Iyad Alazzam

A Systematic Literature Review on Software-Defined Networking

Software-Defined Networking (SDN) is a recently evolving networking architecture that focuses on the separation of control and data planes. Unlike traditional switches, SDN switches include flow tables that are remotely controlled by a separate software application, the controller. SDN is not completely new; it formulates an architecture on top of several good practices. In this paper, we examined the obtainable knowledge about SDN through conducting a systematic literature review (SLR) to evaluate the current SDN state of the art in terms of research tracks, publications, trends, etc. We systematically evaluate research in SDN based on questions formulated for this purpose. The results present outline information about the most active research areas, tools, security issues, obstacles, limitations, strengths, and opportunities in SDN.

Feature-Based Test Focus Selection Technique Using Classes Connections Weight

Testing could cost more than fifty percent of all development cost, particularly integration testing consumes around eighty percent of testing cost. Integration testing aims to discover errors in the connections among classes which are collaborate and communicate in order to provide specific services. Though, testing all connections among classes is impractical because of the cost, effort and time constraints. Test focus selection might help testers to concentrate on the main and vital connections among classes which it could be the most error prone ones. The authors proposed approach amalgamates the static and dynamic analysis in order to detect, trace, and weight the connections among classes through method level communications. Their approach harnessed an open source tracing tool MUTT. The MUTT allows them to return all the methods in all classes that have been called respecting to any specific feature which has triggered by the system user. The experimental results reveal how the proposed approach achieves good mutation testing score on the systems under study.

Software Design Principles to Enhance SDN Architecture

SDN as a network architecture emerged on top of existing technologies and knowledge. Through defining the controller as a software program, SDN made a strong connection between networking and software engineering. Traditionally, network programs were vendor specific and embedded in hardware switches and routers. SDN focuses on isolation between control and forwarding or data planes. However, in the complete SDN network, there are many other areas (i.e. CPU, memory, hardware, bandwidth and software). In this paper, we propose extending SDN architecture and propose isolation layers with the goal of improving the overall network design. Such flexible architecture can support future evolution and changes without the need to significantly change original components or modules.

Regression Test-Selection Technique Using Component Model Based Modification: Code to Test Traceability

Regression testing is a safeguarding procedure to validate and verify adapted software, and guarantee that no errors have emerged. However, regression testing is very costly when testers need to re-execute all the test cases against the modified software. This paper proposes a new approach in regression test selection domain. The approach is based on meta-models (test models and structured models) to decrease the number of test cases to be used in the regression testing process. The approach has been evaluated using three Java applications. To measure the effectiveness of the proposed approach, we compare the results using the re-test to all approaches. The results have shown that our approach reduces the size of test suite without negative impact on the effectiveness of the fault detection.

Effective pair programming practice: toward improving student learning in software engineering class

Pair programming is one of the software development practices in which two programmers working together in partnership using one computer, cooperating with each other on the same problem. Previous research indicates that the pair programming show positive impact on the quality of produced product on the team attitudes and feeling. A formal pair programming experiments were conducted at Yarmouk University to assess and evaluate empirically the impact of pair programming in improving the learning effectiveness, efficiency, and gratification of students in software engineering course. Results reveal that students’ gratification, efficiency and effectiveness are increased when pair programming is used. Moreover, this paper shows experiment results about the compatibility between pairs. The results indicate that students who pair based on their skills are more compatible than the students who pair with different skills.

Software fault proneness prediction: a comparative study between bagging, boosting, and stacking ensemble and base learner methods

Modules with defects might be the prime reason for decreasing the software quality and increasing the cost of maintenance. Therefore, the prediction of faulty modules of systems under test at early stages contributes to the overall quality of software products. In this research three symmetric ensemble methods: bagging, boosting and stacking are used to predict faulty modules based on evaluating the performance of 11 base learners. The results reveal that the defect prediction performance of the base learner classifier and ensemble learner classifiers is the same for naive Bayes, Bayes net, PART, random forest, IB1, VFI, decision table, and NB tree base learners, the case was different for boosted SMO, bagged J48 and boosted and bagged random tree. In addition the results showed that the random forest classifier is one of the most significant classifiers that should be stacked with other classifiers to gain the better fault prediction.

The impact of using pair programming: a case study

Several studies tried to evaluate the impact of using pair programming in computer educational courses or in actual programming projects in the industry. We studied the effect of pair programming practice on the performance of students who do not like and face problems with understanding programming courses through conducting a case study of several programming tasks in third-level practical programming course using individual and pair programming options. We tried to evaluate using pairs of students where one has very good programming skills unlike the other pair who suffers problems in programming. We also conducted a comparison study with papers in the area of pair programming to compare the different approaches that are used in evaluating pair programming practices. In computer programming education, pair programming can be used as part of the education, helping students learn from each other especially those who do not like and face obstacles in learning programming.

Combined Source Code Approach for Test Case Prioritization

Regression testing is an activity in the software testing process to ensure the software is validated and verified after modification occurred on software. It is costly process procedure which has been expected to reach half cost of the software maintenance cost. Many techniques and approaches have been used in regression testing process to enhance the efficiency and effectiveness of regression testing process. Such as test case reduction, test case selection, test case prioritization and retest all. Test case prioritization has been used in regression testing to increase the effectiveness through selecting the most vital test case that has the ability in finding and uncovering errors in the system under test. This paper has introduced a new algorithm for prioritizing test cases in test suite that is based on method and line of code coverage. Test cases which cover the most methods and line of code are more effective and efficient in finding errors.

Design patterns detection based on its domain

Software maintenance is an important issue during the software design life cycle, especially, in late stages. Frequent changes in the software system with lack of documentation lead to the increase in the cost of maintenance. For this reason an important step for software maintenance is detecting patterns from the source code to provide relevant information that can help in understanding the system design and improve its documentation. Design patterns help maintainers and developers to understand the implementation of any software system which make software maintenance process faster and well-informed. Also it decreases the time and efforts that are needed in learning the software. Detecting patterns is not an easy task because the nature of design patterns. This research introduces a detection process based on software domains. This work is done through collecting five different domains for Java open source code. The dynamic analysis approach is used in extracting patterns. The experimental results showed that there are existing some common patterns between source codes which have the same domain in some source codes.

Software attributes that impact popularity

Marketing schemes of software products involve different types of approaches based on the nature of the software, the target customers, level of complexity, etc. Open source software products in particular, target largely software developers or users with a significant level of technical experience. This drives our project to evaluate the level of popularity for open software products based on internal software attributes or metrics. We collected a dataset of several open source projects. We used the number of downloads as an indicator of software popularity among its target audience or customers. Using different tools, we collected 65 metrics for each software project. Collected software metrics are related to the software size, design quality and complexity. Results showed consistently, that popularity increases when some metrics such as (McCabe Cyclomatic Complexity) increases. Interestingly such metrics usually appear as significant indicators for software complexity and where their high values impact negatively software quality.