Software testing fuzzy logic

Guaje stands for generating understandable and accurate fuzzy models in a java environment. How important is it to be exactly right when a rough answer will do. Org server, php, openssl, pngcrush, bash, firefox, bind, qt, and sqlite. Using fuzzy logic in test case prioritization for regression. It was designed to allow the computer to determine the distinctions among data which is neither true nor false. In fuzzy logic setting, exact rules and membership functions are difficult tasks. Assertions have been recognized as a powerful tool. This is especially true for security testing where the goal is not to prove that the software does what it is supposed to do, but rather that it doesnt do what its. This report documents the implementation of the fuzzy logic ramp metering algorithm at the northwest district of the washington state department of transportation.

An estimation of software reusability using fuzzy logic. These set of rules are also called a knowledge base. Many researchers in software engineering have addressed the effectiveness and quality metric of software testing, and many interesting results have been obtained. Introduction testing is widely recognized as a key quality assurance qa activity in the software development process. Nov 29, 2008 inverted pendulum controlled by a plc with a fuzzy logic software package. M, faridabad, haryana 2 assistant professor, department of computer science, b. Software reuse is defined as software development with several existing modules. Using fuzzy logic techniques for assertionbased software testing. Fuzzing or fuzz testing is an automated software testing technique that involves providing. The fuzzy logic works on the levels of possibilities of input to achieve the definite output. We estimate the quality cost occurring during the development of software for an avionic suite in a fighter aircraft and demonstrate that applying fuzzy logic. A programmers guide to the fuzzy logic ramp metering algorithm.

The main goal of the proposed technique is to enhance. Artificial intelligence fuzzy logic systems tutorialspoint. An efficient strategy for covering array construction with. The idea behind fuzz testing is that software applications and systems. Program assertions have been recognized as a supporting tool during software development, testing, and maintenance. American fuzzy lop fuzzer concolic testing monkey testing random. Test case prioritization using fuzzy logic for gui based software.

Tools can take the drudgery out of the more tedious development and testing tasks and let us get back to what we love. For details on the code, see the technical report a programmers guide to the fuzzy logic ramp metering algorithm. The strategy is applicable to software testing activities in which the combination of input configurations is considered. Thus, the strategy is comparatively slow in generating cas with combination strength beyond 4. The fl method imitates the way of decision making in a human which consider all the possibilities between digital values t and f.

If the address matches an existing account you will receive an email with instructions to reset your password. To this end, a new quality and effectiveness measurement based on fuzzy logic is proposed. Fuzzy logic algorithm helps to solve a problem after considering all available data. In this paper, we presented a novel software testing metric technique for assertionbased software testing that is based on fuzzy logic technology. Fuzzy logic is all about the relative importance of precision. Software design, integration, testing, and evaluation. Based testing metrics technique that is based on fuzzy logic. To develop fuzzy logic protocols, we have to integrate rulebased programming. A fuzzy logic ramp metering algorithm was implemented on 126 ramps in the greater seattle area. The main goal of the proposed approach is to enhance the performance of assertionbased software testing in the presence of large number of assertions. In that research, software agents are used to gather. Nov 02, 2012 we will demonstrate how we used fuzzy testing based on junit 4 and emf to find bugs in the implementation of a real world application. Fuzzy logics fuzzy inference systemfis is the one that solves the complexities in the algorithms.

The main goal of the proposed technique is to enhance the performance of assertionbased. Optimizing software testing using fuzzy logic in aspect oriented programming jyoti1, susheela hooda2 1student, department of computer science, b. Experiments were conducted to verify the proposed measurement using real data from actual software testing projects. Related issues like the software quality features and fuzzy reasoning for test project similarity measurement are discussed, which can deal with quality and. Evaluation of a fuzzy logic ramp metering algorithm. Bootkits keyloggers screen scrapers exploits backdoors logic bombs payloads denial of service web shells web application security phishing.

Regression testing calls for selection of appropriate test cases after modification have been made in the software. Fuzzy logic systems fls produce acceptable but definite output in response to incomplete, ambiguous, distorted, or inaccurate fuzzy input. Research a programmers guide to the fuzzy logic ramp. It can be implemented in systems with various sizes and capabilities ranging from small microcontrollers to large, networked, workstationbased control systems. Inverted pendulum controlled by a plc with a fuzzy logic software package. Fuzzy logic is used with neural networks as it mimics how a person would make decisions, only much faster. Fuzzing or fuzz testing is an automated software testing technique that involves providing invalid, unexpected, or random data as inputs to a computer program. A test suite is developed for the initial version of the software and reused to test each successive version of the software. Recently, a test case prioritization concept that is based on software agents and fuzzy logic was reported in.

