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Recently, there has been a significant increase in the number of Artificial Intelligence (AI) systems, software, and components. As a result, it is crucial to evaluate their quality. Quality models for AI have in fact been proposed, but there is a lack of Systematic Mapping Studies (SMS) for quality models in AI systems, software, and components. The goal of this paper is to understand, classify, and critically evaluate existing quality models for AI systems, software, and components. This study conducts an SMS to investigate quality models proposed by various authors in the past. The study only found quality models for AI systems and software. So far, the SMS has revealed no work on AI software component quality models. Finally, the limitations of the quality models and the implications for future research and development efforts are discussed.

Model-based testing is a substantial approach that is based on and involving models. It is well known for achieving test coverage and for generating and executing test cases automatically. The main and core activity of model-based testing is the modelling activity. Models are used to explain and represent the behaviour of the product. The requirement will be translated into models and those models will be used in generating the test cases automatically in model-based testing. The modelling activity clarifies test requirement and contribute to automatic generation and execution of large test suites with tool support. Model-based testing provides numerous advantages in testing; mainly on achieving appropriate test coverage and reduce manual effort and time spent since it can execute the test cases automatically. Despite all the benefit it can provide, there are some drawbacks too. However, the challenges faced can overcome by implementing proper test modelling activity and by adopting a well-versed test management activity. Thus, in this paper, we have studied the existing testing process, the taxonomy of model-based testing and model-based testing steps and proposed an extensive lifecycle for model-based testing with detail activities and steps to be carried out in order to test and validate access control requirement for multi-tenant application.

Misuse case is one of the security requirement elicitation techniques that are easy to use and learn. Unfortunately, the current guideline provided is too general. The process of identifying the misuse case and threats is open for the analyst's interpretation. Lack of knowledge in security threats also can make it worse. These problems can lead to analysis paralysis situation. In this paper, we proposed a catalogue-based guideline to support misuse case techniques to elicit security requirements. This guideline consists of two catalogues used to assist software developers in identifying attacks and threats from a misuse case diagram. We experimented with selected students to evaluate the effectiveness of the guideline in identifying threats and types of threats. We also evaluated the usability of the guideline by conducting experts reviews. Experiment's result shows sufficient evidence that using the misuse case with the proposed catalogue-based guideline is more effective in identifying threats and types of threats than using the misuse case without a guideline. Expert review's result also shows that the catalogue-based guideline is more usable in identifying threats than without using the guideline.

Component-based software development (CBSD) is an alternative approach to constructing software systems that offers numerous benefits, particularly in decreasing the complexity of system design. However, deploying components into a system is a challenging and error-prone task. Model-checking is one of the reliable methods to systematically analyze the correctness of a system. Its brute-force checking of the system’s state space assists to significantly expand the level of confidence in the system. Nevertheless, model-checking is limited by a critical problem called state space explosion (SSE). To benefit from model-checking, an appropriate method is required to reduce SSE. In the past two decades, a great number of SSE reduction methods have been proposed containing many similarities, dissimilarities, and unclear concepts in some cases. This research, firstly, plans to present a review of SSE handling methods and classify them based on their similarities, principle, and characteristics. Second, it investigates the methods for handling SSE problem in the verification process of CBSD and provides insight into the potential limitations, underlining the key challenges for future research efforts.

Although customization plays a significant role in the provision of software as a service (SaaS), delivering a customizable SaaS application that reflects the tenant’s specific requirements with acceptable level of quality is a challenge. Drawing on a pr-developed software customization model for SaaS quality, two fundamental objectives of this study were to determine whether different software customization approaches have direct impacts on SaaS quality, and also to assess the construct reliability and construct validity of the model. A questionnaire-based survey was used to collect data from 244 software professionals with experience in SaaS development. Structural equation modeling was employed to test the construct reliability, construct validity, and research hypotheses. The measurement model assessment suggested that the six-construct model with 39 items exhibited good construct reliability and construct validity. The findings of the structural model assessment show that all customization approaches other than the integration approach significantly influence the quality of SaaS applications. The findings also indicate that both configuration and composition approaches have positive impacts on SaaS quality, while the impacts of the other approaches are negative. The empirical assessment and evaluation of this model, which features a rich set of information, provides considerable benefits to both researchers and practitioners.

