System for automatic generation of logical formulas

The satisfiability problem (SAT) is one of the classical and also most important problems of the theoretical computer science and has a direct bearing on numerous practical cases. It is one of the most prominent problems in artificial intelligence and has important applications in many fields, such as hardware and software verification, test-case generation, AI planning, scheduling, and data structures that allow efficient implementation of search space pruning. In recent years, there has been a huge development in SAT solvers, especially CDCL-based solvers (Conflict-Driven Clause-Learning) for propositional logic formulas. The goal of this paper is to design and implement a simple but effective system for random generation of long and complex logical formulas with a variety of difficulties encoded inside. The resulting logical formulas, i.e. problem instances, could be used for testing existing SAT solvers. The entire system would be widely available as a web application in the client-server architecture. The proposed system enables generation of syntactically correct logical formulas with a random structure, encoded in a manner understandable to SAT Solvers. Logical formulas can be presented in different formats. A number of parameters affect the form of generated instances, their complexity and physical dimensions. The randomness factor can be entered to every generated formula. The developed application is easy to modify and open for further extensions. The final part of the paper describes examples of solvers’ tests of logical formulas generated by the implemented generator.

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Test Case Generation Using Progressively Refined Genetic Algorithm for Ajax Web Application Testing

Recent Patents on Computer Science ◽

10.2174/2213275911666181004142946 ◽

2018 ◽

Vol 11 (4) ◽

pp. 276-288

Author(s):

Anuja Arora

Keyword(s):

Genetic Algorithm ◽

Web Application ◽

Test Case Generation ◽

Test Case ◽

Web Application Testing

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Performance of Enhanced Multiple-Searching Genetic Algorithm for Test Case Generation in Software Testing

Mathematics ◽

10.3390/math9151779 ◽

2021 ◽

Vol 9 (15) ◽

pp. 1779

Author(s):

Wanida Khamprapai ◽

Cheng-Fa Tsai ◽

Paohsi Wang ◽

Chi-En Tsai

Keyword(s):

Genetic Algorithm ◽

Software Testing ◽

Random Search ◽

Automatic Generation ◽

Superior Performance ◽

Test Case Generation ◽

Test Case ◽

Test Cases ◽

Network Systems ◽

Routing Problem

Test case generation is an important process in software testing. However, manual generation of test cases is a time-consuming process. Automation can considerably reduce the time required to create adequate test cases for software testing. Genetic algorithms (GAs) are considered to be effective in this regard. The multiple-searching genetic algorithm (MSGA) uses a modified version of the GA to solve the multicast routing problem in network systems. MSGA can be improved to make it suitable for generating test cases. In this paper, a new algorithm called the enhanced multiple-searching genetic algorithm (EMSGA), which involves a few additional processes for selecting the best chromosomes in the GA process, is proposed. The performance of EMSGA was evaluated through comparison with seven different search-based techniques, including random search. All algorithms were implemented in EvoSuite, which is a tool for automatic generation of test cases. The experimental results showed that EMSGA increased the efficiency of testing when compared with conventional algorithms and could detect more faults. Because of its superior performance compared with that of existing algorithms, EMSGA can enable seamless automation of software testing, thereby facilitating the development of different software packages.

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Enterprise WAE: A Lightweight UML Extension for the Characterization of the Presentation Tier of Enterprise Applications with MDD-Based Mockup Generation

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s0218194017500486 ◽

2017 ◽

Vol 27 (08) ◽

pp. 1291-1331

Author(s):

Humberto Cortés ◽

Antonio Navarro

Keyword(s):

Code Generation ◽

Web Application ◽

Service Oriented Architecture ◽

Low Cost ◽

Unified Modeling Language ◽

Automatic Generation ◽

Role Based Access Control ◽

Enterprise Applications ◽

Uml Extension ◽

Automatic Code

Nowadays, the Unified Modeling Language (UML) is the most successful notation for the design of object-oriented applications. However, plain UML is not enough to characterize the web presentation tier of enterprise applications, including the navigational, structural and role-based access control (RBAC) features present in these applications. In this paper, we present Enterprise Web Application Extension (E-WAE), a lightweight UML extension for the modeling of these elements, which permits the inclusion of multitier, Service-Oriented Architecture (SOA) and security design-level patterns in the models. Our approach follows a Model-Driven Development (MDD) approach, which enables the automatic generation of intermediate platform-specific models and automatic code generation for JavaServer Faces (JSF) and Active Server Pages.NET Model-View-Controller (ASP.NET MVC) frameworks. In addition, this generated code can be used as a low-cost mockup for early client validation of the navigational, structural and RBAC features of enterprise applications. E-WAE has been used with different applications. In this paper, we refer to the checkout process in the Amazon website, the delete resources use case in OdAJ2EE, an educational application developed by us, and the US Library of Congress Online Catalog search facility as examples of its applicability.

