Controlling Occurrence Frequencies of Parameter Values in Pair-Wise Testing

2018 ◽  
Vol 28 (07) ◽  
pp. 983-1000 ◽  
Author(s):  
Satoshi Fujimoto ◽  
Hideharu Kojima ◽  
Tatsuhiro Tsuchiya
Keyword(s):  
Test Suite ◽  
Test Case ◽  
Frequency Of Occurrence ◽  
Testing Strategy ◽  
Weighting Method ◽  
Current Test ◽  
Parameter Values ◽  
The Given ◽  
Weighting Methods ◽  
The Ideal

Pair-wise testing is a widely used strategy of software testing. It requires testing every pair of parameter values at least once. This paper focuses weighting of parameter values for this testing strategy. Weighting is an added feature which allows the tester to prioritize different parameter values by specifying their desired frequency of occurrence in a test suite. This feature is desirable as it allows the tester to have more control over the resulting test suite. However, there has been not much research on weighting: to our knowledge, all existing weighting methods treat weights as a second class requirement and cannot generate a test suite that sufficiently respects the given weights. Aiming to overcome this problem, this paper proposes a weighting method which can be used in combination of any one-test-at-a-time greedy test case generation algorithm. By comparing the parameter value distribution in the current test suite and the ideal one specified by the given weights, the method generates each test case so that the resulting test suite can reflect the weights as accurately as possible. The usefulness of the method is demonstrated through empirical results.

scholarly journals Diversifying Focused Testing for Unit Testing

2021 ◽  
Vol 30 (4) ◽  
pp. 1-24
Author(s):  
Héctor D. Menéndez ◽  
Gunel Jahangirova ◽  
Federica Sarro ◽  
Paolo Tonella ◽  
David Clark
Keyword(s):  
Search Algorithm ◽  
Symbolic Execution ◽  
Specific Area ◽  
Test Suite ◽  
Constraint Solving ◽  
Test Case ◽  
Unit Testing ◽  
Bug Detection ◽  
Mutation Score ◽  
The Given

Software changes constantly, because developers add new features or modifications. This directly affects the effectiveness of the test suite associated with that software, especially when these new modifications are in a specific area that no test case covers. This article tackles the problem of generating a high-quality test suite to cover repeatedly a given point in a program, with the ultimate goal of exposing faults possibly affecting the given program point. Both search-based software testing and constraint solving offer ready, but low-quality, solutions to this: Ideally, a maximally diverse covering test set is required, whereas search and constraint solving tend to generate test sets with biased distributions. Our approach, Diversified Focused Testing (DFT), uses a search strategy inspired by GödelTest. We artificially inject parameters into the code branching conditions and use a bi-objective search algorithm to find diverse inputs by perturbing the injected parameters, while keeping the path conditions still satisfiable. Our results demonstrate that our technique, DFT, is able to cover a desired point in the code at least 90% of the time. Moreover, adding diversity improves the bug detection and the mutation killing abilities of the test suites. We show that DFT achieves better results than focused testing, symbolic execution, and random testing by achieving from 3% to 70% improvement in mutation score and up to 100% improvement in fault detection across 105 software subjects.

scholarly journals Regression Test Suite Reduction using an Hybrid Technique Based on BCO And Genetic Algorithm

2013 ◽  
pp. 26-33
Author(s):  
Bharti Suri ◽  
Isha Mangal ◽  
Varun Srivastava
Keyword(s):  
Optimization Problems ◽  
Minimum Time ◽  
Test Suite ◽  
Test Case ◽  
Hybrid Technique ◽  
Bee Colony ◽  
Bee Colony Optimization ◽  
Test Suite Reduction ◽  
The Given ◽  
Swarm Intelligence Algorithm

Regression testing is a maintenance activity that is performed to ensure the validity of modified software. The activity takes a lot of time to run the entire test suite and is very expensive. Thus it becomes a necessity to choose the minimum set of test cases with the ability to cover all the faults in minimum time. The paper presents a new test case reduction hybrid technique based on Genetic algorithms(GA) and bee colony optimization (BCO) .GA is an evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. BCO is a swarm intelligence algorithm. The proposed approach adopts the behavior of bees to solve the given problem. It proves to be optimistic approach which provides optimum results in minimum time.