An intrusion detection system (IDS) is an active research topic and is regarded as one of the important applications of machine learning. An IDS is a classifier that predicts the class of input records associated with certain types of attacks. In this article, we present a review of IDSs from the perspective of machine learning. We present the three main challenges of an IDS, in general, and of an IDS for the Internet of Things (IoT), in particular, namely concept drift, high dimensionality, and computational complexity. Studies on solving each challenge and the direction of ongoing research are addressed. In addition, in this paper, we dedicate a separate section for presenting datasets of an IDS. In particular, three main datasets, namely KDD99, NSL, and Kyoto, are presented. This article concludes that three elements of concept drift, high-dimensional awareness, and computational awareness that are symmetric in their effect and need to be addressed in the neural network (NN)-based model for an IDS in the IoT.

Background: Landmark-based approaches of two- or three-dimensional coordinates are the most widely used in geometric morphometrics (GM). As human face hosts the organs that act as the central interface for identification, more landmarks are needed to characterize biological shape variation. Because the use of few anatomical landmarks may not be sufficient for variability of some biological patterns and form, sliding semi-landmarks are required to quantify complex shape. Results: This study investigates the effect of iterations in sliding semi-landmarks and their results on the predictive ability in GM analyses of soft-tissue in 3D human face. Principal Component Analysis (PCA) is used for feature selection and the gender are predicted using Linear Discriminant Analysis (LDA) to test the effect of each relaxation state. The results show that the classification accuracy is affected by the number of iterations but not in progressive pattern. Also, there is stability at 12 relaxation state with highest accuracy of 96.43% and an unchanging decline after the 12 relaxation state. Conclusions: The results indicate that there is a particular number of iteration or cycle where the sliding becomes optimally relaxed. This means the higher the number of iterations is not necessarily the higher the accuracy.

The composition mechanisms and interactions of current component models are mostly base on port or function calls from other components. However, in both styles, the number of interactions that depend on the number of ports and method calls may increase dramatically. Hence, to avoid such complexity of composing components and coordination of the interaction among them, a component model and policy to provide a separation between the components and coordinating is needed. This study presents a formal specification of a novel component model for discrete-event and non-blocking component-based systems called PUTRACOM. A new component model, named PUTRACOM is presented in this paper. PUTRACOM supports to develop concurrent software systems with discrete-event. PUTRACOM defines components by two essential features; they are the Observer/Observable unit and a computation unit. These two features allow a component to have fixed behavior without any dependency on other components. The components can be composed using a well-defined set of connectors. PUTRACOM has been formally defined based on the well-defined and sound methods like CSP and RTSs. PUTRACOM provides a way to construct components and coordinate them with a well-founded mechanism. The model defines a set of exogenous connectors and an observer/observable unit to encapsulate components and coordination. In order to illustrate the way of component composition in the proposed model, an example of the control system of a refrigerator is used. Moreover, to evaluate its applicability, the example has been implemented in Colored Petri Net (CPN) tools.

One of the most pertinent applications of image analysis is face recognition and one of the most common genetic disorders is Down syndrome (DS), which is caused by chromosome abnormalities in humans. It is currently a challenge in computer vision in the domain of DS face recognition to build an automated system that equals the human ability to recognize face as one of the symmetrical structures in the body. Consequently, the use of machine learning methods has facilitated the recognition of facial dysmorphic features associated with DS. This paper aims to present a concise review of DS face recognition using the currently published literature by following the generic face recognition pipeline (face detection, feature extraction, and classification) and to identify critical knowledge gaps and directions for future research. The technologies underlying facial analysis presented in recent studies have helped expert clinicians in general genetic disorders and DS prediction.

