Relevant bibliographies by topics / Software testing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Software testing'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Software testing"

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Seth, Jyotsna, Mukul Varshney, and Shivani Garg Abha Kiran Rajpoot. "Automated Testing: An Edge Over Manual Software Testing." International Journal of Trend in Scientific Research and Development Volume-1, Issue-4 (June 30, 2017): 710–13. http://dx.doi.org/10.31142/ijtsrd2232.

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Ansari, Mohammed Afzal, and Kiran Bhimrao Ingle. "Software Testing." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 979–84. http://dx.doi.org/10.22214/ijraset.2022.43914.

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Abstract— With the developing complexity of today’s software program applications injunction with the increasing competitive pressure has driven the excellent assurance of developed software towards new heights. software program trying out is an inevitable part of the software program development Lifecycle and retaining in keeping with its criticality in the pre and submit development process makes it something that have to be catered with stronger and green methodologies and strategies. This paper objectives to speak about the prevailing in addition to advanced trying out techniques for the betterquality warranty functions. Keywords— Testing Methodologies, Software Testing Life Cycle, Testing Frameworks, Automation Testing, Test Driven Development, Test optimization, Quality Metrics
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Armitage, A. F. "Testing Software." Measurement and Control 24, no. 9 (November 1991): 286–91. http://dx.doi.org/10.1177/002029409102400904.

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Freeman, H. "Software testing." IEEE Instrumentation & Measurement Magazine 5, no. 3 (September 2002): 48–50. http://dx.doi.org/10.1109/mim.2002.1028373.

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Hu, Shueh-Cheng, and I.-Ching Chen. "A Software Testing Service Supporting Long-Lived and Asynchronous Testing Jobs." Lecture Notes on Software Engineering 2, no. 4 (2014): 314–19. http://dx.doi.org/10.7763/lnse.2014.v2.142.

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Tawfig, S., and A. Mili. "Testing Software Product Lines: A Case Study." International Journal of Computer and Electrical Engineering 7, no. 1 (2015): 1–25. http://dx.doi.org/10.17706/ijcee.2015.v7.870.

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Cai, Kai-Yuan. "Optimal software testing and adaptive software testing in the context of software cybernetics." Information and Software Technology 44, no. 14 (November 2002): 841–55. http://dx.doi.org/10.1016/s0950-5849(02)00108-8.

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Molu, Fatma. "Software Testing Strategy." International Journal of E-Services and Mobile Applications 6, no. 2 (April 2014): 23–36. http://dx.doi.org/10.4018/ijesma.2014040103.

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Complex financial conversion projects with large budgets have many different challenges. For companies that want to survive in conditions of tough competition, legacy (old) systems must continue to provide the required service throughout the project life cycle and in some circumstances even after project completion partly. In this case, the term coexistence comes into prominence. During this period, testing phase takes more critical role while integration systems' complexity and risk amount increase. Determining testing approach to use is essential to make sure both transformed and legacy systems provide service synchronously. In this paper, testing practices applied in the long conversion processes are discussed. Primarily, the basic features of the critical financial systems are addressed and then the main adoption methods in the literature are summarized. Then a variety of testing methodologies are presented depending on those adoption methods. These samples based on real-life experiences of transformation project. The most extensive example of real-time online financial systems is core banking systems. This paper covers the testing life cycle process of the large scale project of core banking system transformation project of a bank in Turkey.
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Ebert, Christof, Divith Bajaj, and Michael Weyrich. "Testing Software Systems." IEEE Software 39, no. 4 (July 2022): 8–17. http://dx.doi.org/10.1109/ms.2022.3166755.

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Noijons, José. "Oral Testing Software." CALICO Journal 19, no. 2 (November 30, 2017): 462–71. http://dx.doi.org/10.1558/cj.35164.

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Dissertations / Theses on the topic "Software testing"

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Дядечко, Алла Миколаївна, Алла Николаевна Дядечко, Alla Mykolaivna Diadechko, and V. V. Kontchevich. "Software testing and software bugs." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/13487.

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Henderson, Lehman Edwin Jr. "Testing eigenvalue software." Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/185744.

