scholarly journals Automatic Generation Mechanism of Cause-Effect Graph with Informal Requirement Specification Based on the Korean Language

2021 ◽  
Vol 11 (24) ◽  
pp. 11775
Author(s):  
Woo Sung Jang ◽  
Young Chul (Robert) Kim
Keyword(s):  
Requirement Engineering ◽  
Automatic Generation ◽  
Generation Mechanism ◽  
Test Cases ◽  
Korean Language ◽  
Software Developers ◽  
Informal System ◽  
Requirements Specifications ◽  
System Requirements ◽  
Requirement Specifications

In requirement engineering, an important issue is how to transform and tailor the informal system requirements of users or customers into more structured specification documents, which are then used by the software developers. In addition, it is both challenging and necessary to redefine and analyze, from ill-defined or unknown requirements, specifications correctly and automatically generate test cases with them. There are few kinds of research in Korea for automatically reducing requirement complexity and developing test cases of the Korean language-based requirement specifications. Why do we need requirement simplification? Requirement complexity causes analyzers less readability and low understandability. To do this, we propose the automatic cause-effect generation via a requirement simplification mechanism of informal requirement specifications with the Korean language, which works the following procedures: (1) the automatic simplification of informal requirement sentences, (2) the generation of Condition/Conjunction/Clause Tree (C3Tree) Model, (3) and the Cause-effect generation.

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

Mathematics ◽  
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.

scholarly journals Using Fuzzy Logic in Test Case Prioritization for Regression Testing Programs with Assertions

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ali M. Alakeel
Keyword(s):  
Fuzzy Logic ◽  
Regression Testing ◽  
Test Case ◽  
Test Cases ◽  
Test Case Prioritization ◽  
Software Developers ◽  
Novel Approach ◽  
History Of ◽  
Supporting Tool

Program assertions have been recognized as a supporting tool during software development, testing, and maintenance. Therefore, software developers place assertions within their code in positions that are considered to be error prone or that have the potential to lead to a software crash or failure. Similar to any other software, programs with assertions must be maintained. Depending on the type of modification applied to the modified program, assertions also might have to undergo some modifications. New assertions may also be introduced in the new version of the program, while some assertions can be kept the same. This paper presents a novel approach for test case prioritization during regression testing of programs that have assertions using fuzzy logic. The main objective of this approach is to prioritize the test cases according to their estimated potential in violating a given program assertion. To develop the proposed approach, we utilize fuzzy logic techniques to estimate the effectiveness of a given test case in violating an assertion based on the history of the test cases in previous testing operations. We have conducted a case study in which the proposed approach is applied to various programs, and the results are promising compared to untreated and randomly ordered test cases.

AUTOMATIC GENERATION OF TEST CASES FROM ACTIVITY DIAGRAMS FOR UML BASED TESTING (UBT)

2015 ◽  
Vol 77 (13) ◽  
Author(s):  
Oluwatolani Oluwagbemi ◽  
Hishammuddin Asmuni
Keyword(s):  
Automatic Generation ◽  
Test Cases ◽  
System Testing ◽  
Activity Diagrams ◽  
Model File ◽  
Transition Criteria

Activity diagrams are one of UML behavioural models suitable for system testing because it has the capacity to effectively describe the behaviours of systems under development. In this paper, a technique is proposed that generates test cases from activity diagrams by constructing an activity flow tree (AFT) which stores all the information extracted from the model file of the diagram through the help of a parser. Then, we applied an algorithm to generate test cases from the constructed tree. Test cases were generated based on the elements of activity diagrams such as activity sequences, associated descriptions and conditions. The proposed technique generated accurate test cases that completely tallied with the modeled requirements in the diagram. We utilized all-paths, basic pair paths, conditions, branches and transition criteria for generating test cases using ATM withdrawal operation software as a case study.

Automatic Requirement Classification: Tackling Inconsistencies Between Requirements and Regulations

2014 ◽  
Vol 08 (01) ◽  
pp. 47-65 ◽  
Author(s):  
Daniel Ott ◽  
Frank Houdek
Keyword(s):  
Large Scale ◽  
Electronic Control Unit ◽  
Control Unit ◽  
Research Direction ◽  
Requirement Engineering ◽  
Electronic Control ◽  
Passenger Cars ◽  
Engineering Research ◽  
Current Requirement ◽  
Requirement Specifications

Current Requirement Engineering research must face the need to deal with the increasing scale of today's requirement specifications. One important and recent research direction is handling the consistency assurance between large scale specifications and many additional regulations (e.g. national and international norms and standards), which the specifications must consider or satisfy. For example, the specification volume for a single electronic control unit (ECU) in the automotive domain sums up to 3000 to 5000 pages distributed over 30 to 300 individual documents (specification and regulations). In this work, we present an approach to automatically classify the requirements in a set of specification documents and regulations to content topics in order to improve review activities in identifying cross-document inconsistencies. An essential success criteria for this approach from an industrial perspective is a sufficient classification quality with minimal manual effort. In this paper, we show the results of an evaluation in the domain of automotive specifications at Mercedes-Benz passenger cars. The results show that one manually classified specification is sufficient to derive automatic classifications for other documents within this domain with satisfactory recall and precision. So, the approach of using content topics is not only effective but also efficient in large scale industrial environments.

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