Despite the benefits of standardization, the customization of Software as a Service (SaaS) application is also essential because of the many unique requirements of customers. This study, therefore, focuses on the development of a valid and reliable software customization model for SaaS quality that consists of (1) generic software customization types and a list of common practices for each customization type in the SaaS multi-tenant context, and (2) key quality attributes of SaaS applications associated with customization. The study was divided into three phases: the conceptualization of the model, analysis of its validity using SaaS academic-derived expertise, and evaluation of its reliability by submitting it to an internal consistency reliability test conducted by software-engineer researchers. The model was initially devised based on six customization approaches, 46 customization practices, and 13 quality attributes in the SaaS multi-tenant context. Subsequently, its content was validated over two rounds of testing after which one approach and 14 practices were removed and 20 practices were reformulated. The internal consistency reliability study was thereafter conducted by 34 software engineer researchers. All constructs of the content-validated model were found to be reliable in this study. The final version of the model consists of 6 constructs and 44 items. These six constructs and their associated items are as follows: (1) Configuration (eight items), (2) Composition (four items), (3) Extension (six items), 4) Integration (eight items), (5) Modification (five items), and (6) SaaS quality (13 items). The results of the study may contribute to enhancing the capability of empirically analyzing the impact of software customization on SaaS quality by benefiting from all resultant constructs and items.

Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. Hence, the algorithm must overcome the problem of dynamic update in the internal parameters or countering the concept drift. However, using neural network-based semi-supervised stream data learning is not adequate due to the need for capturing quickly the changes in the distribution and characteristics of various classes of the data whilst avoiding the effect of the outdated stored knowledge in neural networks (NN). This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). The framework trains the NN on previously labeled data and its knowledge is used to calculate the error of the core online-offline clustering block. The genetic optimization is responsible for selecting the best parameters of the core model to minimize the error. This integration aims to handle the concept drift. We designated this model as hyper-heuristic framework for semi-supervised classification or HH-F. Experimental results of the application of HH-F on real datasets prove the superiority of the proposed framework over the existing state-of-the art approaches used in the literature for sequential classification data with evolving nature.

Background: The application of three-dimensional scan models offers a useful resource for studying craniofacial variation. The complex mathematical analysis for facial point acquisition in three-dimensional models has made many craniofacial assessments laborious. Method: This study investigates three-dimensional (3D) soft-tissue craniofacial variation, with relation to ethnicity, sex and age variables in British and Irish white Europeans. This utilizes a geometric morphometric approach on a subsampled dataset comprising 292 scans, taken from a Liverpool-York Head Model database. Shape variation and analysis of each variable are tested using 20 anchor anatomical landmarks and 480 sliding semi-landmarks. Results: Significant ethnicity, sex, and age differences are observed for measurement covering major aspects of the craniofacial shape. The ethnicity shows subtle significant differences compared to sex and age; even though it presents the lowest classification accuracy. The magnitude of dimorphism in sex is revealed in the facial, nasal and crania measurement. Significant shape differences are also seen at each age group, with some distinct dimorphic features present in the age groups. Conclusions: The patterns of shape variation show that white British individuals have a more rounded head shape, whereas white Irish individuals have a narrower head shape. White British persons also demonstrate higher classification accuracy. Regarding sex patterns, males are relatively larger than females, especially in the mouth and nasal regions. Females presented with higher classification accuracy than males. The differences in the chin, mouth, nose, crania, and forehead emerge from different growth rates between the groups. Classification accuracy is best for children and senior adult age groups.

Sexual dimorphism in Homo-sapiens is a phenomenon of a direct product of evolution by natural selection where evolutionary forces acted separately on the sexes which brought about the differences in appearance between male and female such as in shape and size. Advances in morphometrics have skyrocketed the rate of research on sex differences in human and other species. However, the current challenges facing 3D in the acquisition of facial data such as lack of homology, insufficient landmarks to characterize the facial shape and complex computational process for facial point digitization require further study in the domain of sex dimorphism. This study investigates sexual dimorphism in the human face with the application of Automatic Homologous Multi-points Warping (AHMW) for 3D facial landmark by building a template mesh as a reference object which is thereby applied to each of the target mesh on Stirling/ESRC dataset containing 101 subjects (male = 47, female = 54). The semi-landmarks are subjected to sliding along tangents to the curves and surfaces until the bending energy between a template and a target form is minimal. Principal Component Analysis (PCA) is used for feature selection and the features are classified using Linear Discriminant Analysis (LDA) with an accuracy of 99.01 % which demonstrates that the method is robust.