The fuzzy logic designer app lets you design and test fuzzy inference systems for modeling complex system behaviors. The software quality features and analogybased reasoning are discussed, which can deal with quality and. Prediction of software reliability using neural network. Free software for generating understandable and accurate fuzzy systems. Assertionbased software testing metrics approach based on. Among these, fuzzy logic and neural network techniques are broadly used to assess software reusability, software maintainability, software understandability etc. The task becomes difficult when the source code is not available. These consist of fuzzy logic system, neural network model and genetic algorithm techniques. Using neural network and fuzzy logic techniques for predicting software reliability sultan aljahdali on. Thus, it is a free software tool licensed under gplv3 with the aim of supporting the design of interpretable and accurate fuzzy systems by means of combining several preexisting open source tools. In a narrow sense, fuzzy logic is a logical system, which is an extension of multivalued logic. However, in a wider sense fuzzy logic fl is almost synonymous with the theory of fuzzy sets, a theory which relates to classes of objects with unsharp boundaries in which membership is a matter of degree. I am going to describe how we can divide big amount of scenarios to several groups using math. Using fuzzy logic techniques for assertionbased software.

Therefore, many software testing techniques to automate the process of software testing have been reported in the literature. Using fuzzy logic techniques for assertionbased software testing metrics 1. Gohner, prioritization of test cases using software agents and fuzzy logic, in proceedings of the 5th ieee international conference on software testing, verification and validation icst 12, pp. Aug, 20 software testing is one of the important processes of software engineering discipline. Software testing is a very labor intensive and costly task. Then it takes the best possible decision for the given the input.

The architecture of fuzzy logic consists of the following components. Mar 17, 2020 fuzzy logic has been applied to various fields, from control theory to ai. How to provide costeffective strategies for software testing has been one of the research. Fuzz testing describes system testing processes that involve a randomized or distributed approach. Modeling software testing costs and risks using fuzzy. In this paper, we present an assertionbased testing metrics technique that is based on fuzzy logic. Something similar to the process of human reasoning. Feb 20, 2020 fuzzy logic can be programmed in a situation where feedback sensor stops working. However, adding fuzzy logic to the pso would have extra computational requirements. And these rules or conditions would act as fuzzy sets which therein helps in evaluating trading decisions. This programmers guide contains the software design for the new and modified code, the. Fuzzy logic is not always correct, so the results are based on assumptions and may not be widely accepted. Optimizing software testing using fuzzy logic in aspect. Pdf on adaptive testing with fuzzy logic victor garcia.

Fuzzy logic are extensively used in modern control systems such as expert systems. When an exact match is not found for a sentence or phrase, fuzzy matching can be applied. Research in testing has received considerable attention in the last two decades 2,8,20,14. What is the role of fuzzy logic in algorithmic trading. Modeling software testing costs and risks using fuzzy logic paradigm. Developing a reliable software system, several issues need to be addressed. We estimate the quality cost taking place during the software development for an upgraded avionic suite in a fighter aircraft and demonstrate that applying fuzzy logic methodology can yield results comparable to probabilistic calculations less than 4% difference in each of five vvt cost categories. Testing of graphical user interfaces guis was a neglected research area till last decade 4. The main goal of the proposed technique is to enhance the. The program is then monitored for exceptions such as crashes, failing builtin code assertions, or potential memory leaks.

This is the set of rules along with the ifthen conditions that are used for making decisions. Software testing process is time consuming and costly, so the size of test suite plays an important role. The paper deals with the features of the software testing effort ste estimation problem by proposing a novel fuzzy model by integrating cocomo, fuzzy logic and weighing techniques, test effort drivers teds into a single platform. Using fuzzy logic techniques for assertionbased software testing metrics. Fuzzy logic systems software free download fuzzy logic systems. 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. Sep 11, 2008 automated tools are essential to software development. Fuzzy logic are used in natural language processing and various intensive applications in artificial intelligence. This paper makes an attempt to estimate reliable software testing effort using fuzzy logic. However, one issue of paramount importance in software testing the intrinsic imprecise and uncertain relationships within testing metrics is left unaddressed. But, modern developments in fuzzy logic have reduced the number of rules in the rule base. Implementation of regression testing using fuzzy logic.

M, faridabad, haryana abstract software testing is one of the most important. Fuzzy logic is a fascinating area of research because it does a good job of trading off between significance and precision something that humans have been managing for a very long time. So far it helped in detection of significant software bugs in dozens of major free software projects, including x. Software testing optimization through test suite reduction. Warm and fuzzy stickyminds stickyminds software testing. You can use fuzzy logic toolbox software with matlab technical computing software as a tool for solving problems with fuzzy logic. Fuzzy cause effect models of software testing artificial. The work presents the use of fuzzy logic to develop an expert system, capable of selecting the test cases retaining the effectiveness and efficiency while at the same time reducing the number of test cases. In this paper, we develop appropriate fuzzy logic models and utilize similar raw data to compute quality costs under a fuzzy logic paradigm i. Pdf how to provide costeffective strategies for software testing has been one of the research focuses in software engineering for a long time.

Modeling software testing costs and risks using fuzzy logic. Request pdf a fuzzy logic based approach for software testing. This is a test of the equipment before the packexpo 2003. It professionals often use the term to talk about efforts to stress test applications by feeding random data into them in order to spot any errors or hangups that may occur. Using fuzzy logic in test case prioritization for regression testing.

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