Context: Cross-site scripting (XSS) is a security vulnerability that affects web applications. It occurs due to improper or lack of sanitization of user inputs. The security vulnerability caused many problems for users and server applications. Objective: To conduct a systematic literature review on the studies done on XSS vulnerabilities and attacks. Method: We followed the standard guidelines for systematic literature review as documented by Barbara Kitchenham and reviewed a total of 115 studies related to cross-site scripting from various journals and conference proceedings. Results: Research on XSS is still very active with publications across many conference proceedings and journals. Attack prevention and vulnerability detection are the areas focused on by most of the studies. Dynamic analysis techniques form the majority among the solutions proposed by the various studies. The type of XSS addressed the most is reflected XSS. Conclusion: XSS still remains a big problem for web applications, despite the bulk of solutions provided so far. There is no single solution that can effectively mitigate XSS attacks. More research is needed in the area of vulnerability removal from the source code of the applications before deployment.

It is only less than a decade that agile SD methods were introduced and got popular steadily. The defined values in these methods and their outcomes have motivated many software producers to use these methods. Since migration from traditional software development methods to agile methods is growing highly, managers of the companies should be aware of problems, hindrances and challenges they may face with during the agile transformation process. This study focused on challenges which companies may face with and it is necessary that managers think about solving them. Classifying them into four main categories; organization and management, people, process and tools are the areas that challenges have been seen in recent studies.

Abstract-Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. The problems of slow and premature convergence to suboptimal solution remain an existing struggle that GA is facing. Due to lower diversity in a population, it becomes challenging to locally exploit the solutions. In order to resolve these issues, the focus is now on reaching equilibrium between the explorative and exploitative features of GA. Therefore, the search process can be prompted to produce suitable GA solutions. This paper begins with an introduction, Section 2 describes the GA exploration and exploitation strategies to locate the optimum solutions. Section 3 and 4 present the lists of some prevalent mutation and crossover operators. This paper concludes that the key issue in developing a GA is to deliver a balance between explorative and exploitative features that complies with the combination of operators in order to produce exceptional performance as a GA as a whole.Index Terms-Crossover operator, mutation operator, exploitation, exploration. I. INTRODUCTIONThe main search operator in Genetic algorithms (GA) is the crossover operator which equally as significant as mutation, selection and coding in GA. The crossover operator functions primarily in the survey of information that is accessible through the search space, which inadvertently improves the behavior of the GA. On another note, mutation is a secondary operator. It functions to alter the genes of the offspring. A mutator will diversify the existing population and this inadvertently allows GAs to exploit promising areas of the search space thus avoiding local solutions [1]. Some of the mutation operators are designed to explicitly overcome certain types of issues over others [2]. The performance among all the comparative of GA operators are easily validated and compared through unbiased test problems from the literature, which are diverse in properties in terms of complexity and modality. This study substantially contributes in reviewing some prevalent mutation and crossover operators. The operators maintain a good balance between explorative and exploitative strategies while manufacturing the optimum GA solutions. II. ACHIEVING EXPLORATION AND EXPLOITATION IN GENETIC ALGORITHMA crossover or mutation can function as an exploration or exploitation operator [3], [4]. Although optimization algorithms with higher degree of exploitation may have Manuscript received August 30, 2016; revised December 8, 2016. Siew Mooi Lim is with University Malaysia of Computer Science and Engineering, Malaysia (e-mail: limsm66@gmail.com).higher convergence speed, the challenge lies in locating the optimal solution and chances are it may not get past a local optimum. On the other hand, algorithms that favor exploration over exploitation might consume more time in locating the global optimum, that is, coincidentally, due to its less sophisticated candidate solutions. A comprehensive survey in exploratio...

Abstract

Problem statement: E-learning is gaining more acceptance as days pass because it provides learning opportunity any time and in any place. Different people have different preferences in terms of learning style such as reading text, listing audio or video, speaking and communication. To support these different learning preferences, there is need for multiple e-learning delivery methods and teaching techniques. Furthermore, there are many stakeholders of e-learning systems such as system developers, administrators, instructors, instructional designers, multimedia designers, online facilitators, independent evaluators. Whose views are important indicators for a complete e-learning system evaluation, but the most important views of e-learning quality are user view, developer's view and manger's view. Approach: The main aim of this study is to propose a new technique to evaluate e-learning website quality from developer's view. To achieve our objective an extensive study on related resources was conducted. Our technique adopts the weights of quality characteristics which are obtained by carefully selected questionnaires' from professional developers. We also present the evaluation process using AHP technique and the result of trial evaluation for validation of our technique Result: We proposed four quality characteristics named Service Content, System Functionality, Information Technology and System Reliability. We further, proposed 11 subcharacteristics with its attributes by following the structure of standard IOS/IEC 912. Conclusion: Our results show that the proposed technique could be useful and effective for ensuring that high quality systems are developed.