There is a growing concern among Muslims over the need to ensure Sharia compliance in e-commerce transactions. Because non-conformity to Sharia principles can result in a lack of trust and a barrier for many Muslims to partake in e-commerce transactions. However, there is currently no comprehensive and clearly specified Sharia compliance requirements guideline for e-commerce systems. Therefore, a need to explore and develop a comprehensive guideline for Sharia compliance requirements in e-commerce systems. In this study, an exploratory qualitative study involving eight semi-structured interviews with Sharia compliance scholars/experts was conducted. Consequently, a conventional content analysis of data was carried out with the aid of QSR-NVivo 11. Findings from the study revealed that e-commerce is acceptable and indeed encouraged in Islam so long as it enhances the welfare of society. The fundamental Sharia compliance requirements for e-commerce are adherence to the Maqasid Sharia and the fulfillment of Islamic law of contract obligations. This requires e-commerce systems to be structured towards enhancing the welfare of the society and compliance with the form, contracting parties, and subject matter obligations of Islamic law of contract. Therefore, this study proffers a comprehensive framework of Sharia compliance requirements for e-commerce systems which provides notions that agree with the Quran, Sunnah, and e-commerce best practices. The framework provides a comprehensive but parsimonious guide that would enhance understanding and support the development of Sharia compliant e-commerce systems. Furthermore, it would guide researchers, consumers, vendors, developers, analysts, and regulators with interest in the Sharia compliance e-commerce domain.

Business process models tend to get more and more complex with age, which hurts the ease with which designers can understand and modify them. Few metrics have been proposed to measure this complexity, and even fewer have been tested in the Business Process Execution Language (BPEL) context. In this paper, we present three related experimental studies whose aim was to analyse the ability of four selected structural metrics to predict BPEL process model understandability and modifiability. We used Spearman’s rho and regression analysis in all three experiments. All metrics passed the correlation tests meaning that they can serve as understandability and modifiability indicators. Further, four of the metrics passed the regression test for understanding time implying that they can serve as understandability predictors. Finally, only one metric passed the regression test for modification time implying that it can serve as a modifiability predictor.

In software engineering, formal methods allow the design, modelling and verification of hardware and software systems. Formal methods introduce preciseness, remove ambiguity in specifications, and support the verification of requirements and design properties. Methods and approaches are needed to manage the formal models and handle their complexity. Refinement has been carried out for system artefacts ranging from modelling and design levels like architectures, and state machines to implementation and programming levels like source code. Refinement is a significant way for building complicated systems starting from simple ones by adding features gradually. Refinement has to be understood carefully in the context of formal specification and verification. This article provides a survey on some refinement techniques and methods and in the context of formal methods and software engineering. We believe that this survey sheds a light on the research direction in regards to the refinement of formal methods. This survey also helps formal methods practitioners and users in observing and understanding the advantages and limitations of refinements methods and techniques of various studied formal methods. Accordingly, they can decide which formal method is to be used in modelling systems via refinement or which formal method is to be extended with new concepts and notions to support refinement.

Software needs to deliver acceptable levels of quality, whilst meeting the functional demands of users. This need is gaining more consideration in Enterprise Resource Planning (ERP) and multi-tenant software. This study investigated the effect of software customization on external quality attributes via four pertinent primary studies, which were summarized, aggregated, discussed and presented through a systematic literature review. The primary studies in this review were chosen through the application of inclusion and exclusion criteria to applicable articles published during the period 2000-2016; they were analysed using research questions that focused on software customization, software quality attributes and measures, approaches, and impact results. The results revealed that each primary study had been applied in the context of ERP and demonstrated that different types of customizations can have various effects on particular quality attributes. Accordingly, further research is needed to determine the impact of customization on each external quality attribute.

