Regression Testing: Analysis of its Techniques for Test Effectiveness

Dahiya, Omdev

doi:10.30534/ijatcse/2020/105912020

Cited by 9 publications

(4 citation statements)

References 21 publications

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“…We have worked towards documenting the work of numerous researchers on different bio-inspired algorithms to solve large-scale real-world problems for finding optimal solution and their usage in software testing as well. As testing overall improves the quality of software [298]. Researchers were inspired in diverse ways to develop such diverse algorithms getting inspired from nature.…”

Section: Resultsmentioning

confidence: 99%

An Exploratory Retrospective Assessment on the Usage of Bio-Inspired Computing Algorithms for Optimization

Dahiya¹

2020

IJETER

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In the era of digitalization, every task is performed with the help of software-dependent applications. Therefore, the developed software is required to be robust, reliable, and fault free. Testing is performed to check the functioning of the developed software to evaluate whether the software product is error-free or not. Test cases play a vital role in the testing process. However, with the advancement of time, a particular test suite becomes so lengthy that the execution of all the test cases is not possible due to limited time and resources. Researchers have proposed diverse techniques to make the testing process an effective one. This study has worked towards finding the usage of bio-inspired computing algorithms used for optimization. The reason behind this is because these algorithms have performed exceptionally well in addressing complex problems to provide workable solutions in a reasonable time. It is observed that only a handful of these algorithms were applied in testing, such as ant colony optimization, bee colony optimization, neural networks, and genetic algorithms. Even progress is made in the limited area of these algorithms. This study was conducted with a motive to sort out the most popular bio-inspired algorithms and to explore their working principles, developments made till now, along with the scope of their application. This paper has discussed how the development of these algorithms has progressed from already explored algorithms to the development of many new ones such as cuckoo search, artificial bee colony, bat algorithm, firefly algorithm, flower pollination algorithm, and many more. This study will help the researchers to gain insight into choosing the algorithm and explore them in developing new techniques for optimization.

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Section: Resultsmentioning

confidence: 99%

An Exploratory Retrospective Assessment on the Usage of Bio-Inspired Computing Algorithms for Optimization

Dahiya¹

2020

IJETER

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“…In addition to heating, preparation can also be conducted by the cold alkaline method. Determination with a spectrophotometer requires a standard curve, and the wavelength used is 620 nm [39].Spectrophotometry is an analytical instrument that is widely used and continues to grow with various modifications in its application, including through Algorithm-based Spectrophotometry [40].The data obtained can be further processed or analyzed for a variety of more communicative data displays, including by the regression testing for test effectiveness technique [41].…”

Section: Amylopectin Analysis By Spectrophotometrymentioning

confidence: 99%

Review on the Analysis Methods of Starch, Amylose, Amylopectinin Food and Agricultural Products

Subroto¹

2020

IJETER

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Starch is one of the biggest components of carbohydrates in food and other biological materials. The main components of starch consist of amylose and amylopectin. The comparison between amylose and amylopectin greatly influences the functional, physicochemical, and pasting properties of starch. Various methods of analyzing starch, amylose, and amylopectin content have been widely studied for various purposes. This review describes several types of quantitative analysis methods for starch, amylose and amylopectin. Quantitative methods to determine starch content include the polarimetry, anthrone, Fourier-transform infrared spectroscopy (FTIR), spectrophotometry, penetrometry, and Luff schoorl. The methods for determining amylose content are spectrophotometry and gravimetry, while the method for determining amylopectin content using X-Ray Diffraction (XRD) and gravimetry. Each method has several advantages and disadvantages so that it can be used to determine the method suitable for materials with certain characteristics.

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“…Studying all the previous work done by various researchers helps us to assess that there is a critical need to work in the field of making reliable software in fixed time and cost asked customers/organizations. The quality of software can be increased through many ways like testing each component at every phase of the software development life cycle (early removal of bugs), using various optimization techniques [31][32][33][34][35][36][37][38]. Nowadays, a reliable, more efficient, and fault-free software product is demanded in almost every field like routing protocols in the area of communication, big data analysis in the area of security of web, social networking sites, facial recognition and for working in a smart environment, etc [39][40][41][42][43][44][45][46][47][48][49].…”

Section: Hu Et Al Used Modified Adaptive Testing For Developing a Model For Estimating The Reliability Of Component-based Systemsmentioning

confidence: 99%

Component-Based Software System using Computational Intelligence Technique for Reliability Prediction

Yadav¹

2020

IJATCSE

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Software developers and companies are working to create reliable software for their users. This has resulted in the need for enhancing predictive software quality models for risk-less software development based on the type of software. Development and testing costs can be reduced by reusing existing codes and components. Re-use of components results in increased productivity, quality, and maintainability of the software as iterations are made for incremental changes, new developments altogether, and reducing development cost, time, effort. Component-based software systems along with soft computing techniques should be used for having more reliable software. With the increase in demand for software quality prediction, several techniques have been used to predict software quality. The focus of this paper is on the software product's quality; metrics and we thoroughly review the literature of existing computational intelligence/soft computing techniques and analyze the findings according to the techniques. We have discussed models for software quality prediction for component-based software and computational intelligence techniques which are widely prevalent for software quality prediction and compare different techniques. In our study, we have done a comparative analysis of soft computing techniques. This study will help the other researchers to study and understand which technique would be more helpful in making the software reliability prediction model for component-based software by combining different computational techniques.

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Regression Testing: Analysis of its Techniques for Test Effectiveness

Cited by 9 publications

References 21 publications

An Exploratory Retrospective Assessment on the Usage of Bio-Inspired Computing Algorithms for Optimization

An Exploratory Retrospective Assessment on the Usage of Bio-Inspired Computing Algorithms for Optimization

Review on the Analysis Methods of Starch, Amylose, Amylopectinin Food and Agricultural Products

Component-Based Software System using Computational Intelligence Technique for Reliability Prediction

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