Genetic algorithm secure procedures algorithm to manage data integrity of test case prioritization methodology

Test case prioritization includes testing experiments in a request that builds the viability in accomplishing some execution objectives. The importance amongst the most imperative testing objectives is the fast rate of fault recognition. Test case ought to run in a request that extends the likelihood of fault discovery furthermore that detects the most serious issues at the early stage of testing life cycle. In this paper, we develop and prove the necessity of Component-Based Software testing prioritization framework which plans to uncover more extreme bugs at an early stage and to enhance software product deliverable quality utilizing Genetic Algorithm (GA) with java decoding technique. For this, we propose a set of prioritization keys to plan the proposed Component-Based Software java framework. In our proposed method, we allude to these keys as Prioritization Keys (PK). These keys may be project size, scope of the code, information stream, and bug inclination and impact of fault or bug on overall system, which prioritizes the Component-Based Software framework testing. The integrity of these keys was measured with implementation of key assessment metric called KAM that will likewise be ascertained. This paper demonstrates how software testing can be efficient with management of data integrity factor to avoid major security issues. One of the main advantages of our approach is that domain specific semantics can be integrated with the data quality test cases prioritization, thus being able to discover test feed data quality problems beyond conventional quality measures.

Software testing is a very important and crucial phase of software development life cycle. In order to develop good quality software, the effectiveness of the software has been tested. Test cases and test suites are prepared for testing, and it should be done in minimum time for which test case prioritization and optimization techniques are required. The main aim of test case prioritization is to test software in minimum time and with maximum efficiency, so for this there are many techniques, and to develop a new or better technique, existing techniques should be known. This paper presents a review on the techniques of test case prioritization and optimization. This paper also provides analysis of the literature available for the same.

In the early 1990’s, various investigations were launched into higher education policies for post-apartheid South Africa. It was in these debates that the South African Post Secondary Education (SAPSE) funding formula was established. It was later established that it was a flawed document as suggested by Bunting (1994:141-149) and cited by Cloete, Maassen, Fehnel, Moja, Gibbon and Perold (2007:93). The SAPSE funding framework which was established in 1982 for the historically White universities applied throughout the late 1980s and early 1990s to all other universities and technikons, was eventually abolished. This was essentially an apartheid funding framework and it could not be used in the current transformed higher education system. The New Funding Framework (2003) gives advantage to comprehensive and traditional universities. It is also graduate output driven. The HEMIS transformed system is committed to equity and strong linkages with national development needs. It was argued by most stakeholder Institutions that with the abolition of the SAPSE funding framework, it would result in major benefits for some groups of institutions and equate to major costs for others. Thus, the significance of this study is to ensure an effective and efficient way for the data to be maintained in order to support the mission and vision of the Durban University of Technology. Bitzer (2009:354) states that South African universities have become highly unpredictable. Universities have moved from an isolated, divided system in the apartheid era toward a single coordinated system. This system has higher levels of participation and responsiveness. Yet it is within a developing economy and poor quality of primary and secondary education that South African higher education therefore faces a multitude of challenges. Bitzer (2009:354) further explains how conditions of unpredictability further worsens the complexities of planning, policy setting and decision making which then impacts negatively on corporate governance and management activities. The purpose was to investigate data management as a strategic information tool and its importance at the Durban University of Technology. The problem revolved around, inter alia, data management and accuracy as structured interventions impacting sound decision making. The research design adopted a quantitative methodological approach that used a precoded self administered questionnaire. The empirical component involved a survey method considering that it was an in-house investigation where the target population equated to 174 respondents. A significant 74% response rate was obtained using the personal method of data collection. Several hypotheses were formulated relating to data quality initiatives, data owners and their responsibility and frequency of data analysis in order to determine accuracy. These were tested using the Pearson chi-square test and data that was analyzed to determine frequencies and percentages of responses. The data was analyzed using the computerized Statistical Program for Social Sciences (SPSS) program. A highly significant finding was that 95.31% of the respondents strongly agreed that data management and integrity is of utmost importance at the Durban University of Technology. One recommendation suggests that for the Durban University of Technology to manage its data as an asset, a policy on data integrity and integration policy should be developed and implemented. Another recommendation highlighted that staff should strive to attain proper classification on he database, considering that this directly impacts on the accuracy of the HEMIS submissions to the Ministry of Education for the state allocated subsidy. The study concludes with directions for further research as well. DOI: 10.5901/mjss.2014.v5n15p313