Ahiolohiya poetychnoyi zbirky Lazarya Baranovycha Żywoty świętych (1670)

2020 ◽  
pp. 249-258
Author(s):  
Olena Ruda
Keyword(s):  
Family Life ◽  
18Th Century ◽  
The Given ◽  
The Ideal ◽  
Poetry Collection

The purpose of the article is the analysis of hagiology in Lazar Baranovych’s poetry collection entitled Żywoty świętych (1670). This includes the fulfi lment of such tasks: 1) To enumerate the saints mentioned in the poetry collection; 2) To determine to which church/epoch/place of worship or order of sainthood they belong; 3) To determine how full the saints’ details of biography are refl ected in the poetry collection mentioned above; 4) To understand Lazar Baranovych’s view on the topic of diff erent kinds of sainthood clearly; 5) To measure the actuality of his views given the context of the 18th century Ukraine. The results of the research are shared in the given article, showing how exactly Lazar Baranovych defi ned for himself the concept of the sainthood at the fi rst place. They also tell us about his views on the call for monkhood and family life and help us to reconstruct the images of the ideal spiritual shepherd, female Christian etc.

scholarly journals Malmquist Productivity Index by Extended VIKOR Method Using Interval Numbers

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Mohammad Fallah ◽  
Amir Mohajeri ◽  
Esmaeil Najafi
Keyword(s):  
Multicriteria Decision Making ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Ideal Solution ◽  
Vikor Method ◽  
Decision Matrix ◽  
Interval Numbers ◽  
Productivity Rate ◽  
The Given ◽  
The Ideal

The VIKOR method was developed for multicriteria optimization of complex systems. It determines the compromise ranking list and the compromise solution obtained with the given weights. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. Here, the VIKOR method is used for two timestandt+1. In order to calculate the progress or regression via Malmquist productivity index, the positive and negative ideals at timestandt+1are calculated first. Then we introduce the multi-criteria ranking index based on the particular measure of “closeness” to the ideal solution and calculate the separation of each alternative from the ideal solution at timestandt+1. Then we use the Malmquist productivity index to calculate the progress or regression of all alternatives. In this paper, productivity of alternatives available in decision matrix with interval numbers and their improvement or deterioration is researched. To achieve this practical goal, use of extended VIKOR is made to calculate Malmquist productivity index for multicriteria decision-making (MCDM) problem with interval numbers, and by applying Malmquist productivity index, productivity rate of growth for alternatives is calculated. Finally, a numerical example illustrates and clarifies the main results developed in this paper.

A network thermodynamic model of salt and water flow across the kidney proximal tubule

1978 ◽  
Vol 235 (6) ◽  
pp. F638-F648 ◽  
Author(s):  
S. R. Thomas ◽  
D. C. Mikulecky
Keyword(s):  
Proximal Tubule ◽  
Water Flow ◽  
Thermodynamic Model ◽  
Circuit Simulation ◽  
Basolateral Membrane ◽  
Kidney Proximal Tubule ◽  
Network Analyses ◽  
Pump Rate ◽  
Parameter Values ◽  
The Given

This network thermodynamic model of kidney proximal tubule epithelium treats coupled salt and water flow across each component membrane of the epithelium. We investigate the effects of various relative internal parameter values on the concentration of transepithelial flow, the concentrations in the cell and interspace, and the distribution of flows between cellular and paracellular routes. Best fit is obtaine if the apical and basolateral membrane reflection coefficients (or) are equal. The measured transepithelial filtration coefficient, Lp, is a function not only of the component Lps but also of the internal concentrations, or's, and permeabilities. For the given system topology (i.e., connectedness), parameters of component membranes must be within a narrow range to be consistent with experimental results. The dependence of the concentration of transported fluid on the balance between the solute pump rate and the transepithelial volume flow driving force is shown. This has implications for the effects of peritubular or lumen oncotic pressure on salt and water flow. With Appendix B of this paper and a user's guide for a circuit-simulation package (e.g., SPICE or PCAP) the reader can perform similar network analyses of transport models himself.