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This dissertation describes a significant advance in automated testing of eigenvalue software. Several programs are described that assist the researcher in verifying that a new program is stable. Using backwards error techniques popularized by Wilkinson, a maximizer or "hill climber" systematically searches for instabilities in the program being tested. This work builds on software first reported by Miller and removes the restriction of not being able to work on iterative methods. Testing eigenvalue solver programs with sets of small random input data can often find instabilities, but the described hill climbing technique is more efficient. Using only ten sets of starting points, the maximizer will often find the instability, if it exists, in only a few tries.
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Медведєва, С. О., and О. А. Абдуллаєв. "Testing. Basic concepts of testing software." Thesis, ВНТУ, 2019. http://ir.lib.vntu.edu.ua//handle/123456789/24789.

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У даній доповіді розглянуто основні концепції та види тестування програмного забезпечення, а також окреслено важливість приділення йому великої уваги у інших сферах.
This paper examines the basic concepts and methods of software testing, and highlights the importance of paying attention to testing in other areas
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Noller, Yannic. "Hybrid Differential Software Testing." Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/21968.

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Differentielles Testen ist ein wichtiger Bestandteil der Qualitätssicherung von Software, mit dem Ziel Testeingaben zu generieren, die Unterschiede im Verhalten der Software deutlich machen. Solche Unterschiede können zwischen zwei Ausführungspfaden (1) in unterschiedlichen Programmversionen, aber auch (2) im selben Programm auftreten. In dem ersten Fall werden unterschiedliche Programmversionen mit der gleichen Eingabe untersucht, während bei dem zweiten Fall das gleiche Programm mit unterschiedlichen Eingaben analysiert wird. Die Regressionsanalyse, die Side-Channel Analyse, das Maximieren der Ausführungskosten eines Programms und die Robustheitsanalyse von Neuralen Netzwerken sind typische Beispiele für differentielle Softwareanalysen. Eine besondere Herausforderung liegt in der effizienten Analyse von mehreren Programmpfaden (auch über mehrere Programmvarianten hinweg). Die existierenden Ansätze sind dabei meist nicht (spezifisch) dafür konstruiert, unterschiedliches Verhalten präzise hervorzurufen oder sind auf einen Teil des Suchraums limitiert. Diese Arbeit führt das Konzept des hybriden differentiellen Software Testens (HyDiff) ein: eine hybride Analysetechnik für die Generierung von Eingaben zur Erkennung von semantischen Unterschieden in Software. HyDiff besteht aus zwei parallel laufenden Komponenten: (1) einem such-basierten Ansatz, der effizient Eingaben generiert und (2) einer systematischen Analyse, die auch komplexes Programmverhalten erreichen kann. Die such-basierte Komponente verwendet Fuzzing geleitet durch differentielle Heuristiken. Die systematische Analyse basiert auf Dynamic Symbolic Execution, das konkrete Eingaben bei der Analyse integrieren kann. HyDiff wird anhand mehrerer Experimente evaluiert, die in spezifischen Anwendungen im Bereich des differentiellen Testens ausgeführt werden. Die Resultate zeigen eine effektive Generierung von Testeingaben durch HyDiff, wobei es sich signifikant besser als die einzelnen Komponenten verhält.
Differential software testing is important for software quality assurance as it aims to automatically generate test inputs that reveal behavioral differences in software. The concrete analysis procedure depends on the targeted result: differential testing can reveal divergences between two execution paths (1) of different program versions or (2) within the same program. The first analysis type would execute different program versions with the same input, while the second type would execute the same program with different inputs. Therefore, detecting regression bugs in software evolution, analyzing side-channels in programs, maximizing the execution cost of a program over multiple executions, and evaluating the robustness of neural networks are instances of differential software analysis with the goal to generate diverging executions of program paths. The key challenge of differential software testing is to simultaneously reason about multiple program paths, often across program variants, in an efficient way. Existing work in differential testing is often not (specifically) directed to reveal a different behavior or is limited to a subset of the search space. This PhD thesis proposes the concept of Hybrid Differential Software Testing (HyDiff) as a hybrid analysis technique to generate difference revealing inputs. HyDiff consists of two components that operate in a parallel setup: (1) a search-based technique that inexpensively generates inputs and (2) a systematic exploration technique to also exercise deeper program behaviors. HyDiff’s search-based component uses differential fuzzing directed by differential heuristics. HyDiff’s systematic exploration component is based on differential dynamic symbolic execution that allows to incorporate concrete inputs in its analysis. HyDiff is evaluated experimentally with applications specific for differential testing. The results show that HyDiff is effective in all considered categories and outperforms its components in isolation.
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Miller, Timothy. "Using specification animation to support specification testing and software testing /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe.pdf.

