Related papers: Fault Predictions in Object Oriented Software
The presence of software vulnerabilities is an ever-growing issue in software development. In most cases, it is desirable to detect vulnerabilities as early as possible, preferably in a just-in-time manner, when the vulnerable piece is…
Predicting issue lifetime can help software developers, managers, and stakeholders effectively prioritize work, allocate development resources, and better understand project timelines. Progress had been made on this prediction problem, but…
We study the problem of scheduling jobs on fault-prone machines communicating via a shared channel, also known as multiple-access channel. We have $n$ arbitrary length jobs to be scheduled on $m$ identical machines, $f$ of which are prone…
Building defect prediction models based on online learning can enhance prediction accuracy. It continuously rebuilds a new prediction model when adding a new data point. However, predicting a module as "non-defective" (i.e., negative…
Software reliability models are an important tool in quality management and release planning. There is a large number of different models that often exhibit strengths in different areas. This paper proposes a model that is based on a…
Fixing software faults contributes significantly to the cost of software maintenance and evolution. Techniques for reducing these costs require datasets of software faults, as well as an understanding of the faults, for optimal testing and…
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…
Modern programming languages (e.g., Java and C#) provide features to separate error-handling code from regular code, seeking to enhance software comprehensibility and maintainability. Nevertheless, the way exception handling (EH) code is…
In modern industrial systems, machinery frequently operates under dynamic environments with continuously varying loads and speeds. Consequently, deep learning-based fault diagnosis models often suffer from severe performance degradation…
Traditionally, research in Business Process Management has put a strong focus on centralized and intra-organizational processes. However, today's business processes are increasingly distributed, deviating from a centralized layout, and…
When optimizing problems with uncertain parameter values in a linear objective, decision-focused learning enables end-to-end learning of these values. We are interested in a stochastic scheduling problem, in which processing times are…
Fault based testing is a technique in which test cases are chosen to reveal certain classes of faults. At present, testing professionals use their personal experience to select testing methods for fault classes considered the most likely to…
Major software failures are reported to be due to misconfiguration. As manual configuration is too error-prone to be deemed a reliable strategy for dynamic and complex systems, automated configuration management has become a standard.…
Software defect prediction plays a crucial role in estimating the most defect-prone components of software, and a large number of studies have pursued improving prediction accuracy within a project or across projects. However, the rules for…
In this paper, we consider a problem of failure prediction in the context of predictive maintenance applications. We present a new approach for rare failures prediction, based on a general methodology, which takes into account peculiar…
Recently Java programming environment has become so popular. Java programming language is a language that is designed to be portable enough to be executed in wide range of computers ranging from cell phones to supercomputers. Computer…
Just-in-time defect prediction (JIT-DP) aims to predict the likelihood of code changes resulting in software defects at an early stage. Although code change metrics and semantic features have enhanced prediction accuracy, prior research has…
During testing, developers can place oracles externally or internally with respect to a method. Given a faulty execution state, i.e., one that differs from the expected one, an oracle might be unable to expose the fault if it is placed at a…
Over the past few years, deep learning methods have been applied for a wide range of Software Engineering (SE) tasks, including in particular for the important task of automatically predicting and localizing faults in software. With the…
Fault identification and testing has always been the most specific concern in the field of software development. To identify and testify the bug we should be aware of the source of the failure or any unwanted issue. In this paper, we are…