The central role of test automation in software quality assurance

Challenges and Improvements, 2011

The objective of this industry study was to shed light on the current situation and improvement needs in software test automation. To this end, 55 industry specialists from 31 organizational units were interviewed. In parallel with the survey, a qualitative study was conducted in 12 selected software development organizations. The results indicated that the software testing processes usually follow systematic methods to a large degree, and have only little immediate or critical requirements for resources. Based on the results, the testing processes have approximately three fourths of the resources they need, and have access to a limited, but usually sufficient group of testing tools. As for the test automation, the situation is not as straightforward: based on our study, the applicability of test automation is still limited and its adaptation to testing contains practical difficulties in usability. In this study, we analyze and discuss these limitations and difficulties.

International Journal of Computer Applications, 2011

Software plays an important role in complex systems, especially for complex applications such as Video surveillance application, transportation, financial management, communication, biomedical applications and so on. For these systems, tester needs to concentrate on performances such as efficient operation, fault tolerance, safety and security. The basic problem is the complexity of the task, which has to be performed on a software application. Unlike hardware, software cannot break or wear out, but can fail during its life cycle .Software problems, essentially, have to be solved with quality assurance tools such as testing procedures, quality data reporting. In this context, the paper proposes a new approach to automate software testing process to cover maximum test plan time and also to increase software quality. In this paper a method explained to cover each module without missing any test scenario and guarantees software with high quality and decrease testing life cycle time by establishing automation life cycle to develop scripts.

TJPRC, 2014

The growing importance of Software in the present scenario can be attributed to the fact that software is utilized in several different ways for different issues to provide different types of solutions. The subject of Software Engineering is so vast and varied that it encompasses several areas such as manufacturing of Refrigerators, Air Conditioning Systems, Automobiles, Space Engineering, Wireless and Mobile Communications. Therefore, in most cases, software usually need to adhere to a specifications so that they can perform to produce only those results that are expected and enunciated. In general, keeping in view of the present scenario, a software professional goes through a certain process to establish that the software conforms to a given specification. This process, verification and validation (V & V), ensures that the software conforms to its specification and that the customers ultimately receive what they ordered. Software testing is one of the techniques to use during V & V. To be able to use resources in a better way, computers should be able to help out in the “art of software testing” to a higher extent, than is currently the case today. The main issue is to not retrench human resources from the process of software testing itself altogether but to consider the fact that software engineering is an art and science of identifying suitable solutions to critical problems by not just involving computers alone to solve the testing issues but software engineers should themselves participate and come out with better and suitable solutions to those problems where computers are clearly not that good to provide appropriate solutions. This research work presents a systematic and methodical approach aimed at examining, classifying and improving the concept of automated software testing and is built upon the assumption that software testing could be automated to a higher extent. Throughout this thesis an emphasis has been put on “real life” applications and the testing of these applications. One of the contributions in this thesis is the research aimed at uncovering different issues with respect to automated software testing. The research is performed through a series of case studies and experiments which ultimately also leads to another contribution—a model for expressing, clarifying and classifying software testing and the automated aspects thereof. An additional contribution in this thesis is the development of framework which in turns acts as a broad substratum for a framework for object message pattern analysis of intermediate code representations. This is achieved keeping in view of the procedures relating to code optimization and effective code generation at all levels. 260 Chittineni Aruna & R. Siva Ram Prasad Impact Factor (JCC): 6.8785 Index Copernicus Value (ICV): 3.0 The results that are expected in this thesis indicate how software testing can be improved, extended and better classified with respect to automation aspects. The main contribution lays in the investigations and the improvements related issues with regard to automated software testing. A comprehensive study has been made by the researchers to tackle the very crust of the problem of software testing methodologies. It has to be noted that testing software in an automated way has been a goal for researchers and industry during the last few decades. Nevertheless, the success rate has not been readily available. Some tools that are partly automated have evolved, while at the same time the methodologies for testing software has improved, thus leading to an overall improvement. Even today, much of the software testing procedures are performed manually which is not reliable, prone to errors, inefficient and also a costly affair. Even today several questions still remain unanswered. For instance, we have the question of when and how to stop the process of testing software when is it not economically feasible to continue to test software? It is very much evident that investing so much of time and money for testing an application which will be used only for a few times, in a non-critical environment, is probably a waste of resources.[1] At the same time, when software engineers develop software that will be placed in a critical domain and extensively used, an answer to that question needs to be found. Secondly, there is the problem of resources. It is to be noted that small- and medium-sized companies are today, as always, challenged by their resources, or to be more precise, the lack thereof. Deadlines must be kept at all costs even when, in some cases, the cost turns out to be the actual reliability of their products. In addition to the growing complexity of software, the size of the problem becomes more and more complex and huge. Keeping in view of the question of complexity and to be more precise based on the fact that software has grown in complexity and size which have become very much part of the problem of software testing and the type of research work that needs to be done to improvise on these issues is to be given a methodical and systematic approach.