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Radnoci, Ramon. "Methods for Testing Concurrent Software." Thesis, University of Skövde, School of Humanities and Informatics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-3173.

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Most software today is concurrent and are used in everything from cell-

phones, washing machines, cars to aircraft control systems. The reliability

of the concurrent software may be more or less critical, depending on which

a.o. domain it is functioning in. Irrespective of domain, the concurrent

software must be sufficiently reliable.

It is therefore interesting to study how adaptable test methods for sequential

software are to test concurrent software. Novel test methods for concurrent

software can be developed by adapting test methods for sequential software.

In this dissertation, adaptability factors have been identified by conducting

a literature survey over state-of-the-art test methods. Directions taken in

the research of concurrent software testing is described by the survey. The

survey also demonstrates differences and similarities between test methods.

Three research contributions has been achieved by this dissertation. First,

this dissertation presents a survey over state-of-the-art-test methods. The

second contribution is the identified adaptability factors that should be

added to a test method for sequential software, that will be adapted to test

concurrent software. Finally, the third contribution to the field of concurrent

software testing is the identified future work in areas where test methods for

concurrent software has not been researched much or at all.

 

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Garrepalli, Thrinay. "Knowledge Management in Software Testing." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-10974.

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Context: Software testing is a knowledge intensive process and the use of Knowledge Management (KM) methods and principles makes software testing even more beneficial. Thus there is a need of adapting KM into software testing core process and attain the benefits that it provides in terms of cost, quality etc. There has been an extensive literature published in the context of KM in software testing. But it is still unclear about the importance of KM with respect to testing techniques as well as testing aspects i.e. each activity that takes part during testing and the outcomes that they result such as test artifacts is considered as testing aspect. Thus there is a requisite for studies to focus on identifying the challenges faced due to lack of KM along with the importance of KM with respect to testing aspects, testing techniques and thus can provide recommendations to apply Knowledge Management to those that get benefited from it.   Objectives: In this thesis, we investigate the usage and implementation of KM in Software testing. The major objectives of current thesis include, To identify various software testing aspects that receive more attention while applying KM. To analyze the software testing techniques i.e. test design, test execution and test result analysis and evaluate them and highlight which of these have more involvement of KM. To identify the software testing techniques where tacit or explicit knowledge is currently used. To gather challenges faced by industry due to lack of KM initiatives in software testing.   Methods: We conducted a Systematic Literature Review (SLR) through a snowballing method based on the guidelines from Wohlin in order to identify various software testing aspects and testing techniques that have more involvement of KM and challenges that are faced due to lack of KM. A questionnaire intended for web-based survey was prepared from the gathered literature results to complement and further supplement them and to categorize the testing techniques based on the type of knowledge they utilize. The studies were analyzed in relation to their rigor and relevance to assess the quality of the results. The data obtained from survey were statistically analyzed using descriptive statistics and Chi-square test of significance.   Results: We identified 35 peer reviewed papers among which 31 were primary and 4 were secondary studies. The literature review results indicated 9 testing aspects being in focus when applying KM within various adaptation contexts. In addition, few testing techniques were found to get benefited from the application of KM. Several challenges were identified from the literature review such as improper selection and application of better suited techniques, low reuse rate of Software Testing knowledge, barriers in Software testing knowledge transfer, impossible to quickly achieve the most optimum distribution of human resources during testing etc. 54 full answers were received to the survey. The survey showed that Knowledge Management was being applied in software testing in most of the industries. It was observed that test result analysis, test case design, test planning and testing techniques stood out as the most important testing aspects being focused while KM is applied. Regarding software testing techniques, 17 test design techniques, 5 test execution techniques and 5 test result analysis techniques gain more attention in the context of KM. Moreover, the results suggest that tacit knowledge was utilized for most of these techniques. Several new challenges are obtained from the survey such as lacking quality in terms of testing results or outcomes, difficulties in finding relevant information and resources during testing, applying more effort than required during testing, having a huge loss of know-how by neglecting explicit and tacit knowledge during test design etc.   Conclusions. To conclude, various challenges are being faced due to the lack of KM. Our study also brings supporting evidence that applying KM in Software Testing is necessary i.e. to increase test effectiveness, selection and application of better suited techniques and so on. It was also observed that perceptions vary between the literature and the survey results obtained from the practitioners regarding testing aspects and testing techniques, as few aspects and techniques which are being categorized as the most important in the literature are not given the same priority by the respondents. Thus the final list of testing aspects and testing techniques is provided and empirical findings can likewise help practitioners to specifically apply KM more for those that are very much in need of it. Besides, it was found that most of the techniques require and utilize tacit knowledge to apply them and techniques such as shadowing, observing, training and recording sessions can help to store tacit knowledge for those that are in need of it. Thus researchers can recognize the advantages from this thesis and can further extend to various software life cycle models.
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Odia, Osaretin Edwin. "Testing in Software Product Lines." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3853.

