influence of model structure and test case profile on the prioritization of test cases in the context of model-based testing

Test case prioritization techniques aim at defining an order of test cases that favor the achievement of a goal during test execution, such as revealing failures as earlier as possible. A number of techniques ...

A metrics suite for JUnit test code: a multiple case study on open source software

The code of JUnit test cases is commonly used to characterize software testing effort. Different metrics have been proposed in literature to measure various perspectives of the size of JUnit test cases. Unfort...

Designing fault-tolerant SOA based on design diversity

Over recent years, software developers have been evaluating the benefits of both Service-Oriented Architecture (SOA) and software fault tolerance techniques based on design diversity. This is achieved by creat...

Method-level code clone detection through LWH (Light Weight Hybrid) approach

Many researchers have investigated different techniques to automatically detect duplicate code in programs exceeding thousand lines of code. These techniques have limitations in finding either the structural o...

The problem of conceptualization in god class detection: agreement, strategies and decision drivers

The concept of code smells is widespread in Software Engineering. Despite the empirical studies addressing the topic, the set of context-dependent issues that impacts the human perception of what is a code sme...

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Research on Various Software Development Lifecycle Models

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• First Online: 31 October 2020
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• Nabeel Asif Khan 17  

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1290))

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• Proceedings of the Future Technologies Conference

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Software development life cycle models define a guideline for the design, development and testing of the software. These models ensure that software meets the customer requirements and is developed within the given timeframe and budget. There are various SDLC models used for software development. This paper describes various types of traditional SDLC models like waterfall mode, v model and spiral model. It also describes contemporary models like agile model and RAD model. The paper also highlights the importance of security procedures in software development life cycle process. The basic motive of this paper is to study variety of models and make a relative study of them to understand their advantages and disadvantages.

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Kumar, S., Dubey, P.: Software development life cycle (SDLC) analytical comparison and survey on traditional and agile methodology, Abhinav Nat. Mon. Refereed J. Res. Sci. Technol. 2 (8) 2013

Google Scholar  

Nanda, M.P.: Productivity improvement through agile transformation. J. Manage. Res. Anal. 5 (4), 211–218 (2018)

Bhatnagar, M.V., Rather, M.A.: A comparative study of software development life cycle models. J. Appl. Innov. Eng. Manage. 4 (10), 23–29 (2015)

Navita: A study on software development life cycle & its model. In: International Journal of Engineering Research in Computer Science and Engineering, September 2017

Kavitha, D., Lalband, N.: Software engineering for smart healthcare applications. Int. J. Appl. Innovative Technol. Exploring Eng. 8 , 325–331 (2015)

Dubey, D., Mishra, A.: A comparative study of different software development life cycle models in different scenarios. Int. J. Adv. Res. Comput. Sci. Manage. Stud. 1 (5) 2013

Idrees, M., Iqbal, S.Z.: Z-SDLC model: a new model for software development life cycle (SDLC). Int. J. Eng. Adv. Res. Technol. 3 , 8 (2017)

Mani, Y.K.: A review paper on software development lifecycle models. J. Emerg. Technol. Innovative Res. 5 (2), 2018

de Vicente Mohino, J., Bermejo Higuera, J., Bermejo Higuera, J.R., Sicilia Montalvo, J.A.: The application of a new secure software development life cycle (S-SDLC) with agile methodologies. Electronics 8 (11), 1218 (2019)

Kaur, S.: International Journal of Advanced Research in Computer Science and Software Engineering, November 2015

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Arizona State University, Tempe, AZ, 85281, USA

Nabeel Asif Khan

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Khan, N.A. (2021). Research on Various Software Development Lifecycle Models. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Proceedings of the Future Technologies Conference (FTC) 2020, Volume 3. FTC 2020. Advances in Intelligent Systems and Computing, vol 1290. Springer, Cham. https://doi.org/10.1007/978-3-030-63092-8_24

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Schmidt, D., 2024: The Latest Work from the SEI: an OpenAI Collaboration, Generative AI, and Zero Trust. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed April 15, 2024, https://insights.sei.cmu.edu/blog/the-latest-work-from-the-sei-an-openai-collaboration-generative-ai-and-zero-trust/.

APA Citation

Schmidt, D. (2024, April 10). The Latest Work from the SEI: an OpenAI Collaboration, Generative AI, and Zero Trust. Retrieved April 15, 2024, from https://insights.sei.cmu.edu/blog/the-latest-work-from-the-sei-an-openai-collaboration-generative-ai-and-zero-trust/.

Chicago Citation

Schmidt, Douglas. "The Latest Work from the SEI: an OpenAI Collaboration, Generative AI, and Zero Trust." Carnegie Mellon University, Software Engineering Institute's Insights (blog) . Carnegie Mellon's Software Engineering Institute, April 10, 2024. https://insights.sei.cmu.edu/blog/the-latest-work-from-the-sei-an-openai-collaboration-generative-ai-and-zero-trust/.

