scholarly journals The Derivation of Defect Priorities and Core Defects through Impact Relationship Analysis between Embedded Software Defects

2020 ◽  
Vol 10 (19) ◽  
pp. 6946
Author(s):  
Sang Moo Huh ◽  
Woo-Je Kim
Keyword(s):  
Field Studies ◽  
Embedded Software ◽  
Task Management ◽  
Software Defects ◽  
Relationship Analysis ◽  
Software Defect ◽  
Test Order ◽  
External Interface ◽  
The Impact

As embedded software is closely related to hardware equipment, any defect in embedded software can lead to major accidents. Thus, all defects must be collected, classified, and tested based on their severity. In the pure software field, a method of deriving core defects already exists, enabling the collection and classification of all possible defects. However, in the embedded software field, studies that have collected and categorized relevant defects into an integrated perspective are scarce, and none of them have identified core defects. Therefore, the present study collected embedded software defects worldwide and identified 12 types of embedded software defect classifications through iterative consensus processes with embedded software experts. The impact relation map of the defects was drawn using the decision-making trial and evaluation laboratory (DEMATEL) method, which analyzes the influence relationship between elements. As a result of analyzing the impact relation map, the following core embedded software defects were derived: hardware interrupt, external interface, timing error, device error, and task management. All defects can be tested using this defect classification. Moreover, knowing the correct test order of all defects can eliminate critical defects and improve the reliability of embedded systems.

scholarly journals Intelligent radar software defect classification approach based on the latent Dirichlet allocation topic model

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xi Liu ◽  
Yongfeng Yin ◽  
Haifeng Li ◽  
Jiabin Chen ◽  
Chang Liu ◽  
...  
Keyword(s):  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Recall Rate ◽  
Defect Classification ◽  
Software Defects ◽  
Classification Approach ◽  
Software Defect ◽  
Model Combining ◽  
Dirichlet Allocation

AbstractExisting software intelligent defect classification approaches do not consider radar characters and prior statistics information. Thus, when applying these appaoraches into radar software testing and validation, the precision rate and recall rate of defect classification are poor and have effect on the reuse effectiveness of software defects. To solve this problem, a new intelligent defect classification approach based on the latent Dirichlet allocation (LDA) topic model is proposed for radar software in this paper. The proposed approach includes the defect text segmentation algorithm based on the dictionary of radar domain, the modified LDA model combining radar software requirement, and the top acquisition and classification approach of radar software defect based on the modified LDA model. The proposed approach is applied on the typical radar software defects to validate the effectiveness and applicability. The application results illustrate that the prediction precison rate and recall rate of the poposed approach are improved up to 15 ~ 20% compared with the other defect classification approaches. Thus, the proposed approach can be applied in the segmentation and classification of radar software defects effectively to improve the identifying adequacy of the defects in radar software.

scholarly journals Intelligent Radar Software Defect Classification Approach based on the Latent Dirichlet Allocation Topic Model

2021 ◽  
Author(s):  
Xi Liu ◽  
Yongfeng Yin ◽  
Haifeng Li ◽  
Jiabin Chen ◽  
Chang Liu ◽  
...  
Keyword(s):  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Recall Rate ◽  
Defect Classification ◽  
Software Defects ◽  
Classification Approach ◽  
Software Defect ◽  
Model Combining ◽  
Dirichlet Allocation

Abstract Existing software intelligent defect classification approaches don’t consider radar characters and prior statistics information. Thus when applying these appaoraches into radar software testing and validation, the precision rate and recall rate of defect classification are poor and have effect on the reuse effectiveness of software defects. To solve this problem, a new intelligent defect classification approach based on the latent Dirichlet allocation (LDA) topic model is proposed for radar software in this paper. The proposed approach includes the defect text segmentation algorithm based on the dictionary of radar domain, the modified LDA model combining radar software requirement, the top acquisition and classification approach of radar software defect based on the modified LDA model. The proposed approach is applied on the typical radar software defects to validate the effectiveness and applicability. The application results illustrate that the prediction precison rate and recall rate of the poposed approach are improved up to 15%~20% compared with the other defect classification approaches. Thus, the proposed approach can be applied in the segmentation and classification of radar software defecs effectively to improve the identifying adequacy of the defects in radar software.

scholarly journals Mining Software Repositories for Defect Categorization

2015 ◽  
Vol 11 (1) ◽  
pp. 31 ◽  
Author(s):  
Sakthi Kumaresh ◽  
Ramachandran Baskaran
Keyword(s):  
Domain Knowledge ◽  
Software Defects ◽  
Software Cost ◽  
Software Defect ◽  
Using Data ◽  
Software Bug ◽  
Defect Extraction ◽  
Bug Repositories ◽  
Different Levels

