Related papers: An Exploratory Study on Regression Vulnerabilities
Software vulnerabilities remain a significant risk factor in achieving security objectives within software development organizations. This is especially true where either proprietary or open-source software (OSS) is included in the…
New model of software safety is offered. Distribution of mistakes in program on stages of life cycle is researched. Study of ways of increase of reliability of software at help simulation program is leaded.
One of the biggest expense in software development is the maintenance. Therefore, it is critical to comprehend what triggers maintenance and if it may be predicted. Numerous research have demonstrated that specific methods of assessing the…
Performance is a critical quality attribute in software development, yet the impact of method-level code changes on performance evolution remains poorly understood. While developers often make intuitive assumptions about which types of…
Public development processes are a key characteristic of open source projects. However, fixes for vulnerabilities are usually discussed privately among a small group of trusted maintainers, and integrated without prior public involvement.…
As software is evolving, code changes can introduce regression bugs or affect the behavior in other unintended ways. Traditional regression test generation is impractical for detecting unintended behavioral changes, because it reports all…
Replay and rollback attacks threaten cloud application integrity by reintroducing authentic yet stale data through an untrusted storage interface to compromise application decision-making. Prior security frameworks mitigate these attacks by…
The year 2022 saw a significant increase in Microsoft vulnerabilities, reaching an all-time high in the past decade. With new vulnerabilities constantly emerging, there is an urgent need for proactive approaches to harden systems and…
The Department of Homeland Security in the United States estimates that 90% of software vulnerabilities can be traced back to defects in design and software coding. The financial impact of these vulnerabilities has been shown to exceed 380…
We introduce a simple microscopic description of software bug dynamics where users, programmers and a maintainer interact through a given program, with a particular emphasis on bug creation, detection and fixing. When the program is written…
Aim: In contrast to studies of defects found during code review, we aim to clarify whether code reviews measures can explain the prevalence of post-release defects. Method: We replicate a study by McIntoshet. al that uses additive…
The regression test selection problem--selecting a subset of a test-suite given a change--has been studied widely over the past two decades. However, the problem has seen little attention when constrained to high-criticality developments…
Open-source software (OSS) vulnerabilities are increasingly prevalent, emphasizing the importance of security patches. However, in widely used security platforms like NVD, a substantial number of CVE records still lack trace links to…
Users around the world rely on software-intensive systems in their day-to-day activities. These systems regularly contain bugs and security vulnerabilities. To facilitate bug fixing, data-driven models of automatic program repair use pairs…
Large language models (LLMs) are increasingly prevalent in security research. Their unique characteristics, however, introduce challenges that undermine established paradigms of reproducibility, rigor, and evaluation. Prior work has…
Software vulnerabilities bear enterprises significant costs. Despite extensive efforts in research and development of software vulnerability detection methods, uncaught vulnerabilities continue to put software owners and users at risk. Many…
As a software system evolves, its architecture tends to degrade, and gradually impedes software maintenance and evolution activities and negatively impacts the quality attributes of the system. The main root cause behind architecture…
Machine-learning models demand periodic updates to improve their average accuracy, exploiting novel architectures and additional data. However, a newly updated model may commit mistakes the previous model did not make. Such…
Many safety failures in machine learning arise when models are used to assign predictions to people (often in settings like lending, hiring, or content moderation) without accounting for how individuals can change their inputs. In this…
Developers build all the software artifacts in development. Existing work has studied the social behavior in software repositories. In one of the most important software repositories, a bug repository, developers create and update bug…