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This thesis presents research aimed at investigating different activities involved in software product lines testing process and possible improvements towards achieving developing high quality software product lines at reduced cost and time. The research was performed using systematic review procedures of Kitchenham. The reviews carried out in this research covers several areas relating to software product lines testing. The reasons for performing a systematic review in this research are to; summarize the existing evidence covering testing in software product line context, to identify gaps in current research and to suggest areas for further research. The contribution of this thesis is research aimed at revealing the different activities, issues and challenges in software product lines testing. The research into the different activities in software product lines lead to the proposed SPLIT Model for software product lines testing. The model helps to clarify the steps and activities involved in the software product line testing process. It provides and easy to follow map for testers and managers in software product line development organizations. The results were mainly on how testing in software product lines can be improved upon, towards achieving software product line goals. The basic contribution is the proposed model for product line testing, investigation into, and possible improvement in, issues related to software product line testing activities.
The main purpose of the research as presented in this thesis is to present a clear picture of testing in the context of software product lines, which is quite different from testing in single product. The focus of this thesis is specifically the different steps and activities involved in software product lines testing and possible improvements in software product lines testing activities and issues towards achieving the goals of developing high quality software product lines at reduced cost and time. But, for software product lines to achieve its goals, there should be a comprehensive set of testing activities in software product lines development. The development activities from performing analyses and creating designs to integrating programs in software product line context, component testing and tools support for software product lines testing should be taken into consideration.
0046762913149 eddy_odia2002@yahoo.co.uk
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Moschoglou, Georgios Moschos. "Software testing tools and productivity." Virtual Press, 1996. http://liblink.bsu.edu/uhtbin/catkey/1014862.

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Testing statistics state that testing consumes more than half of a programmer's professional life, although few programmers like testing, fewer like test design and only 5% of their education will be devoted to testing. The main goal of this research is to test the efficiency of two software testing tools. Two experiments were conducted in the Computer Science Department at Ball State University. The first experiment compares two conditions - testing software using no tool and testing software using a command-line based testing tool - to the length of time and number of test cases needed to achieve an 80% statement coverage for 22 graduate students in the Computer Science Department. The second experiment compares three conditions - testing software using no tool, testing software using a command-line based testing tool, and testing software using a GUI interactive tool with added functionality - to the length of time and number of test cases needed to achieve 95% statement coverage for 39 graduate and undergraduate students in the same department.
Department of Computer Science
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Nguyen, Duy Cu. "Testing Techniques for Software Agents." Doctoral thesis, Università degli studi di Trento, 2009. https://hdl.handle.net/11572/368032.