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Advanced search space pruning with acoustic look-ahead for WFST based LVCSR

2013 IEEE International Conference on Acoustics, Speech and Signal Processing ◽

10.1109/icassp.2013.6638965 ◽

2013 ◽

Cited By ~ 2

Author(s):

David Nolden ◽

Ralf Schluter ◽

Hermann Ney

Keyword(s):

Search Space ◽

Look Ahead ◽

Advanced Search ◽

Search Space Pruning

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Improved Accuracy for Automated Communication Pattern Characterization Using Communication Graphs and Aggressive Search Space Pruning

Programming and Performance Visualization Tools - Lecture Notes in Computer Science ◽

10.1007/978-3-030-17872-7_3 ◽

2019 ◽

pp. 38-55 ◽

Cited By ~ 2

Author(s):

Philip C. Roth

Keyword(s):

Search Space ◽

Communication Pattern ◽

Communication Graphs ◽

Search Space Pruning ◽

Improved Accuracy

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Cloud based Agile Methodology Test Automation for Web Application by Using Tanh Activated Clustering and Classification Model (TACC) in Machine Learning

Webology ◽

10.14704/web/v18si05/web18290 ◽

2021 ◽

Vol 18 (Special Issue 05) ◽

pp. 1137-1157

Author(s):

V. Vamsi Krishna ◽

G. Gopinath

Keyword(s):

Web Application ◽

Web Applications ◽

Cost Effective ◽

Daily Basis ◽

Automatic Testing ◽

Classification Model ◽

Test Case ◽

Test Automation ◽

The Status ◽

Clustering And Classification

Automatic functional tests are a long-standing issue in software development projects, and they are still carried out manually. The Selenium testing framework has gained popularity as an active community and standard environment for automated assessment of web applications. As a result, the trend setting of web services is evolving on a daily basis, and there is a need to improve automatic testing. The study involves to make the system to understand the experiences of previous test cases and apply new cases to predict the status of test case using Tanh activated Clustering and Classification model (TACC). The primary goal is to improve the model's clustering and classification output. The outcomes show that the TACC model has increased performance and demonstrated that automated testing results can be predicted, which is cost effective and reduces manual effort to a greater extent.

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Prediction of Caption and Emoji of an Image using Deep Learning

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1472.0982s1119 ◽

2019 ◽

Vol 8 (2S11) ◽

pp. 3721-3724

Keyword(s):

Deep Learning ◽

Social Networking ◽

Web Application ◽

Automatic Generation ◽

Application Framework ◽

Challenging Problem ◽

Artificial Intelligence Research ◽

Learning Techniques ◽

User Friendly ◽

Visually Impaired Persons

With the invention of deep learning, there is a good progress in image classification. But automatic generation of captions for images is still a challenging problem and is in the initial stages of artificial intelligence research. Automatic description of images has applications in social networking and will be useful to visually impaired persons. This paper concentrates on designing a user-friendly web application framework which can predict the caption of an image using deep learning techniques. The verbs and objects present in the caption are used for forming the emoji and for predicting the major color of the image

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Test Case Generation for Data Flow Testing using Cuckoo Search Algorithm

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1377.0982s1119 ◽

2019 ◽

Vol 8 (2S11) ◽

pp. 2953-2964

Keyword(s):

Data Flow ◽

Search Algorithm ◽

Fitness Function ◽

Cuckoo Search ◽

Automatic Generation ◽

Cuckoo Search Algorithm ◽

Test Case ◽

Stochastic Algorithm ◽

Data Flow Testing ◽

Work Done

Software testing consumes the major portion of the total efforts required for software development. This activity is very time consuming and labor intensive. It is very hard to do testing in optimal manner. In this paper a new approach is proposed, which uses the nature inspired stochastic algorithm called Cuckoo Search Algorithm (CSA) for the automatic generation of test data for data flow testing. This approach considers all def-use as test adequacy criteria. For assistance to CSA in the state space a new fitness function is also proposed by using the concept of dominator tree and branch distance in a CFG. To validate the proposed approach experiments are carried out on 10 benchmarked programs and findings are contrasted with earlier work done in this domain. Further in order to prove that proposed approach performs better than the above mentioned approaches a statistical difference test (T-test) is also performed.

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