Early detection of software defects is very important to decrease the software cost and subsequently increase the software quality. Success of software industries not only depends on gaining knowledge about software defects, but largely reflects from the manner in which information about defect is collected and used. In software industries, individuals at different levels from customers to engineers apply diverse mechanisms to detect the allocation of defects to a particular class. Categorizing bugs based on their characteristics helps the Software Development team take appropriate actions to reduce similar defects that might get reported in future releases. Classification, if performed manually, will consume more time and effort. Human resource having expert testing skills & domain knowledge will be required for labeling the data. Therefore, the need of automatic classification of software defect is high.This work attempts to categorize defects by proposing an algorithm called Software Defect CLustering (SDCL). It aims at mining the existing online bug repositories like Eclipse, Bugzilla and JIRA for analyzing the defect description and its categorization. The proposed algorithm is designed by using text clustering and works with three major modules to find out the class to which the defect should be assigned. Software bug repositories hold software defect data with attributes like defect description, status, defect open and close date. Defect extraction module extracts the defect description from various bug repositories and converts it into unified format for further processing. Unnecessary and irrelevant texts are removed from defect data using data preprocessing module. Finally grouping of defect data into clusters of similar defect is done using clustering technique. The algorithm provides classification accuracy more than 80% in all of the three above mentioned repositories.

ON THE CLASSIFICATION OF DIGITAL TECHNOLOGIES IN CIVIL PROCESS

2019 ◽  
pp. 27-35
Author(s):  
Alexandr Neznamov
Keyword(s):  
Information Processing ◽  
Scientific Community ◽  
Digital Technologies ◽  
Significant Feature ◽  
Legal Proceedings ◽  
Civil Process ◽  
Civil Proceedings ◽  
Processing Information ◽  
The Impact

Digital technologies are no longer the future but are the present of civil proceedings. That is why any research in this direction seems to be relevant. At the same time, some of the fundamental problems remain unattended by the scientific community. One of these problems is the problem of classification of digital technologies in civil proceedings. On the basis of instrumental and genetic approaches to the understanding of digital technologies, it is concluded that their most significant feature is the ability to mediate the interaction of participants in legal proceedings with information; their differentiating feature is the function performed by a particular technology in the interaction with information. On this basis, it is proposed to distinguish the following groups of digital technologies in civil proceedings: a) technologies of recording, storing and displaying (reproducing) information, b) technologies of transferring information, c) technologies of processing information. A brief description is given to each of the groups. Presented classification could serve as a basis for a more systematic discussion of the impact of digital technologies on the essence of civil proceedings. Particularly, it is pointed out that issues of recording, storing, reproducing and transferring information are traditionally more «technological» for civil process, while issues of information processing are more conceptual.

Influence of internal and external risks on sustainability of financial system of Аltai krai

2018 ◽  
Vol 35 (4) ◽  
pp. 133-136
Author(s):  
R. N. Ibragimov
Keyword(s):  
Sustainable Development ◽  
Financial Stability ◽  
Management Strategy ◽  
Financial System ◽  
Risk Management Strategy ◽  
The Sustainable Development ◽  
The Stability ◽  
The Impact

The article examines the impact of internal and external risks on the stability of the financial system of the Altai Territory. Classification of internal and external risks of decline, affecting the sustainable development of the financial system, is presented. A risk management strategy is proposed that will allow monitoring of risks, thereby these measures will help reduce the loss of financial stability and ensure the long-term development of the economy of the region.

Fish diversity

2017 ◽  
Author(s):  
Derek Burton ◽  
Margaret Burton
Keyword(s):  
Life Style ◽  
Fish Diversity ◽  
Additional Species ◽  
The Impact ◽  
Current Species

Fish diversity is considered in terms of variety of their morphological, taxonomic, habitat and population attributes. Fish, with over 30, 000 current species, represent the largest group of vertebrates. The complexity of classification of a group of this size and antiquity, together with recognition of additional species, demands continuous ongoing revision. The impact of the recent fundamental changes in fish classification in 2016 is discussed. Life in water involves adaptations to widely different habitats which can result in physiological morphological and life-style variations which are reviewed.

scholarly journals Formation of an Export-Oriented Agricultural Economy and Regional Open Innovations

2021 ◽  
Vol 7 (1) ◽  
pp. 32
Author(s):  
Victor L. Shabanov ◽  
Marianna Ya Vasilchenko ◽  
Elena A. Derunova ◽  
Andrey P. Potapov
Keyword(s):  
Agricultural Economy ◽  
Institutional Management ◽  
Agricultural Exports ◽  
Modeling Methodology ◽  
Fixed Assets ◽  
Analysis Application ◽  
The Impact ◽  
The Relationship