The purpose of this study was to investigate data management as a strategic information tool and its importance at the Durban University of Technology. The problem revolved around, inter alia, data management and data accuracy as structured interventions impacting on sound decision making. There were many challenges identified with regard to data management at the Durban University of Technology. The research design adopted a quantitative methodological approach that was used for collecting data through the use of a precoded self administered questionnaire. The empirical component involved a survey method considering that in was an in-house investigation and the target population equated to only 174 respondents. A significant response rate of 74% was obtained using the personal method for the data collection. Several hypotheses were formulated relating to data quality initiatives, data owners and their responsibility and frequency of data analysis in order to determine accuracy. These were tested using the Pearson chi-square test as well as data that was analyzed to determine frequencies and percentages of responses. The data was analyzed using the computerized Statistical Program for Social Sciences (SPSS) program. There were some significant findings that emerged from the empirical analysis. A highly significant finding was that 95.31% of the respondents strongly agreed that data management and integrity is of utmost importance at the Durban University of Technology. One of the recommendation suggest that an imperative for the Durban University of Technology to manage its data as an asset, a policy on data integrity and integration policy should be developed and implemented. Another recommendation highlighted and staff should strive to attain proper classification on the database, considering that this directly impacts on the accuracy of the HEMIS submissions to the Ministry of Education for the state allocated subsidy. The study concludes with directions for further research as well.

Test case prioritization technique aims to improve test efficiency rate by sorting test cases according to some specific criteria. Requirements play an important role throughout software testing. This paper proposes a test case prioritization method based on requirement correlations. Prioritization of requirements is defined by the users and the developers. This technique focuses on requirements with detected faults after the last regression testing. By readjusting prioritization of fault-related requirements, it can optimize the order of test cases. Experimental results show that this technique exactly contributes to achieving high testing efficiency.

Software testing, although once considered a liability has evolved into a necessity over the years and now it has become the most important part of the software engineering process. However, the problem with Software Testing is the amount and the magnitude of the tasks which starts with the execution of simple test cases, gradually increasing in number and complexity eventually reaching incomprehensible proportion. The dynamism in software testing compounds the problem further. It could be changing requirements, different testing methodologies or variations in approaches. This makes it necessary to derive some metrics to evaluate the constraints on what should be tested and to what extent and which test cases should be prioritized over others to maximize the coverage with least efforts. The aim of this paper is to come up with something simpler, logical, quantitative, and convincing in results.

HSP: A hybrid selection and prioritisation of regression test cases based on information retrieval and code coverage applied on an industrial case study

Regression testing is an important and costly strategy in software testing. To decrease its cost, many methods have been proposed including the test case prioritization methods. The aim of the prioritization methods is to define an ideal order of test cases that allows for higher coverage and early fault detection with minimal number of executed test cases. However, the problem with most of the existing test case prioritization methods is the random sorting of test cases when two or more test cases record equal priority values. In this paper, the effectiveness of an enhanced weighted method using a unique priority value, UniVal, is proposed. Unival prioritizes test cases based on code coverage criteria with information from history of previous executions. In addition, a controlled experiment was executed, and the results were statistically analyzed to assess the effectiveness of the proposed method. The results indicates better performance with regard to prioritize test cases and achieve higher APFD values.  Â

Data management in always-on enterprise information systems is an important function that must be governed, that is, planned, supervised, and controlled. According to Data Management Association, data management is the development, execution, and supervision of plans, policies, programs, and practices that control, protect, deliver, and enhance the value of data and information assets. The challenges of successful data management are numerous and vary from technological to conceptual and managerial. The purpose of this chapter is to consider some of the most challenging aspects of data management, whether they are classified as data continuity aspects (e.g., data availability, data protection, data integrity, data security), data improvement aspects (e.g., coping with data overload and data degradation, data integration, data quality, data ownership/stewardship, data privacy, data visualization) or data management aspect (e.g., data governance), and to consider the means of taking care of them.