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Software agents and multiagent systems are a promising technology for today's complex, distributed systems. Methodologies and techniques that address testing and reliability of these systems are increasingly demanded, in particular to support systematic verification/validation and automated test generation and execution. This work deals with two major research problems: the lack of a structured testing process in engineering software agents and the need of adequate testing techniques to tackle the nature of software agents, e.g., being autonomous, decentralized, collaborative. To address the first problem, we proposed a goal-oriented testing methodology, aiming at defining a systematic and comprehensive testing process for engineering software agents. It encompasses the development process from the early requirements analysis until the deployment. We investigated how to derive test artefacts, i.e. inputs, scenarios, and so on, from agent requirements specification and design, and use these artefacts to refine the analysis and design in order to detect problems early. More importantly, they are executed afterwards to find defects in the implementation and build confidence in the operation of the agents under development. Concerning the second problem, the peculiar properties of software agents make testing them troublesome. We developed a number of techniques to generate test cases, automatically or semi-automatically. These include goal-oriented, ontology-based, random, and evolutionary generation techniques. Our experiments have shown that each technique has different strength. For instance, while the random technique is effective in revealing crashes or exceptions, the ontology-based one is strong in detecting communication faults. The combination of these techniques can help to detect different types of fault, making software agents more reliable. All together, the generation, evaluation, and monitoring techniques form a bigger picture: our novel continuous testing method. In this method, test execution can proceed unattendedly and independently of any other human-intensive activity; test cases are generated or evolved continuously using the proposed generation techniques; test results are observed and evaluated by our monitoring and evaluation approaches to give feedbacks to the generation step. The aim of continuous testing is to exercise and stress the agents under test as much as possible, the final goal being the possibility to reveal yet unknown faults. We applied a case study to illustrate the proposed methodology and performed three experiments to evaluate the performance of the proposed techniques. The obtained results are promising.
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Books on the topic "Software testing"

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Roper, Marc. Software testing. London: McGraw, 1994.

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Software testing. 2nd ed. Indianapolis, IN: Sams Pub., 2006.

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Software testing. London: McGraw-Hill, 1994.

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Software testing. Cambridge: Cambridge University Press, 2011.

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Software testing. Indianapolis, Ind: Sams, 2001.

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Software Testing Fundamentals. New York: John Wiley & Sons, Ltd., 2003.

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Beizer, Boris. Software testing techniques. 2nd ed. New York: Van Nostrand Reinhold, 1990.

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Sharma, Mukesh. Software Testing 2020. Boca Raton : Taylor & Francis Group, CRC Press, 2017.: Auerbach Publications, 2016. http://dx.doi.org/10.1201/9781315378008.

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Majchrzak, Tim A. Improving Software Testing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27464-0.

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Jena, Ajay Kumar, Himansu Das, and Durga Prasad Mohapatra, eds. Automated Software Testing. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2455-4.

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Book chapters on the topic "Software testing"

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Peled, Doron A. "Software Testing." In Texts in Computer Science, 249–78. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3540-6_9.

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O’Regan, Gerard. "Software Testing." In Undergraduate Topics in Computer Science, 137–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07816-3_8.

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O’Regan, Gerard. "Software Testing." In Undergraduate Topics in Computer Science, 105–21. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57750-0_7.

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Fraser, Gordon, and José Miguel Rojas. "Software Testing." In Handbook of Software Engineering, 123–92. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00262-6_4.

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Majchrzak, Tim A. "Software Testing." In SpringerBriefs in Information Systems, 11–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27464-0_2.

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Irving, Damien, Kate Hertweck, Luke Johnston, Joel Ostblom, Charlotte Wickham, and Greg Wilson. "Testing Software." In Research Software Engineering with Python, 271–98. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003143482-12.

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Sherer, Susan A. "Software Testing." In Software Failure Risk, 195–208. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3020-6_9.

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Houston, Susan M. "Software Testing." In The Project Manager's Guide to Health Information Technology Implementation, 133–42. 3rd ed. New York: Productivity Press, 2021. http://dx.doi.org/10.4324/9781003206668-11.

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Jorgensen, Paul C., and Byron DeVries. "Software Complexity." In Software Testing, 353–72. 5th ed. Boca Raton: Auerbach Publications, 2021. http://dx.doi.org/10.1201/9781003168447-18.

