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Empirical studies have shown that most software interaction faults involve one or two variables interacting, with progressively fewer triggered by three to six variables interacting. This paper introduces a model for the origin of this distribution. We start with two empirically reasonable assumptions regarding the distribution of branch conditions in code and the proportion of t-way combinations...
Stochastic simulations are developed and employed across many fields, to advise governmental policy decisions and direct future research. Faulty simulation software can have serious consequences, but its correctness is difficult to determine due to complexity and random behaviour. Stochastic simulations may output a different result each time they are run, whereas most testing techniques are designed...
Software project artifacts such as source code, requirements, and change logs represent a gold-mine of actionable information. As a result, software analytic solutions have been developed to mine repositories and answer questions such as "who is the expert?,'' "which classes are fault prone?,'' or even "who are the domain experts for these fault-prone classes?'' Analytics often require...
Methods for predicting issue lifetime can help software project managers to prioritize issues and allocate resources accordingly. Previous studies on issue lifetime prediction have focused on models built from static features, meaning features calculated at one snapshot of the issue's lifetime based on data associated to the issue itself. However, during its lifetime, an issue typically receives comments...
In software project management, software development effort estimation (SDEE) is one of the critical activities. Analogy-Based Estimation (ABE) is most popular estimation technique suggested in SDEE literature [1, 7, 22]. Researchers have proposed various methods to improve the accuracy of ABE by adjusting the retrieved solution. The research suggests all published calibration methods depend on linear...
Fixing some security failures are difficult because they cannot be easily reproduced. To address Hardly Reproducible Vulnerabilities (HRVs), security experts spend a significant amount of time, effort, and budget. Sometimes they do not succeed in the reproduction step and ignore some security failures. The exploitation of a vulnerability due to its irreproducibility may cause severe consequences....
In project management, project plan is made based on the prediction results of the project. Predicting the number of defects is one of important prediction. To enhance the prediction accuracy of the number of defects, many studies proposed various prediction models. The model is built using a dataset collected in past projects, and the number of defects is predicted using the model and the data of...
Once a software project has been developed and delivered, any modification to it corresponds to maintenance. Software maintenance (SM) involves modifications to keep a software project usable in a changed or a changing environment, reactive modifications to correct discovered faults, and modifications to improve performance or maintainability. Since the duration of SM should be predicted, in this...
Missing Data (MD) is a widespread problem that can affect the ability to use data to construct effective software development effort prediction systems. This paper investigates the use of missing data (MD) techniques with Fuzzy Analogy. More specifically, this study analyze the predictive performance of this analogy-based technique when using toleration, deletion or k-nearest neighbors (KNN) imputation...
Defect prediction on unlabeled datasets is one of the most active research areas in software engineering. Generally, cross-project defect prediction (CPDP) and unsupervised learning defect prediction are utilized to address this problem. The fundamental idea of CPDP is the transfer learning that reuses the prediction model built by labeled source projects. However, because of the difference of data...
Gaussian process fitting, or kriging, is often used to create a model from a set of data. Many available software packages do this, but we show that very different results can be obtained from different packages even when using the same data and model. Seven different fitting packages that run on four different platforms are compared using various data functions and data sets that reveal there are...
The paper first discusses the importance of discrete event simulation (DES) in the business school curriculum. It next notes how small Macintosh lap tops have become increasingly popular among business students. We next discuss what DES software is available on the Mac, first directly, then indirectly by running DES software for Windows in some way on the Mac. Noting that there is not much simple...
Software effort estimation influences almost all the process of software development such as: bidding, planning, and budgeting. Hence, delivering an accurate estimation in early stages of the software life cycle may be the key of success of any project. To this aim, many solo techniques have been proposed to predict the effort required to develop a software system. Nevertheless, none of them proved...
The paper presents application of STATISTICA v6.0 and STATISTICA NEURAL NETWORKS software for electrical load forecasting. Relevance of forecasting is influenced by the fact that extraction of minerals in oil and gas industry is increasing. As oil extraction and transportation is very power intensive, the problem of load growth has arisen. Then, a task for forecasting of load growth occurs. The results...
Recent years have seen a proliferation of complex Advanced Driver Assistance Systems (ADAS), in particular, for use in autonomous cars. These systems consist of sensors and cameras as well as image processing and decision support software components. They are meant to help drivers by providing proper warnings or by preventing dangerous situations. In this paper, we focus on the problem of design time...
“Transfer learning”: is the process of translating quality predictors learned in one data set to another. Transfer learning has been the subject of much recent research. In practice, that research means changing models all the time as transfer learners continually exchange new models to the current project. This paper offers a very simple “bellwether” transfer learner. Given N data sets, we find which...
To assist the vulnerability identification process, researchers proposed prediction models that highlight (for inspection) the most likely to be vulnerable parts of a system. In this paper we aim at making a reliable replication and comparison of the main vulnerability prediction models. Thus, we seek for determining their effectiveness, i.e., their ability to distinguish between vulnerable and non-vulnerable...
Este artículo abarca un estudio del análisis hiperespectral en el proceso de fermentación de granos de cacao violeta. La aplicación de técnicas de procesamiento de imágenes hiperespectrales en el cacao es escasa. Este artículo presenta un estudio basado en el cálculo de índices espectrales, encontrando una correlación con los parámetros bioquímicos que indican una correcta evolución de la fermentación...
Software defect prediction aims to determine whether a software module is defect-prone by constructing prediction models. The performance of such models is susceptible to the high dimensionality of the datasets that may include irrelevant and redundant features. Feature selection is applied to alleviate this issue. Because many feature selection methods have been proposed, there is an imperative need...
The application of digital instrumentation and control systems in Nuclear Power Plants (NPPs) provides a series of advantages, but it also raises challenges in the reliability analysis of safety-critical systems in the NPPs. Software testing is one of the most significant processes to assure software reliability, and the safety-critical systems of NPPs are sensitive to the severity of software faults,...
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