A history-based cost-cognizant test case prioritization technique in regression testing

Regression testing is important for maintaining software quality. However, the cost of regression testing is relatively high. Test case prioritization is one way to reduce this cost. Test case prioritization techniques sort test cases for regression testing based on their importance. In this paper, we design and implement a test case prioritization method based on the location of a change. The method consists of three steps: (1) clustering test cases, (2) prioritizing the clusters with respect to the relevance of the clusters to a code change, and (3) test case prioritization within each cluster based on metrics. We propose a metric for measuring test case importance based on Requirement Complexity, Code Complexity, and Code Coverage. To evaluate our method, we apply it on a launch interceptor problem program, and measure the inclusiveness and precision for clusters of test cases with respect to code change in specific test cases. Our results show that our proposed change-based prioritization method increases the likelihood of executing more relevant test cases earlier.

Traceability plays an important role in the development of computing systems, specifically, the complex ones. It provides several benefits to stakeholders and developers during the different phases of the systems development life cycle, including verification & validation and maintenance. Unfortunately, there are very few works in literature addressing the concept of traceability in multi-agent systems development methodologies. Having an incremental and iterative process, the well-known PASSI (Process for Agent Societies Specification and Implementation) methodology needs an explicit traceability in order to facilitate the understanding of the MAS under development and to better manage the changes occurring during the development process. In addition, it can lead to a requirement-based verification & validation. In this paper, we propose a new traceability meta-model for the PASSI methodology by introducing explicit traceability links of functional requirements through the various phases of the development life cycle.

Software metrics program for risk assessment

Test case prioritization techniques attempt to reorder test cases in a manner that increases the rate at which faults are detected during regression testing. Coverage-based test case prioritization techniques typically use one of two overall strategies: a total strategy or an additional strategy . These strategies prioritize test cases based on the total number of code (or code-related) elements covered per test case and the number of additional (not yet covered) code (or code-related) elements covered per test case, respectively. In this article, we present a unified test case prioritization approach that encompasses both the total and additional strategies. Our unified test case prioritization approach includes two models ( basic and extended ) by which a spectrum of test case prioritization techniques ranging from a purely total to a purely additional technique can be defined by specifying the value of a parameter referred to as the f p value. To evaluate our approach, we performed an empirical study on 28 Java objects and 40 C objects, considering the impact of three internal factors (model type, choice of f p value, and coverage type) and three external factors (coverage granularity, test case granularity, and programming/testing paradigm), all of which can be manipulated by our approach. Our results demonstrate that a wide range of techniques derived from our basic and extended models with uniform f p values can outperform purely total techniques and are competitive with purely additional techniques. Considering the influence of each internal and external factor studied, the results demonstrate that various values of each factor have nontrivial influence on test case prioritization techniques.

Integrating security at each phase of the software Development Life cycle (SDLC) has become an urgent need. Moreover, security must not be overlooked at early phases of SDLC. This helps to minimize cost and efforts for later phase of the life cycle. In addition, software security metrics are the tools to judge level of security of software. Without the use of the metrics, no one can ensure the usefulness of any approach which claims to improve security of the software. The paper presents a phase-wise review of security metrics and the issues in their adaptation. Though there are security metrics available for each phase of the software development life cycle, their usefulness in the software industry or in research is in question without their validation. In addition, a concrete research is needed to develop security metrics at early phases of software development life cycle.