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Jorgensen, Paul C., and Byron DeVries. "System Testing." In Software Testing, 291–336. 5th ed. Boca Raton: Auerbach Publications, 2021. http://dx.doi.org/10.1201/9781003168447-16.

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Conference papers on the topic "Software testing"

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Sardana, Mihir, Tanupriya Choudhury, and Dev Kumar Chaudhary. "Extensive review on software testing and pipeline testing softwares." In 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC). IEEE, 2017. http://dx.doi.org/10.1109/icbdaci.2017.8070842.

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Cheatham, Thomas J., Jungsoon P. Yoo, and Nancy J. Wahl. "Software testing." In the 1995 ACM 23rd annual conference. New York, New York, USA: ACM Press, 1995. http://dx.doi.org/10.1145/259526.259548.

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Mudholkar, Pankaj, Megha Mudholkar, and Snehal Kulkarni. "Software testing." In ICWET '10: International Conference and Workshop on Emerging Trends in Technology. New York, NY, USA: ACM, 2010. http://dx.doi.org/10.1145/1741906.1742242.

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Carrington, David. "Teaching software testing." In the second Australasian conference. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/299359.299369.

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Palanque, Philippe, Regina Bernhaupt, Ronald Boring, and Chris Johnson. "Testing Interactive Software." In CHI '06 extended abstracts. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1125451.1189335.

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Harrold, Mary Jean. "Testing evolving software." In the 1st conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1342211.1342213.

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"Testing reusable software." In the conference, chair Gregory M. Bowen. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/143557.143744.

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Iskrenovic-Momcilovic, Olivera, and Aca Micic. "Mechatronic Software Testing." In 2007 8th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services. IEEE, 2007. http://dx.doi.org/10.1109/telsks.2007.4376049.

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Kishore, Sheel, Satjeet S. Khalsa, Eric R. Feingold, Sridhar B. Seshadri, and Ronald L. Arenson. "PACS software testing." In Medical Imaging VI, edited by Yongmin Kim. SPIE, 1992. http://dx.doi.org/10.1117/12.59492.

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Edwards, Stephen H. "Teaching software testing." In Companion of the 18th annual ACM SIGPLAN conference. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/949344.949431.

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Reports on the topic "Software testing"

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Shimeall, Timothy J., and Stephen C. Shimeall. Iterative Software Testing. Fort Belvoir, VA: Defense Technical Information Center, June 1992. http://dx.doi.org/10.21236/ada255953.

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Thompson, Kelly Glen. Software Testing - Auditing Software Quality Assurance Plans. Office of Scientific and Technical Information (OSTI), June 2017. http://dx.doi.org/10.2172/1364571.

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3

Ferenbaugh, Charles. Software Testing – An Overview. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1853915.

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4

Dean, Lon R. Software Tech News. Software Testing Series: Part 1,. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada367570.

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McGregor, John D. Testing a Software Product Line. Fort Belvoir, VA: Defense Technical Information Center, December 2001. http://dx.doi.org/10.21236/ada401736.

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6

Ruggiero, Christy E., and Reid B. Porter. Mama Software Features: Uncertainty Testing. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1133766.

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7

Hoover, Alex. Software Change and Regression Testing. Fort Belvoir, VA: Defense Technical Information Center, November 2001. http://dx.doi.org/10.21236/ada405771.

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8

Black, Paul E., Paul Ammann, and Wei Ding. Model checkers in software testing. Gaithersburg, MD: National Institute of Standards and Technology, 2002. http://dx.doi.org/10.6028/nist.ir.6777.

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9

Gavrila, Serban I., and Elizabeth Fong. Forensic software testing support tools :. Gaithersburg, MD: National Institute of Standards and Technology, 2004. http://dx.doi.org/10.6028/nist.ir.7103a.

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10

Banks, David, William Dashiell, Leonard Gallagher, Charles Hagwood, Raghu Kacker, and Lynne Rosenthal. Software testing by statistical methods:. Gaithersburg, MD: National Institute of Standards and Technology, 1998. http://dx.doi.org/10.6028/nist.ir.6129.

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