Crowdsourced software testing (CST) uses a crowd of testers to conduct software testing. Currently, the microtasking model is used in CST; in it, a testing task is sent to individual testers who work separately from each other. Several studies mentioned that the quality of test reports produced by individuals was a drawback because a large number of invalid defects were submitted. Additionally, individual workers tended to catch the simple defects, not those with high complexity. This research explored the effect of having pairs of collaborating testers working together to produce one final test report. We conducted an experiment with 75 workers to measure the effect of this approach in terms of (1) the total number of unique valid defects detected, (2) the total number of invalid defects reported, and (3) the possibility of detecting more difficult defects. The findings show that testers who worked in collaborating pairs can be as effective in detecting defects as an individual worker; the differences between them are marginal. However, CST significantly affects the quality of test reports submitted in two dimensions: it helps reduce the number of invalid defects and also helps detect more difficult defects. The findings are promising and suggest that CST platforms can benefit from new mechanisms that allow for the formation of teams of two individuals who can participate in doing testing jobs.

Some typical latest research results were summarized according to the analysis and research on the current situation of software testing both at home and abroad in this paper. On the basis of the current researches on software testing, the writer discussed the future research topic on software testing and proposed the assumption on software testing’s subject, industry and technique development. It laid the foundation both for further boosting the development and formation of software testing discipline system and for effectively studying on the scientific development mechanism of software testing techniques and its industry. Keywords-software engineering; software quality; software testing; automated testing; research orientation.

Software testing is a crucial part of software development, it ensures that the software been developed performs all functional requirements and is free from any form of defect and errors. This ensures that the software is of good quality and standard. While testing a software, it is important to be time and cost consciousness. This reason has made most testers switch from the manual testing process to automation of software testing, to reduce time and cost. But then selecting a software testing tool for automated testing that best fit a project is important yet challenging task, the objective of this paper is to evaluate some of the most used software testing tool, identify their strength and weakness and also the field where they can be employed, either for mobile testing, web service testing or both. The method utilized in the paper involved the analysis of recommended literatures to pinpoint necessary testing tools selected based on inclusion and exclusion criteria, that were evaluated. The result of the analysis indicted that based on the selected criteria, testing tools that supports web platform testing made up 17%, while tools that supported desktop and mobile platforms was 10% and 7% respectively. also, 7% of the tools examined were found to be open source tools while 12% were licensed tools. 10% of the testing tools examined supported the test result and report generation criterion while tools that require the knowledge of programming language was least as only 3% of examined tools supported this criterion. It was observed that there is no one perfect tool for testing, but for a particular testing purpose, tradeoffs can be made to select the best tool depending on the size of the project, the budgeted cost for testing, the platform of the application and also the language that is used to develop the project.

Abstract High reliability, safety and professional software quality are compelling requirement to software applied in civil aviation field. In this article, the status and characteristic of software testing in civil aviation field are summarized and analyzed. On the basis of analysis to the personal system of tester, testing environment and guaranty system of software testing, some constructive suggestions are presented for building up the integrated and efficient software testing system.

Software Testing is the core part of computer science & engineering curriculum. It has been observed that software testing has been taught much in Computer science & engineering disciplines at undergraduate level. Software Testing Education (STE) involves time, cost, risk, quality, integration, communication, human resource, and procurement management skills. The STE at undergraduate and graduate level is a challenging task because it also requires knowledge and experience. This article aims to investigate and synthesize the state-of-the-art research in STE for the improvement of STE curriculum, pedagogical tools and techniques, cognitive, empirical and assessments methods. STE research approaches has been categorized into five categories including empirical type, research approaches, software testing education processes, key areas, and curricula. The ninety-seven articles for the area of STE have been chosen after rigorous systematic screening process published in during 2004 to 2021. Furthermore, tools and techniques, testing processes, pedagogy and student performance are the frequently addressed in STE; whereas assessment methods, gamification, curriculum and exemplary program development appeared as mostly ignored areas. Lastly, research gaps and challenges relate to STE has been presented as future directions for the faculty, software industry, and researchers.