The software development phase would frequently go through several changes and modifications. These are challenges that the tester of a system needs to face to ensure that the quality of the system aligns with the budget, resources, and time to deliver. Numerous techniques have been proposed to solve these problems and one of them is the test case prioritization (TCP) technique. The TCP technique is widely used for single event test cases. Thus, this paper would like to propose the Multifactor Weightage Approach (MFWA) using combinations of six factors to prioritize event sequence test cases. The percentage of test effort efficiency was used to measure the efficiency of the comparison technique. The results showed that the MFWA was more efficient compared to the random technique in terms of detecting faults earlier.

The increase in the number of open source software (OSS) users have drawn attention to improving usability. Usability is a clear concept that encompassing both task and user characteristics as well as functionality. Usability is an essential factor that affects user acceptance and OSS sustainability, which is considered as the key to the success of the OSS. To some extent, usability is one concern of the larger issue of system acceptability and sustainability. Therefore, usability is an important factor that needs to be considered since the software that is not usable is not going to be sustainable. The objective of this paper is to review researchers' efforts to improve, investigate, and evaluate the usability factor that may affect the OSS acceptability and sustainability and map the research scenery from the articles into a comprehensible structured taxonomy, which would help the researchers to identify different research gaps of this field. A survey of the usability in OSS conducted and 6033 studies identified by a search in four scholarly databases using a query that includes the keywords (usability or learnability or efficiency or satisfaction) and (open source software or OSS). A total of 46 studies are selected. By manually searching in ACM, Springer, and Google Scholar five other studies identified, and thus a total of 51 studies were the final set that includes in this paper. Based on research topics, a taxonomy created and divided into four principal categories which improve OSS usability, analyze OSS usability, evaluate OSS usability, and select and adopt OSS. A comprehensive overview and synthesis of these categories are presented as well. This paper contributes to identifying the possible opportunities and gaps for enabling the participation of interested researchers in this research area. And give possibilities for extending the use of usability research and practices to create more sustainable software. Also, helps in selecting suitable OSS among the

In response to the growing demand for higher quality Voice over IP (VoIP) communication, there are multiple high-speed access links, including Wi-Fi and Long Term Evolution (LTE) for the mobile end-users. The combination of the access links provides a hybrid network environment in which the end-users can switch from one to another, whichever provides a higher level of VoIP quality of service (QoS). Apart from the type of the access link, the VoIP codecs are also another key factor that directly affects the overall QoS of the voice communication. Due to inherent characteristics, different networks have distinct limitations and requirements. Considering these differences, the visualizing and analysing the performance and behaviour of each codec on its underlying network will lead to a proper VoIP codec selection, which in turn will result in optimal voice QoS for the mobile end-users. This study proposes a method to quantify and analyse the performance of different VoIP codecs in a hybrid LTE-802.11ac network in which the mobile end-users have two corresponding network interface cards. The aim is to find the codecs that suit the most for LTE and 802.11ac networks and thereby optimize the QoS of the VoIP communication. The NS3 tool is used to develop and implement a variety of distinct scenarios within which different QoS performance metrics are precisely measured. The obtained results signify the extensive impact of the codecs on the QoS of the voice communication for both LTE and 802.11ac users and also the importance of the VoIP codec selection procedure for each network.

Children with dyslexia are synonymous with having difficulties in learning to read. Dyslexic children commonly encounter visual, auditory and kinesthetic deficits which cause an inability to process the information in their brain despite no visual, hearing and motor impairments. The current teaching approach used is through traditional instruction such as books, flashcards, boards and many more. However, children with dyslexia require a multisensory approach which allows them to utilize all their senses, be it eyes, ears, voice, and tactile, in learning. Tangible interaction has gained a reputation as an alternative approach to bringrichness and intuitiveness of a multimodal using physical tangible objects while interacting with a digital space. In order to provide the appropriate tools for dyslexic children in learning, design guidelines of tangible interaction learning model are established and supported by theories and other related works in the dyslexia domain. In regards to the design guidelines, an initial tangible interaction prototype called DisleksiaBelajar 3dT is going to be developed for children with dyslexia. The prototype may serve as an interactive and supportive tool for dyslexic children to learn Malay language.