International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), 2023

As the domain of software development continues to progress in terms of intricacy and magnitude, the integration of automated testing has become a vital element in ensuring the excellence and dependability of software. The implementation of automated testing frameworks assumes a pivotal role in streamlining the testing procedure; nevertheless, the selection of the appropriate framework category presents challenges and necessitates making prudent compromises. This academic paper presents a comprehensive exploration of automated testing frameworks, exhaustively investigating their diverse categories, attributes, and the associated compromises that emerge from their adoption. The paper initiates with a comprehensive examination of the literature, encompassing a concise overview of the current research and industry patterns regarding test automation frameworks. Following this, it presents an intricate evaluation of various types of frameworks, such as keyword-driven, data-driven, and behavior-driven frameworks, clarifying their individual principles and functionalities. One of the main topics explored in this paper concerns the factors that influence the choice of a particular type of test automation framework. By presenting a framework for decision-making, we offer guidance to professionals and organizations in making informed decisions that align with their project requirements, team expertise, and testing goals. Furthermore, this paper critically evaluates the trade-offs and challenges associated with each type of framework, addressing concerns related to different aspects of the framework. To assist professionals and decision-makers, we conclude by providing best practices and recommendations for effectively implementing and managing test automation frameworks. Moreover, we investigate the perspective of test automation frameworks, accentuating emerging patterns and contemplating the consequences of developing technologies like artificial intelligence and machine learning. In summary, this paper presents a comprehensive guide to the different types and trade-offs of test automation frameworks, equipping software professionals with the knowledge and insights necessary to make well-informed decisions and enhance the efficiency and effectiveness of their testing processes.

2002

in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering. The thesis is equivalent to 10 weeks of full time studies.

Electronic Notes in Theoretical Computer Science, 2006

The development of large software systems is a complex and error prone process. Faults might occur at any development stage and they must be identified and removed as early as possible to stop their propagation and reduce verification costs. Quality engineers must be involved in the development process since the very early phases to identify required qualities and estimate their impact on the development process. Their tasks span over the whole development cycle and go beyond the product deployment through maintenance and post mortem analysis. Developing and enacting an effective quality process is not a simple task, but it requires that we integrate many quality-related activities with product characteristics, process organization, available resources and skills, and budget constraints. This paper discusses the main characteristics of a good quality process, then surveys the key testing phases and presents modern functional and model-based testing approaches.

Testing is a necessary, but sometimes tedious chore for finding faults in software. Finding faults is essential for ensuring quality and reliability of software for industry. These are valuable traits consumers consider when investing capital and therefore essential to the reputation and financial well-being of a business. This research involves an ongoing trade-off between time and computational resources when testing via random selection of test cases versus complex logical means to find faults. More time will be devoted to an analysis of random test case selection and whether the amount of extra test cases run due to random selection is a viable alternative to the potential time spent fully evaluating the logic for coverage of a generic predicate. The reader will gain knowledge about the expectations for the increase in test cases if randomized selection is employed at some point in the process of testing.

2010

Abstract The main goal of the seminar``Practical Software Testing: Tool Automation and Human Factors''was to bring together academics working on algorithms, methods, and techniques for practical software testing, with practitioners, interested in developing more soundly-based and well-understood testing processes and practices. The seminar's purpose was to make researchers aware of industry's problems, and practitioners aware of research approaches.

Abstract—with increasingly high demands of quality software in every field of life and decreasingly time schedules for the delivery of software products, old manual testing techniques are causing software organizations to lag behind in the competition. Automated testing is the alternate. Test automation software suits are being worked upon and maintained by the software engineers in modern software organizations. But even they are not the best for the purpose. A software needs periodic up gradation, fixing of reported bugs and going through regression testing. Developing a new software with similar features is a similar case. In both these cases same testing software scripts won’t work and they need changes to adapt to test new software features. This could be time consuming and error prone, as those small changes may create bugs in the testing software suit itself, hence a costly and risky activity. This problem is becoming so dominant that software engineering field has come up with yet another solution and that is Test Automation with Artificial Intelligence. Software testing is mere repetition of test cases with small changes. These small changes have built in patterns that are repeated from a test case to a test case. So, why not make testing software self-learning? With AI built in, testing software can recognize and save those repeating patterns, learn from them, detect small changes in the software, change the test cases accordingly, apply them and output the result. And it does that without human intervention which makes it far less error prone than when it was in the hands of human. These qualities will make AI software test automation the future of software testing; an economical and risk free activity. In this review paper I have tried to mention the problems which have been reported in the testing automation in case of classical techniques and how AI techniques improves testing automation.

2006

Quality assurance, and in particular software testing and verification, are areas that yet have much to offer to the industry. Companies that develop software need to improve their skills in this area to get the best return on investments. Important future strategies for survival are to collaborate with academia to find solutions to several difficult problems within software testing. Some of the areas and experiences in software testing that needs to be improved from an industry perspective is discussed, like test automation and component test. We have created a way to improve designers testing, which we call software quality rank. This ranking system takes known research results, including knowledge and tools from static-and run-time analysis and making them work in industry. The software quality rank aims to improve testing on the component level. We have saved a lot of money by improving the test area, and we share some of the lessons learned to aid other businesses with the same endeavor.