Modeling software testing costs and risks using fuzzy logic paradigm

2007 ◽  
Vol 80 (6) ◽  
pp. 817-835 ◽  
Author(s):  
Avner Engel ◽  
Mark Last
Keyword(s):  
Fuzzy Logic ◽  
Software Testing ◽  
Modeling Software ◽  
Testing Costs

scholarly journals Using Fuzzy Logic Techniques for Assertion-Based Software Testing Metrics

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Ali M. Alakeel
Keyword(s):  
Fuzzy Logic ◽  
Software Testing ◽  
Black Box ◽  
Testing Methods ◽  
Software Developers ◽  
Automated Software Testing ◽  
Large Numbers ◽  
Testing Techniques ◽  
And Performance ◽  
Automated Software

Software testing is a very labor intensive and costly task. Therefore, many software testing techniques to automate the process of software testing have been reported in the literature. Assertion-Based automated software testing has been shown to be effective in detecting program faults as compared to traditional black-box and white-box software testing methods. However, the applicability of this approach in the presence of large numbers of assertions may be very costly. Therefore, software developers need assistance while making decision to apply Assertion-Based testing in order for them to get the benefits of this approach at an acceptable level of costs. In this paper, we present an Assertion-Based testing metrics technique that is based on fuzzy logic. The main goal of the proposed technique is to enhance the performance of Assertion-Based software testing in the presence of large numbers of assertions. To evaluate the proposed technique, an experimental study was performed in which the proposed technique is applied on programs with assertions. The result of this experiment shows that the effectiveness and performance of Assertion-Based software testing have improved when applying the proposed testing metrics technique.

scholarly journals Forward prediction of aeolian systems using fuzzy logic, constrained by data from recent and ancient analogues

2001 ◽  
Vol 80 (1) ◽  
pp. 53-70 ◽  
Author(s):  
Caroline Hern ◽  
Ulf Nordlund ◽  
Kees van der Zwan ◽  
Kenny Ladipo
Keyword(s):  
Fuzzy Logic ◽  
Regional Scale ◽  
Pilot Project ◽  
Reservoir Rock ◽  
Modeling Software ◽  
Generic Modeling ◽  
Well Data ◽  
Facies Types ◽  
Aeolian Systems ◽  
Gas Fields

AbstractAeolian sands are the main reservoir rock in some of the largest gas fields, such as the Shell-Exxon Groningen Field, operated by NAM. Although aeolian reservoirs have been studied for many years, there is still room for improvement in the predictive modeling of such reservoirs. A pilot project with this objective was initiated by SIEP B.V. in 1997, together with Heriot-Watt University in Edinburgh, UK and with Uppsala University, Sweden, to evaluate the factors influencing aeolian systems, and to formulate a forward model using ‘fuzzy logic’.The project was initiated to develop a fuzzy system for generic modeling of aeolian architectures. The key aims were to be able to predict the type, amount and distribution of major facies in generic aeolian systems and specifically to model regional-scale architecture in the sub-surface. Fuzzy rules and sets, which defined the behaviour of aeolian systems, were constructed and used to modify the pre-existing fuzzy modeling software which had been designed for shallow and deep marine systems. The modeling procedure used input data appropriate to the Rotliegend climate, and was validated by comparing the resulting models, in terms of thickness and spatial distribution of facies types, to well data from the Upper Rotliegend interval of the Lauwerszee Trough area, NE Netherlands (Figures 1 & 2).

A FUZZY LOGIC BASED APPROACH FOR SOFTWARE TESTING

2007 ◽  
Vol 21 (04) ◽  
pp. 709-722 ◽  
Author(s):  
ZILI ZHANG ◽  
YANHUI ZHOU
Keyword(s):  
Fuzzy Logic ◽  
Software Engineering ◽  
Software Testing ◽  
Real Data ◽  
Cost Effective ◽  
Similarity Measurement ◽  
Quality Metric ◽  
Effective Strategies ◽  
Long Time ◽  
Effectiveness Measurement

How to provide cost-effective strategies for Software Testing has been one of the research focuses in Software Engineering for a long time. Many researchers in Software Engineering have addressed the effectiveness and quality metric of Software Testing, and many interesting results have been obtained. However, one issue of paramount importance in software testing — the intrinsic imprecise and uncertain relationships within testing metrics — is left unaddressed. To this end, a new quality and effectiveness measurement based on fuzzy logic is proposed. Related issues like the software quality features and fuzzy reasoning for test project similarity measurement are discussed, which can deal with quality and effectiveness consistency between different test projects. Experiments were conducted to verify the proposed measurement using real data from actual software testing projects. Experimental results show that the proposed fuzzy logic based metrics is effective and efficient to measure and evaluate the quality and effectiveness of test projects.

scholarly journals Fuzzy logic modeling software for educational paths data analysis

2020 ◽  
Author(s):  
Alexander A. Tarasyev ◽  
Camilo A. Ospina Acosta ◽  
Gavriil A. Agarkov
Keyword(s):  
Fuzzy Logic ◽  
Data Analysis ◽  
Logic Modeling ◽  
Fuzzy Logic Modeling ◽  
Modeling Software ◽  
Educational Paths

scholarly journals New Software Testing Method Based on Evolutionary Algorithm

2018 ◽  
Vol 7 (3.27) ◽  
pp. 142
Author(s):  
Samiyeh Khosravi ◽  
. .
Keyword(s):  
Fuzzy Logic ◽  
Software Development ◽  
Software Testing ◽  
Test Cases ◽  
Linguistic Variables ◽  
Software Complexity ◽  
Testing Method ◽  
Development Cycle ◽  
Project Estimation

Software Testing is an important part of software development which is performed to support and enhance reliability and quality of software. It consists of estimating testing effort, selecting suitable test team, designing test cases, executing the software with those test cases and examining the results produced by these methods. This paper proposes Fuzzy Based approach for finding out the complexity weight based on requirement. Based on the weight, this paper computes the software complexity point. Fuzzy logic uses membership functions to include linguistic variables and quantifiers. Fuzzy Logic could be used in project estimation purposes efficiently by gathering size data on previously developed programs. The advantage of this model is that it is able to estimate the software complexity which in turn predicts the software requirement stability during the software development cycle.   

Model-Based Software Testing and Analysis with C#

2007 ◽  
Author(s):  
Jonathan Jacky ◽  
Margus Veanes ◽  
Colin Campbell ◽  
Wolfram Schulte
Keyword(s):  
Software Testing ◽  
Model Based
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