Adtha Lawanna

An effective test case selection for software testing improvement

One problem of testing software is selecting the suitable test cases from the test suit regarding the size of the programs. If the size of selected test cases is big, then it can affect the whole performance of software development life cycle. Accordingly, it increases testing time and produce many bugs. Therefore, this paper proposes the improvement of software testing for selecting the appropriate and small number of test cases by considering the amounts of the functions modified, lines of code changed, and numbers of bugs produced after modifying programs. The reason of proposing the software testing improvement model is to prepare effective algorithm, while numbers of bugs are lower than the traditional methods. According to the experimental results, the size of the selected test cases by using the proposed model is less than Retest All, Random, and a Safe Test about 98.70%, 87.86%, and 84.67% respectively. Moreover, the ability of STI is higher than the comparative studies about 1-20 times regarding the number of bugs found after modifying a program.

The digital Thailand strategy and the ASEAN community

The progress of Thailands development needs to be monitored especially in the environment of the ASEAN Economic Community which started formally at the end of the year 2015. Furthermore, Thailand has also established the Thailand 4.0 strategy in alignment with the Thailand 12th Social and Economic Development Plan (2017–2021) and the ASEAN ICT Master Plan in order to drive the Thailand economy into a high‐income country and to be an ASEAN regional center. Because of the efficiency and effectiveness of ICT that can stimulate and support in most work areas, ICT aims to be the foundation of the countrys development in other aspects. Thus, Thailands Ministry of ICT has launched various ICT policies and programs for ICT administrators of different economic sectors because ICT has been considered as an engine of country development, and this causes Thailand to rely more on the adoption of ICT in various sectors. This study focuses on the progression of ICT development and investments, country infrastructures, the quality of the higher education system, business sophistication, and innovation, which are considered as the principal components of Thailand 4.0 strategy. The findings may assist the responsible authorities in both public and private organizations in monitoring, understanding, and expediting strategies and operations in order to achieve the objectives of Thailand 4.0 and to obtain competitive advantages across the ASEAN Economic Community. Furthermore, the findings also help to detect improvement of the Thailands performance with respect to the 5 components development relative to the other ASEAN economies.

Test case design based technique for the improvement of test case selection in software maintenance

Test case selection is the maintenance technique regarding the concept of choosing the appropriate representative of the modified program that has to be changed depending upon the new requirements added for the next modification. The main problem of updating software is the amounts of the test suite that is generated for the tests increases, which can drop the performance of using the new code that added to the previous program. According to this, execution and testing time will increase, including the complexity of integrating the codes also increase. Therefore, the test suite minimization approaches are offered to solve these problems. The objective of proposing the design based technique is to refine the competency of using test case selection to control the large programs by applying four algorithms, which are testing test case, classification, deletion, and selection. The result of determining the size reduction is greater than random selection, general regression technique, and test case prioritization as about 28.00%, 17.00%, and 11.00% approximately.

IT design skills selection for professional development

IT professionals in these days need to obtain multidisciplinary skill sets in order to succeed in their career. Design skill is considered as one of important characteristic for IT professionals. Many researches addressed design skill sets differently. This results in an increasing numbers of design skill items, in which some of those items have their meaning slightly different from each other. These long lists of design skill items can cause to long range of questionnaire. This study evaluates three techniques used for items selection which help reducing the number of skill items but with expect to remain their value within the selected items. The comparative studies used in this work are random selection, statistics selection, and effective coverage-based selection. The study found that the proposed technique provides the most satisfy result comparing to the other two techniques. According to this, the reduction rate by using this model is better than random and statistics algorithms about 47.83% and 34.78% respectively. Moreover, the percent coverage by using the proposed model is higher than the traditional methods approximately 13-26 %.

Test case selection: Vital model for software maintenance

Skills and experiences of choosing the appropriate test cases to represent a test suite for the program modifications deal with steps of preparation, testing bugs and selection methods, while the smallest size is realized. There are selection methods present to solve these problems but the results can be improved to get the satisfied solution. Therefore, this paper prepares the algorithms for handling this situation by proposing the process of testing, demonstrating, removing and selecting the test cases with high efficiency. When compared with the traditional techniques, the proposed model gives better results of size reduction and percent efficiency approximately 44.28%, and 46.27% which are higher than random and regression test selection respectively. While the percentage of finding bugs is smaller than the comparative studies about an average 2.36 times.

An effective model for case-based maintenance in cased-based reasoning systems

Case-based reasoning systems have been applied for machine learning, artificial intelligence, knowledge-based systems and other related fields in order to provide the right solution to the right problem regarding the four processes, which are the process to retrieve, reuse, revise, and retain cases. This paper focuses on the last process because it produces two main problems, which are the size of a case base increase and the ability of preserving the competency decreases. These critical issues are occurring when repeating the cycles of case-based reasoning. Consequently, the case-based maintenance methods are developed to handle the situations. Accordingly, this paper proposes an effective model for case-based maintenance in case-based reasoning systems to give the best results compared with random, utility, footprint, footprint and utility deletion including case addition algorithm. By running the seven comparative studies on ten datasets retrieved from the machine learning repository, especially to study the efficiency of each algorithm in terms of reducing the size of the case base by selecting the small number of case solutions and preserving the competency after the maintenance systems are applied. According to experimental results, the effectiveness of the proposed model for storing the number of case solution gives the lower size of a case base, when compared with the existing techniques about 34.34%-114.84%. Besides, the percentage of adapting solutions for the traditional methods are lower than the proposed model as about 1.12-6.64 times, including the percent solving problem is lower than the effective model approximately 4.73%-33.55%.