IEEE Citation

D. Schmidt, "The Latest Work from the SEI: an OpenAI Collaboration, Generative AI, and Zero Trust," Carnegie Mellon University, Software Engineering Institute's Insights (blog) . Carnegie Mellon's Software Engineering Institute, 10-Apr-2024 [Online]. Available: https://insights.sei.cmu.edu/blog/the-latest-work-from-the-sei-an-openai-collaboration-generative-ai-and-zero-trust/. [Accessed: 15-Apr-2024].

BibTeX Code

@misc{schmidt_2024, author={Schmidt, Douglas}, title={The Latest Work from the SEI: an OpenAI Collaboration, Generative AI, and Zero Trust}, month={Apr}, year={2024}, howpublished={Carnegie Mellon University, Software Engineering Institute's Insights (blog)}, url={https://insights.sei.cmu.edu/blog/the-latest-work-from-the-sei-an-openai-collaboration-generative-ai-and-zero-trust/}, note={Accessed: 2024-Apr-15} }

The Latest Work from the SEI: an OpenAI Collaboration, Generative AI, and Zero Trust

Douglas Schmidt (Vanderbilt University)

April 10, 2024, published in.

Software Engineering Research and Development

As part of an ongoing effort to keep you informed about our latest work, this blog post summarizes some recent publications from the SEI in the areas of large language models for cybersecurity , software engineering and acquisition with generative AI , zero trust , large language models in national security , capability-based planning , supply chain risk management , generative AI in software engineering and acquisition , and quantum computing .

These publications highlight the latest work of SEI technologists in these areas. This post includes a listing of each publication, author(s), and links where they can be accessed on the SEI website.

Considerations for Evaluating Large Language Models for Cybersecurity Tasks by Jeff Gennari, Shing-hon Lau, Samuel J. Perl, Joel Parish (OpenAI), and Girish Sastry (OpenAI)

Generative artificial intelligence (AI) and large language models (LLMs) have taken the world by storm. The ability of LLMs to perform tasks seemingly on par with humans has led to rapid adoption in a variety of different domains, including cybersecurity. However, caution is needed when using LLMs in a cybersecurity context due to the impactful consequences and detailed particularities. Current approaches to LLM evaluation tend to focus on factual knowledge as opposed to applied, practical tasks. But cybersecurity tasks often require more than just factual recall to complete. Human performance on cybersecurity tasks is often assessed in part on their ability to apply concepts to realistic situations and adapt to changing circumstances. This paper contends the same approach is necessary to accurately evaluate the capabilities and risks of using LLMs for cybersecurity tasks. To enable the creation of better evaluations, we identify key criteria to consider when designing LLM cybersecurity assessments. These criteria are further refined into a set of recommendations for how to assess LLM performance on cybersecurity tasks. The recommendations include properly scoping tasks, designing tasks based on real-world cybersecurity phenomena, minimizing spurious results, and ensuring results are not misinterpreted. Read the white paper .

The Future of Software Engineering and Acquisition with Generative AI by Douglas Schmidt (Vanderbilt University), Anita Carleton, James Ivers, Ipek Ozkaya, John E. Robert, and Shen Zhang

We stand at a pivotal moment in software engineering, with artificial intelligence (AI) playing a crucial role in driving approaches poised to enhance software acquisition, analysis, verification, and automation. While generative AI tools initially sparked excitement for their potential to reduce errors, scale changes effortlessly, and drive innovation, concerns have emerged. These concerns encompass security risks, unforeseen failures, and issues of trust. Empirical research on generative AI development assistants reveals that productivity and quality gains depend not only on the sophistication of tools but also on task flow redesign and expert judgment.

In this webcast, SEI researchers explore the future of software engineering and acquisition using generative AI technologies. They examine current applications, envision future possibilities, identify research gaps, and discuss the critical skill sets that software engineers and stakeholders need to effectively and responsibly harness generative AI’s potential. Fostering a deeper understanding of AI’s role in software engineering and acquisition accentuates its potential and mitigates its risks.

The webcast covers

• how to identify suitable use cases when starting out with generative AI technology
• the practical applications of generative AI in software engineering and acquisition
• how developers and decision makers can harness generative AI technology

View the webcast .

Zero Trust Industry Days 2024 Scenario: Secluded Semiconductors, Inc. by Rhonda Brown

Each accepted presenter at the SEI Zero Trust Industry Days 2024 event develops and proposes a solution for this scenario: A company is operating a chip manufacturing facility on an island where there may be loss of connectivity and cloud services for short or extended periods of time. There are many considerations when addressing the challenges of a zero trust implementation, including varying perspectives and philosophies. This event offers a deep examination of how solution providers and other organizations interpret and address the challenges of implementing zero trust. Using a scenario places boundaries on the zero trust space to yield richer discussions.