The final product of software development process is a software system and testing is one of the important stages in this process. The success of this process can be determined by how well it accomplishes its goal. Due to the advancement of technology, various software testing tools have been introduced in the software engineering discipline. The use of software is increasing day-by-day and complexity of software functions are challenging and there is need to release the software within the short quality evaluation period, there is a high demand in adopting automation in software testing. Emergence of automatic software testing tools and techniques helps in quality enhancement and reducing time and cost in the software development activity. Artificial Intelligence (AI) techniques are widely applied in different areas of Software engineering (SE). Application of AI techniques can help in achieving good performance in software Testing and increase the productivity of the software development firms. This paper briefly presents the state of the art in the field of software testing by applying AI techniques in software testing.

The number of applications being built and deployed everyday are increasing by leaps and bounds. To ensure the best user/client experience, the application needs to be free of bugs and other service issues. This marks the importance of testing phase in application development and deployment phase. Basically, testing is dissected into couple of parts being Manual Testing and Automation Testing. Manual testing, which is usually, an individual tester is given software guidance to execute. The tester would post the findings as “passed” or “failed” as per the guidance. But this kind of testing is very costly and time taking process. To eliminate these short comings, automation testing was introduced but it had very little scope and applications are limited. Now, that Artificial Intelligence has been foraying into many domains and has been showing significant impact over those domains. The core principles of Natural Language Processing that can be used in Software Testing are discussed in this paper. It also provides a glimpse at how Natural Language Processing and Software Testing will evolve in the future. Here we focus mainly on test case prioritization, predicting manual test case failure and generation of test cases from requirements utilizing NLP. The research indicates that NLP will improve software testing outcomes, and NLP-based testing will usher in a coming age of software testers work in the not-too-distant times.

Software testing plays a significant role in various software development phases. There are so many software testing techniques available. Selecting the most suitable software testing technique based on multiple factors is challenging for software practitioners. This paper proposes an MCDM-based hybrid approach for selecting the most appropriate software testing technique among various available software testing techniques, considering multiple factors such as cost, schedule, resources, etc. Because of the involvement of multiple factors, the problem of selecting the most appropriate software testing technique can be modeled as an MCDM problem. This study proposes a hybrid approach by integrating two MCDM methods BWM (Best-Worst Method) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), for evaluating various software testing techniques considering multiple factors altogether. For the applicability of the proposed approach, an experimental study was conducted using seven software testing techniques and six evaluation criteria. Results show the proposed approach can be used as an efficient tool for selecting the most suitable software testing technique among various available testing techniques in the presence of multiple factors.

Software testing is the process of running an application with the intent of finding software bugs (errors or other defects). Software applications demand has pushed the quality assurance of developed software towards new heights. It has been considered as the most critical stage of the software development life cycle. Testing can analyze the software item to identify the disparity between actual and prescribed conditions and to assess the characteristics of the software. Software testing leads to minimizing errors and cut down software costs. For this purpose, we discuss various software testing techniques and strategies. This paper aims to study diverse as well as improved software testing techniques for better quality assurance purposes.

Project management has long been a challenge for Information Technology (IT) organizations to learn how to manage projects effectively and efficiently while balancing the iron triangle: cost, time and scope without sacrificing quality. Agile project management (APM) and traditional project management (TPM) are two different approaches related to software development, the core tenet of TPM is that projects are relatively simple, predictable, and linear with well-defined boundaries, whereas APM has emerged as a new methodology for managing high-risk, time-sensitive and scope flexible projects. While it is undeniable that the use of agile project management is increasing, the traditional opposite side continues to exist. The agile approach has an impact on all phases of software development, and they must adapt to this new way of thinking. Software testing is also impacted as a fundamental link in the software development life cycle that ensures quality. Software testing is a vital component of software Quality Assurance (QA) since it serves as the final review of the specification, design, and code. Has software testing evolved along with the evolution of project management? Is there a difference between a traditional and an agile software testing? This paper answers these questions by comparing software testing in the two approaches.