Sexual dimorphism in Homo-sapiens is a phenomenon of a direct product of evolution by natural selection where evolutionary forces acted separately on the sexes which brought about the differences in appearance between male and female such as in shape and size. This study investigates sexual dimorphism in human face with the application of Automatic Homologous Multi-points Warping (AHMW) for 3D facial landmark by building a template mesh as a reference object which is thereby applied to each of the target mesh on Stirling/ESRC dataset containing 101 subjects (male = 47, female = 54). The semi-landmarks are subjected to sliding along tangents to the curves and surfaces until the bending energy between a template and a target form is minimal. Principal Component Analysis (PCA) is used for feature selection and the features are classified using Linear Discriminant Analysis (LDA) with an accuracy of 99.01%.

Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challenges facing facial data acquisition in 3D: such as lack of homology and complex mathematical analysis for facial point digitization. This study proposes facial expression recognition in human with the application of Multi-points Warping for 3D facial landmark. The results indicate that Fear expression has the lowest recognition accuracy while Surprise expression has the highest recognition accuracy. The classifier achieved a recognition accuracy of 99.58%.

Over the decade scientists have been researching to know whether face recognition is performed holistically or with local feature analysis which has led to the proposition of various advanced methods in face recognition, especially using facial landmark. The current facial landmark methods in 3D are mathematically complex, contain insufficient landmarks, lack homology and full of localization error due to manual annotation. This paper proposes an Automatic Homologous Multi-Points Warping (AHMW) for 3D facial landmarking, experimented on three datasets using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks) by building a template mesh as a reference object and thereby applies the template to each of the targets on three datasets. The results show that the method is robust with minimum localization error (Stirling/ESRC:0.077; Bosphorus:0.088; and FRGC v2: 0.083).

Cognitive-Behaviour Intervention (CBI) is designed as a suitable intervention for students by identifying cognitive as well as behaviour conditions. Through CBI, the students' learning goals are easier to establish, and the skills related to particular conditions can be developed. Current dyslexia’s learning interventions were mostly developed to tackle cognitive or behaviour conditions separately. Whereas, the students with dyslexia suffer from cognitive deficiencies as well as behaviour challenges, both the conditions are interrelatedly. As a result, students with dyslexia reportedly underperform, lazy, ignorance and stupid due to the inappropriate learning style. In addition, there are very limited works that allow for adaptability in addressing the dynamic states of the student's learning process such as engagement. A study has shown that students’ engagement could be a predictor of good academic performance. Therefore, in this paper, we present the approach to combine both cognitive and behaviour conditions of the students with dyslexia as well as the intervention in our proposed adaptive learning model. The cognitive model senses the student’s difficulties through exercise given while the behaviour model utilises the machine learning model to address the engagement states of the students. Finally, the model intervene by praising effort, hints and changing activity based on the student’s state. The results showed that a promising new way to assists students with dyslexia in their learning.

Dealing with non-functional properties has a great challenge to software engineers for many years. For many years, software engineers are using this properties provide high quality to the software products they developed. This make it possible for engineers to divide their focus of testing non-functional properties according to, the services the software product renders. Although, non-functional properties of software systems are being described as the most important contributors to the success of software systems, study to date revealed that there is no general consensus on the notion of certain classification of NFPs. This study presents results of a study on the investigation conducted on the different classification of Non-Functional Properties (NFP) of software systems.

Software testing is known as a time-consuming process and tied to time limitations and budget. Any modifications during testing may delay the completion timeline of the project once it no longer under control. Due to that reason, various approaches have been proposed to reduce time, cost and resources. Test case prioritization (TCP) is one of them with the goal to ensure faster detection of faults for an ordered test suite, and it is is more effective than the original test suite. In this paper, the researchers proposed a prioritization algorithm for the event sequences test cases based on faults. Weighted priority has been applied to assign a weight for each test case. The aim of this paper is to avoid selecting any random test case more than once if the test case has the same weight. An experiment has been conducted using one subject program taken from the benchmark source for a comparative study. While the Average Percentage of Fault Detected (APFD) has been selected as an evaluation metric to measure the effectiveness of the enSSP technique and the weighted approach technique. The results depict that the weighted approach technique is more effective in terms of detecting faults and more successful in producing a unique weight for each test case.

