Related papers: The landscape of software failure cause models
An overview and classification of software testing models are done. Recommendations on the choice of models are proposed
Software testing is essential for the reliable development of complex software systems. A key step in software testing is fault localization, which uses test data to pinpoint failure-inducing combinations for further diagnosis. Existing…
I/O efficiency is crucial to productivity in scientific computing, but the increasing complexity of the system and the applications makes it difficult for practitioners to understand and optimize I/O behavior at scale. Data-driven machine…
Context: Software testing plays an essential role in product quality improvement. For this reason, several software testing models have been developed to support organizations. However, adoption of testing process models inside…
Today, software systems have a significant role in various domains among which are healthcare, entertainment, transport and logistics, and many more. It is only natural that with this increasing dependency on software, the number of…
Machine learning has become prevalent across a wide variety of applications. Unfortunately, machine learning has also shown to be susceptible to deception, leading to errors, and even fatal failures. This circumstance calls into question…
Large language models (LLMs) are being rapidly integrated into decision-support tools, automation workflows, and AI-enabled software systems. However, their behavior in production environments remains poorly understood, and their failure…
Defects4J has enabled numerous software testing and debugging research work since its introduction. A large part of its contribution, and the resulting popularity, lies in the clear separation and distillation of the root cause of each…
The dynamic software development organizations optimize the usage of resources to deliver the products in the specified time with the fulfilled requirements. This requires prevention or repairing of the faults as quick as possible. In this…
Defect prediction can be a powerful tool to guide the use of quality assurance resources. However, while lots of research covered methods for defect prediction as well as methodological aspects of defect prediction research, the actual cost…
Defect prediction is one of the most popular research topics due to its potential to minimize software quality assurance efforts. Existing approaches have examined defect prediction from various perspectives such as complexity and developer…
While the methodological rigor of computing research has improved considerably in the past two decades, quantitative software engineering research is hampered by immature measures and inattention to theory. Measurement-the principled…
In a critical software system, the testers have to spend an enormous amount of time and effort to maintain the software due to the continuous occurrence of defects. Among such defects, some severe defects may adversely affect the software.…
We aim to conduct a systematic mapping in the area of testing ML programs. We identify, analyze and classify the existing literature to provide an overview of the area. We followed well-established guidelines of systematic mapping to…
Model-driven engineering (MDE) is believed to have a significant impact in software quality. However, researchers and practitioners may have a hard time locating consolidated evidence on this impact, as the available information is…
Due to its enormous benefits, the research and industry communities have shown an increasing interest in the Microservices Architecture (MSA) style over the last few years. Despite this, there is a limited evidence-based and thorough…
Context: Software start-ups are emerging as suppliers of innovation and software-intensive products. However, traditional software engineering practices are not evaluated in the context, nor adopted to goals and challenges of start-ups. As…
Fault Tree analysis is a widely used failure analysis methodology to assess a system in terms of safety or reliability in many industrial application domains. However, with Fault Tree methodology there is no possibility to express a…
Forming a reliable judgement of a machine learning (ML) model's appropriateness for an application ecosystem is critical for its responsible use, and requires considering a broad range of factors including harms, benefits, and…
The quality and correct functioning of software components embedded in electronic systems are of utmost concern especially for safety and mission-critical systems. Model-based testing and formal verification techniques can be employed to…