scholarly journals Three Measures of Test Adaptation Based on Optimal Test Information

2020 ◽  
Vol 8 (1) ◽  
pp. 1-19
Author(s):  
Gage Kingsbury ◽  
Steven Wise
Keyword(s):  
Optimal Test ◽  
Test Adaptation ◽  
Test Information

scholarly journals Research on optimizing the fault diagnosis strategy of complex electronic equipment

2010 ◽  
Vol 7 (1) ◽  
pp. 223-230
Author(s):  
Hong-Xia Wang ◽  
Xiao-Hui Ye ◽  
Liang Wang
Keyword(s):  
Test Point ◽  
Electronic Equipment ◽  
Fault Detection And Isolation ◽  
Point Selection ◽  
Optimal Test ◽  
Test Information ◽  
Testing Sequence ◽  
Test Point Selection ◽  
Global Optimal ◽  
Test Points

Diagnosis strategy is a testing sequence of the fault detection and isolation. For the distribution of the electronic equipment, a feasible engineering maintenance method is put forward based on the questions of test point selection and diagnosis strategy. The concepts of local diagnosis strategy and global diagnosis strategy are introduced. From which the local optimal diagnosis strategy is determined when the local optimal test points have been introduced by using the test information entropy, furthermore, the global optimal diagnosis strategy is determined by coalescing the local optimal diagnosis strategies. At last, the validity of the method is illustrated by an example from which the conclusion can be drawn that it is an optimal diagnosis strategy and the complexity of computation can be reduced.

scholarly journals Particle swarm optimization to produce optimal solution

2018 ◽  
Vol 7 (1.7) ◽  
pp. 210 ◽  
Author(s):  
C Saranya Jothi ◽  
V Usha ◽  
R Nithya
Keyword(s):  
Particle Swarm Optimization ◽  
Test Data ◽  
Fitness Function ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Optimization Techniques ◽  
Optimal Test ◽  
Swarm Optimization ◽  
Test Information ◽  
Fitness Value

Search-Based Software Testing is the utilization of a meta-heuristic improving scan procedure for the programmed age of test information. Particle Swarm Optimization (PSO) is one of those technique. It can be used in testing to generate optimal test data solution based on an objective function that utilises branch coverage as criteria. Software under test is given as input to the algorithm. The problem becomes a minimization problem where our aim is to obtain test data with minimum fitness value. This is called the ideal test information for the given programming under test. PSO algorithm is found to outperform most of the optimization techniques by finding least value for fitness function. The algorithm is applied to various software under tests and checked whether it can produce optimal test data. Parameters are tuned so as to obtain better results.

Optimal Test Assembly in Practice

2013 ◽  
Vol 221 (3) ◽  
pp. 190-200 ◽  
Author(s):  
Jörg-Tobias Kuhn ◽  
Thomas Kiefer
Keyword(s):  
Particle Physics ◽  
Large Scale ◽  
Block Design ◽  
Linear Optimization ◽  
Mixed Integer ◽  
Optimal Test ◽  
Automated Test Assembly ◽  
Test Assembly ◽  
Block Level ◽  
Mixed Integer Linear Optimization

Several techniques have been developed in recent years to generate optimal large-scale assessments (LSAs) of student achievement. These techniques often represent a blend of procedures from such diverse fields as experimental design, combinatorial optimization, particle physics, or neural networks. However, despite the theoretical advances in the field, there still exists a surprising scarcity of well-documented test designs in which all factors that have guided design decisions are explicitly and clearly communicated. This paper therefore has two goals. First, a brief summary of relevant key terms, as well as experimental designs and automated test assembly routines in LSA, is given. Second, conceptual and methodological steps in designing the assessment of the Austrian educational standards in mathematics are described in detail. The test design was generated using a two-step procedure, starting at the item block level and continuing at the item level. Initially, a partially balanced incomplete item block design was generated using simulated annealing, whereas in a second step, items were assigned to the item blocks using mixed-integer linear optimization in combination with a shadow-test approach.

A Future Online Analyzer for Hidden Project Management Risks

2017 ◽  
Vol 7 (7) ◽  
pp. 99
Author(s):  
Rupali A. Mahajan
Keyword(s):  
Cloud Computing ◽  
Project Management ◽  
Qualitative Study ◽  
Software Testing ◽  
Gold Plating ◽  
Software Cost ◽  
Test Information ◽  
Online Software

The aim of this qualitative study was to investigate and comprehend the conditions that impact software cost, requirement tracking as well as scheduled software testing as an online administration and inspire essential exploration issues. Interviews were led with administrators from five associations. Thestudy utilized qualitative grounded hypothesis as its exploration system. The effects show that the interest for software testing and online requirement monitoring as an online administration is on the ascent and is impacted by conditions, for example, the level of area information required to adequately test a provision, adaptability and expense adequacy as profits, security and estimating as top prerequisites, cloud computing as the project monitor mode and the need for software analyzers to sharpen their abilities. Potential e x p l o r a t i o n territories recommended incorporate requisition regions best suited for online software testing, estimating and treatment of test information among others. The key issue is to monitor client’s requirements, track those requirements and also make it bug free and to avoid requirement gold plating issue. This study will present latest i d e a a b o u t online r e q u i r e m e n t monitoring and software testing.

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