Tangible Interaction (TI) has shown many benefits in various situations for it provides more direct manipulations and haptic feedback. In addition, TI also provide a more enjoyable learning environment. Despite active research in TI, there is limited research on design learning, particularly associated with the TI for children with dyslexia. Current approaches are found to still depend on traditional multisensory teaching materials. However, some literatures argued that the use of traditional multisensory teaching materials used in the current teaching technique is less attractive, lack sense, offer no feedback such as sound and only rely heavily on the teacher. A preliminary study was conducted to understand better how TI works for children with dyslexia. The study is conducted by the research team using a semi-structured interview and observations with teachers who teach dyslexic children. In this paper, an investigation of the teaching materials and learning approaches used in the Dyslexia Association of Malaysia (DAM) learning centre to support children with dyslexia were studied and analysed. Finally, design guidelines are constructed and proposed based on the data obtained from the study conducted. The design guidelines will be adopted to develop a tangible interaction between the learning model and its prototype for children with dyslexia.

The mechanisms adopted by cellular technologies for user identification allow an adversary to collect information about individuals and track their movements within the network; and thus exposing privacy of the users to unknown risks. Despite efforts have been made by Long Term Evolution LTE toward enhancing privacy preserving capabilities, LTE does not eliminate the possibility of user privacy attacks. LTE is still vulnerable to user privacy attacks. This paper includes an evaluation of LTE security architecture and proposes a security solution for the enhancement of paging procedure privacy in LTE. The solution is based on introducing of frequently changing unrelated temporary mobile subscriber identifiers (TMSI) used for identification. The scheme provides secure and effective identity management in respect to the protection of user privacy in LTE during paging process. The scheme is formally verified using proVerif and proved to provide an adequate assurance of user privacy protection.

Graph-based representations of programs such as control flow graph or dependence graph have been used to support program analysis tasks such as program comprehension and software maintenance. However, in the case of Aspect-Oriented Programming (AOP), such graph representations individually is not enough to represent the features of aspect-oriented programs because it could need to identify the flow of control and the relationship of the data. AOP is a technique for improving modularity by separating crosscutting concerns in software development. In this article, a graph model known as Aspect-Oriented Dependence Flow Graph (AODFG) is proposed to represent the structure of aspect-oriented programs. The graph is formed by combining control flow graph and dependence graph into a single graph representation. As a consequence, more information about dependencies involving the features of AOP, such as join point, advice, aspects, their related constructs and the flow of control are able to be analysed. Effectiveness analysis of AODFG has been conducted in an experiment involving twenty software experts applying the graph on the AspectJ benchmark programs. The findings show that they were very satisfied with AODFG as an effective tools for analysing code.

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.

Software as a Service has become a common model for various business applications. Increasingly, software application development companies have followed this model in delivering their software to their customers. SaaS delivery model is a multi-tenant model which reduces operational cost by increasing the resource sharing of one instance of application among multi customers (commonly named tenants). In this model, SaaS provider is not allowed to provide a copy of application code for each tenant, yet they have to permit each tenant to fulfill their different and varying requirements by enabling them to customize the application. This paper explores SaaS customization and the processes which make up the overall procedure. Accordingly, the Five Ws (who, when, what, where, and why) method is used to capture the core elements of SaaS customization, as well as how customization plays a role for the various SaaS stakeholders to introduce a taxonomy of SaaS customization. This taxonomy could provide guidance on SaaS customization.