The aim of the work is to find relevant indicators for assessing the relationship between investments in fixed assets in agriculture, gross output of the industry, and agricultural exports using tools for modeling the impact of innovation and investment development on increasing production and export potential in the context of the formation of an export-oriented agricultural economy. The modeling methodology and the proposed estimating and forecasting tools for diagnosing and monitoring the state of sectoral and regional innovative agricultural systems are used to analyze the relationship between investments in fixed assets in agriculture, gross output of the industry, and agricultural exports based on the construction of the classification of Russian regions by factors that aggregate these features to diagnose incongruence problems and to improve institutional management in regional innovative export-oriented agrosystems. Based on the results of the factor analysis application, an underestimated role of indicators of investment in agriculture, the intensity and efficiency of agricultural production, were established. Based on the results of the cluster analysis, the established five groups of regions were identified, with significant differences in the level of investment in agriculture, the volume of production of the main types of agricultural products, and the export and exported food. The research results are of practical value for use in improving institutional management when planning reforms and transformations of regional innovative agrosystems.

scholarly journals Reproduction and biomarker responses of Eisenia fetida after exposure to imidacloprid in biochar-amended soil

Biochar ◽  
2021 ◽  
Author(s):  
Ngitheni Winnie-Kate Nyoka ◽  
Ozekeke Ogbeide ◽  
Patricks Voua Otomo
Keyword(s):  
Eisenia Fetida ◽  
Field Studies ◽  
Application Rate ◽  
Land Application ◽  
Acetylcholinesterase Inhibition ◽  
Beneficial Effects ◽  
Pesticide Pollution ◽  
The One ◽  
The Impact ◽  
Amended Soil

AbstractTerrestrial and aquatic ecosystems are increasingly threatened by pesticide pollution resulting from extensive use of pesticides, and due to the lack of regulatory measures in the developing world, there is a need for affordable means to lessen environmental effects. This study aimed to investigate the impact of biochar amendment on the toxicity of imidacloprid to life-cycle parameters and biomarker responses of the earthworm Eisenia fetida. E. fetida was exposed to 10% biochar-amended and non-amended OECD artificial soils spiked with 0, 0.75, 1.5, 2.25 and 3 mg imidacloprid/kg for 28 days. An LC50 of 2.7 mg/kg was only computed in the non-amended soil but not in the biochar-amended soil due to insignificant mortality. The EC50 calculated in the non-amended soil (0.92 mg/kg) for reproduction (fertility) was lower than the one computed in the biochar amended (0.98 mg/kg), indicating a decrease in toxicity in the biochar-amended substrate. Significant weight loss was observed at the two highest imidacloprid treatments in the non-amended soil and only at the highest treatment in the biochar-amended substrate, further highlighting the beneficial effects of biochar. Catalase activity decreased significantly at the two highest concentrations of non-amended soil. Yet, in the amended soil, the activity remained high, especially in the highest concentration, where it was significantly higher than the controls. This indicated more severe oxidative stress in the absence of biochar. In all non-amended treatments, there was a significant acetylcholinesterase inhibition, while lower inhibition percentages were observed in the biochar-amended soil. In most endpoints, the addition of biochar alleviated the toxic effects of imidacloprid, which shows that biochar has the potential to be useful in soil remediation. However, there is still a need for field studies to identify the most effective application rate of biochar for land application.

scholarly journals Minimization of the Line Resistance Impact on Memdiode-Based Simulations of Multilayer Perceptron Arrays Applied to Pattern Recognition

2021 ◽  
Vol 11 (1) ◽  
pp. 9
Author(s):  
Fernando Leonel Aguirre ◽  
Nicolás M. Gomez ◽  
Sebastián Matías Pazos ◽  
Félix Palumbo ◽  
Jordi Suñé ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Ex Situ ◽  
Multilayer Perceptrons ◽  
Spice Simulation ◽  
Large Dataset ◽  
High Line ◽  
Calibration Algorithm ◽  
The Impact ◽  
Line Resistance

In this paper, we extend the application of the Quasi-Static Memdiode model to the realistic SPICE simulation of memristor-based single (SLPs) and multilayer perceptrons (MLPs) intended for large dataset pattern recognition. By considering ex-situ training and the classification of the hand-written characters of the MNIST database, we evaluate the degradation of the inference accuracy due to the interconnection resistances for MLPs involving up to three hidden neural layers. Two approaches to reduce the impact of the line resistance are considered and implemented in our simulations, they are the inclusion of an iterative calibration algorithm and the partitioning of the synaptic layers into smaller blocks. The obtained results indicate that MLPs are more sensitive to the line resistance effect than SLPs and that partitioning is the most effective way to minimize the impact of high line resistance values.

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