This year’s event focuses on the Industrial Internet of Things (IIoT), legacy systems, smart cities, and cloud-hosted services in a manufacturing environment. Read the white paper .

Using Large Language Models in the National Security Realm By Shannon Gallagher

At the request of the White House, the Office of the Director of National Intelligence (ODNI) began exploring use cases for large language models (LLMs) within the Intelligence Community (IC). As part of this effort, ODNI sponsored the Mayflower Project at Carnegie Mellon University’s Software Engineering Institute from May 2023 through September 2023. The Mayflower Project attempted to answer the following questions:

• How might the IC set up a baseline, stand-alone LLM?
• How might the IC customize LLMs for specific intelligence use cases?
• How might the IC evaluate the trustworthiness of LLMs across use cases?

In this SEI Podcast, Shannon Gallagher, AI engineering team lead, and Rachel Dzombak, former special advisor to the director of the SEI’s AI Division, discuss the findings and recommendations from the Mayflower Project and provide additional background information about LLMs and how they can be engineered for national security use cases. Listen/View the SEI Podcast .

Navigating Capability-Based Planning: The Benefits, Challenges, and Implementation Essentials By Anandi Hira and William Nichols

Capability-based planning (CBP) defines a framework that has an all-encompassing view of existing abilities and future needs for strategically deciding what is needed and how to effectively achieve it. Both business and government acquisition domains use CBP for financial success or to design a well-balanced defense system. The definitions understandably vary across these domains. This paper endeavors to consolidate these definitions to provide a comprehensive view of CBP, its potential, and practical implementation of its principles. Read the white paper .

Ask Us Anything: Supply Chain Risk Management By Brett Tucker and Matthew J. Butkovic

According to the Verizon Data Breach Report , Log4j-related exploits have occurred less frequently over the past year. However, this Common Vulnerabilities and Exposures (CVE) flaw was originally documented in 2021. The threat still exists despite increased awareness. Over the past few years, the Software Engineering Institute has developed guidance and practices to help organizations reduce threats to U.S. supply chains. In this webcast, Brett Tucker and Matthew Butkovic, answer enterprise risk management questions to help organizations achieve operational resilience in the cyber supply chain. The webcast covers

• enterprise risk governance and how to assess organization’s risk appetite and policy as it relates to and integrates cyber risks into a global risk portfolio
• regulatory directives on third-party risk
• the agenda and topics to be covered in the upcoming CERT Cyber Supply Chain Risk Management Symposium in February

The Measurement Challenges in Software Assurance and Supply Chain Risk Management by Nancy R. Mead, Carol Woody, and Scott Hissam

In this paper, the authors discuss the metrics needed to predict cybersecurity in open source software and how standards are needed to make it easier to apply these metrics in the supply chain. The authors provide examples of potentially useful metrics and underscore the need for data collection and analysis to validate the metrics. They assert that defining metrics, collecting and analyzing data to illustrate their utility, and using standard methods requires unbiased collaborative work to achieve the desired results. Read the white paper .

The Cybersecurity of Quantum Computing: 6 Areas of Research

By Tom Scanlon

Research and development of quantum computers continues to grow at a rapid pace. The U.S. government alone spent more than $800 million on quantum information science research in 2022. Thomas Scanlon, who leads the data science group in the SEI CERT Division, was recently invited to be a participant in the Workshop on Cybersecurity of Quantum Computing, co-sponsored by the National Science Foundation (NSF) and the White House Office of Science and Technology Policy, to examine the emerging field of cybersecurity for quantum computing. In this SEI podcast, Scanlon discusses how to create the discipline of cyber protection of quantum computing and outlines six areas of future research in quantum cybersecurity.

Listen to/view the podcast .

Additional Resources

View the latest SEI research in the SEI Digital Library . View the latest podcasts in the SEI Podcast Series . View the latest installments in the SEI Webcast Series .

Author Page

Digital library publications, send a message, more by the author, applying large language models to dod software acquisition: an initial experiment, april 1, 2024 • by douglas schmidt (vanderbilt university) , john e. robert, 10 benefits and 10 challenges of applying large language models to dod software acquisition, january 22, 2024 • by john e. robert , douglas schmidt (vanderbilt university), the latest work from the sei, january 15, 2024 • by douglas schmidt (vanderbilt university), the top 10 blog posts of 2023, january 8, 2024 • by douglas schmidt (vanderbilt university), applying generative ai to software engineering: navigating ethical and educational landscapes, december 11, 2023 • by john e. robert , douglas schmidt (vanderbilt university), more in software engineering research and development, applying the sei sbom framework, february 5, 2024 • by carol woody, get updates on our latest work..

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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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