相关论文: Test Case Prioritization Techniques for Model-Base…
Test Case Prioritization (TCP) is an important component of regression testing, allowing for earlier detection of faults or helping to reduce testing time and cost. While several TCP approaches exist in the research literature, a growing…
Test Case Prioritization (TCP) is an increasingly important regression testing technique for reordering test cases according to a pre-defined goal, particularly as agile practices gain adoption. To better understand these techniques, we…
Test case prioritisation (TCP) is a critical task in regression testing to ensure quality as software evolves. Machine learning has become a common way to achieve it. In particular, learning-to-rank (LTR) algorithms provide an effective…
Test Case Prioritization (TCP) techniques aim at proposing new test case execution orders to favor the achievement of certain testing goal, such as fault detection. Current TCP research focus mainly on code-based regression testing; however…
Context: During the development process of a software program, regression testing is used to ensure that the correct behavior of the software is retained after updates to the source code. This regression testing becomes costly over time as…
Context: Test case prioritization (TCP) is a technique widely used by software development organizations to accelerate regression testing. Objectives: We aim to systematize existing TCP knowledge and to propose and empirically evaluate a…
Continuous Integration (CI) requires efficient regression testing to ensure software quality without significantly delaying its CI builds. This warrants the need for techniques to reduce regression testing time, such as Test Case…
Regression testing of software is a crucial but time-consuming task, especially in the context of user interface (UI) testing where multiple microservices must be validated simultaneously. Test case prioritization (TCP) is a cost-efficient…
Regression testing in Continuous Integration (CI) pipelines is increasingly costly due to the growing size and execution frequency of test suites. Test Case Prioritization (TCP) mitigates this problem by reordering tests to expose faults…
Regression testing activities greatly reduce the risk of faulty software release. However, the size of the test suites grows throughout the development process, resulting in time-consuming execution of the test suite and delayed feedback to…
Most software companies have extensive test suites and re-run parts of them continuously to ensure recent changes have no adverse effects. Since test suites are costly to execute, industry needs methods for test case prioritisation (TCP).…
In the realm of software development, testing is crucial for ensuring software quality and adherence to requirements. However, it can be time-consuming and resource-intensive, especially when dealing with large and complex software systems.…
Regression testing assures software correctness after changes but is resource-intensive. Test Case Prioritisation (TCP) mitigates this by ordering tests to maximise early fault detection. Diversity-based TCP prioritises dissimilar tests,…
Understanding queuing dynamics of TCP is important for correct router buffer sizing as well as for optimizing the performance of the TCP protocol itself. However, modeling of buffer content dynamics under TCP has received relatively little…
Regression testing is an essential activity to assure that software code changes do not adversely affect existing functionalities. With the wide adoption of Continuous Integration (CI) in software projects, which increases the frequency of…
Assessing reliably the confidence of a deep neural network and predicting its failures is of primary importance for the practical deployment of these models. In this paper, we propose a new target criterion for model confidence,…
To alleviate the cost of regression testing in continuous integration (CI), a large number of machine learning-based (ML-based) test case prioritization techniques have been proposed. However, it is yet unknown how they perform under the…
There is a growing body of research indicating the potential of machine learning to tackle complex software testing challenges. One such challenge pertains to continuous integration testing, which is highly time-constrained, and generates a…
Many cloud systems utilize low-priority flows to achieve various performance objectives (e.g., low latency, high utilization), relying on TCP as their preferred transport protocol. However, the suitability of TCP for such low-priority flows…
Over the last years, machine learning techniques have been applied to more and more application domains, including software engineering and, especially, software quality assurance. Important application domains have been, e.g., software…