In component-based development (CBD), composing components and controlling the interactions among them is not a trivial task. The composition and interaction styles in the current state-of-the-art component-based models mostly are port-to-port connection or method-call based. However, both styles confer complex patterns, since the number of interactions may increase dramatically due to the number of method calls, ports, and connectors. To avoid such complexity, a simple and coherent component model with adequate policies for control is required. In this study, we provide a formal specification for components, composition and interactions issuing in discrete-events and non-blocking component-based systems. Our concurrent component model called PUTRACOM is equipped with Exogenous Connectors as third-party objects for coordination and Observable/Observable Unit (OOU) as a part of components for invocation. These are used to achieve a truly separation between computation and control in order to reduce the complexity that arises in port-to-port connection and method-call based interaction styles. To formally specify our model, we have adopted Communication Sequential Processes (CSP) and Reactive Transition Systems (RTS). The applicability of our model is evaluated using CoCoME case study. We demonstrate how PUTRACOM provides a mechanism to construct independent components and control the interactions between them by well-founded connectors.

Software testing is one of the most vital phases of software development lifecycle that aims to detect software faults. Test case generation dominates the software testing research. SSP is one of many techniques proposed for test case generation. The goal of SSP is to avoid exhaustively testing all possible combinations of inputs and preconditions. The test cases produced by SSP are formed of a sequence of events. For instance, a queue test case might encompass the addition of thirty items onto the queue; deletion of three items, addition of sixty more items, seven deletions and examining the outcome. Notwithstanding perceiving the finite bounds of the queue size, there is an endless engage of sequences along with no upper limit on the sequence’s length. Therefore, the sequence might get lengthy as a result of comprising data states that are redundant. The test suite size is expanded due to the data states redundancies and subsequently, the testing process will become insufficient. Thus, it is a necessity to optimize the SSP test suite by removing the redundant data states. This paper addresses the issue of SSP suite reduction, which part of the process for optimizing test suite produced by the SSP.

Structured query language injection vulnerability (SQLIV) is one of the most prevalent and serious web application vulnerabilities that can be exploited by SQL injection attack (SQLIA) to gain unauthorized access to restricted data, bypass authentication mechanism, and execute unauthorized data manipulation language. Hence, testing web applications for detecting such vulnerabilities is very imperative. Recently, several security testing approaches have been proposed to detect SQL injection vulnerabilities. However, there is no up-to-date comparative study of these approaches that could be used to help security practitioners and researchers in selecting an appropriate approach for their needs. In this paper, six criteria's are identified to compare and analyze security testing approaches; vulnerability covered, testing approach, tool automation, false positive mitigation, vulnerability fixing, and test case/data generation. Using these criteria, a comparison was carried out to contrast the most prominent security testing approaches available in the literature. These criteria will aid both practitioners and researchers to select appropriate approaches according to their needs. Additionally, it will provide researchers with guidance that could help them make a preliminary decision prior to their proposal of new security testing approaches.

The key feature of SaaS application is that it addresses the needs of many different customers using only one software, rather than multiple developments and versions, a concept known as multi-tenancy. However, it typically results in a one-size-fits-all approach and the application only fulfills the requirements that are generic to all tenants. Therefore, a multi-tenancy SaaS application is reliant upon an ability to be customized in order to be successful. Responding to distinctive needs of each customer and maintaining the key feature of developing SaaS application creates complexity in SaaS customization. This paper delves into some challenges related to SaaS customization, and then maps among these challenges in order to structure the problem and objective trees of SaaS customization. This paper may serve as a step towards reducing complexity in SaaS customization.

Finding faults in a program correctly is crucial in software maintenance. In this light, many techniques have been proposed such as program slicing, code coverage, program state and mutation analysis. While all these techniques give us good insight on fault localization, but it appears that these techniques are made based on the assumption that the faults are caused by a single fault. However, in a reality, one fault could also possibly caused by multiple faults. This requires a technique which is specifically designed to handle multiple faults. With this regards, application of mutation analysis to localize faults might generate a vast number of mutants. As a result, these will lead to difficulty in choosing important mutants that are capable of localizing faults. Therefore, there is a need for a technique which able to localize a fault effectively with less number of mutants generated. Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. Since both had their own advantage, we have combined both techniques to enhance multiple localization of software fault. The result of the experiment shows that our technique able to detect multiple faults in various java programs but there is a need for improvement especially in prioritize fault that occurs simultaneously.