Multi-Attribute Comprehensive Evaluation Method for Power Transmission and Transformation Projects

2014 ◽  
Vol 521 ◽  
pp. 245-251
Author(s):  
Kai Xu ◽  
Xiao Yu Ding ◽  
Hong Wei Chen ◽  
Quan Yuan Jiang ◽  
Ke Sun ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Power Transmission ◽  
Comprehensive Evaluation ◽  
Engineering System ◽  
Weighting Method ◽  
Environmental Friendliness ◽  
Comprehensive Evaluation Method ◽  
Moment Estimation ◽  
The Moment ◽  
Weighting Methods

With the number of power transmission and transformation projects increasing, it needs to consider more indices information and utilize more comprehensive evaluation methods in the decision-making of building schemes. As a consequence, a comprehensive evaluation indices system, including the indices of network security, economy, environmental friendliness, adaptation and coordination of the power transmission and transformation engineering system, is firstly built to evaluation construction schemes. Then this paper proposes a multi-attribute comprehensive evaluation method for power transmission and transformation projects. In this method, the optimal combination weighting method based on the moment estimation is adopted to weight for every index. It can overcome the weakness of the subjective weighting methods and the objective methods. After that, the optimal scheme is obtained by the grey correlation-cosine prioritizing evaluation method, which can take into account the distance and angle information of schemes. Finally, the example shows this method can fully consider overall information of each index, having good operability.

scholarly journals Test Case Reduction Using Ant Colony Optimization for Object Oriented Program

2015 ◽  
Vol 5 (6) ◽  
pp. 1424
Author(s):  
Sudhir Kumar Mohapatra ◽  
Srinivas Prasad
Keyword(s):  
Ant Colony Optimization ◽  
System Development ◽  
Object Oriented ◽  
Ant Colony ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Reduction Techniques ◽  
Maintenance Stage ◽  
The Cost

Software testing is one in all the vital stages of system development. In software development, developers continually depend upon testing to reveal bugs. Within the maintenance stage test suite size grow due to integration of new functionalities. Addition of latest technique force to make new test case which increase the cost of test suite. In regression testing new test case could also be added to the test suite throughout the entire testing process. These additions of test cases produce risk of presence of redundant test cases. Because of limitation of time and resource, reduction techniques should be accustomed determine and take away. Analysis shows that a set of the test case in a suit should satisfy all the test objectives that is named as representative set. Redundant test case increase the execution price of the test suite, in spite of NP-completeness of the problem there are few sensible reduction techniques are available. During this paper the previous GA primarily based technique proposed is improved to search out cost optimum representative set using ant colony optimization.

Comparison of Multi-Objective Evolutionary Algorithms to Prioritize Regression Test Cases

2021 ◽  
Vol 9 (12) ◽  
pp. 1445-1454
Keyword(s):  
Fault Detection ◽  
Evolutionary Algorithms ◽  
Fitness Function ◽  
Optimal Solution ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Nsga Ii ◽  
Multi Objective ◽  
Regression Test

Regression testing is one of the most critical testing activities among software product verification activities. Nevertheless, resources and time constraints could inhibit the execution of a full regression test suite, hence leaving us in confusion on what test cases to run to preserve the high quality of software products. Different techniques can be applied to prioritize test cases in resource-constrained environments, such as manual selection, automated selection, or hybrid approaches. Different Multi-Objective Evolutionary Algorithms (MOEAs) have been used in this domain to find an optimal solution to minimize the cost of executing a regression test suite while obtaining maximum fault detection coverage as if the entire test suite was executed. MOEAs achieve this by selecting set of test cases and determining the order of their execution. In this paper, three Multi Objective Evolutionary Algorithms, namely, NSGA-II, IBEA and MoCell are used to solve test case prioritization problems using the fault detection rate and branch coverage of each test case. The paper intends to find out what’s the most effective algorithm to be used in test cases prioritization problems, and which algorithm is the most efficient one, and finally we examined if changing the fitness function would impose a change in results. Our experiment revealed that NSGA-II is the most effective and efficient MOEA; moreover, we found that changing the fitness function caused a significant reduction in evolution time, although it did not affect the coverage metric.

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