Azlin Nordin

Trends and perceptions of evidence-based software engineering research in Malaysia

Evidence-based research has been matured and established in many other disciplines such as in Medicine and Psychology. One of the methods that has been widely used to support evidence-based practices is the Systematic Literature Review (SLR) method. The SLR is a review method that aims to provide unbiased or fair evaluation to existing research evidence. The aim of this study is to gather the trends of evidence-based software engineering (SE) research in Malaysia in particular to identify the usage of SLR method among researchers, academics or practitioners. Based on our tertiary study, we found only 19 published work utilizing evidence-based practices in Malaysia within SE and Computer Science related domains. We have also conducted a survey during SLR workshops for the purpose of gathering perceptions on using SLR. The survey was participated by 78 academics and researchers from five universities in Malaysia. Our findings show that researchers in this country are still at preliminary stage in practicing evidence-based approach. We believe that knowledge and skill on using SLR should be promoted to encourage more researchers to apply it in their research.

Modelling immune systems responses for the development of energy sharing strategies for swarm robotic systems

This paper presents an initial investigation on studying an immune systems response, the granuloma formation, for inspirations on the development of energy sharing strategies for swarm robotic systems. Granuloma formation is a process in which unwanted substances are removed by immune systems. To better understand the components and the processes in granuloma formation, we modeled them using Unified Modelling Language (UML). Based on this model, analogous properties of the granuloma formation and swarm robotic systems are mapped accordingly. Based on these work, energy sharing strategies which are inspired by the process in granuloma formation are proposed for fault tolerance in swarm robotic systems.

Software Requirements Patterns and Meta Model: A Strategy for Enhancing Requirements Reuse (RR)

Reuse is a fundamental activity in software development lifecycle, which can be employed at any stage of development. Reuse of software artefacts, such as requirements, architectures, models, test cases among others, improves software quality and productivity. Because of its higher level of abstraction, requirements reuse (RR) is recognized as reuse approach that can provide more benefits in software development. A number of RR approaches are reported in the literature. These include domain-specific, pattern-based, ontology-based and general approaches. However, these approaches lack a strategy that could incorporate some key aspects of reuse, which are, reusable structure, variability modeling (VM) and traceability of software artefacts. In line with this, we make our contribution in this paper by (1) presenting the concepts and importance of software requirements patterns (SRP) and meta model for the enhancement of RR, (2) proposing a meta modeling strategy based on software product line engineering (SPLE), which comprises SRP, VM and traceability. We believe our proposal is novel and can support developers in SPL and model-driven engineering (MDE) benefit more from reuse in the course of software developments.

RF CMOS-MEMS cantilever resonator

This paper presents use of the simple cantilever beam as RF CMOS-MEMS resonator, which can be scaled like transistor with improved performance. This resonator can be used in the oscillator and filter part of RF transceiver, which can actually be fabricated on chip without losing its Q-factor. The cantilever beam resonator was designed using COMSOL4.3b™ and produce resonance frequency at 10.2MHz, pull-in voltage at 1.5V and Q of 10000.

Disaster Recovery with Minimum Replica Plan for Reliability Checking in Multi-Cloud

Abstract The primary uses for cloud computing are to store data and share resources. The cloud has become a dominant and preferred method to store large amounts of data and enable the sharing of that data among several users. It also enables the use of pay-as-you-go pricing models. Today’s cloud computing environment has required data centers to increase the amount of available storage. There are two main concerns with cloud storage: data reliability and cost of storage. This paper discusses the issue of data recovery in case of a disaster in a Multi-Cloud environment. We propose a preventive approach for data backup and recovery aiming at minimizing the number of replicas and ensure high reliability for data before the disaster. The approach named Preventive Disaster Recovery Plan with Minimum Replica (PDRPMR) which is a cost-effective mechanism to reduce the number of replications in the cloud to be 1 or 2-replicas only without compromising the data reliability. The name PDRPMR originates from its preventive action checking of the availability of replicas and monitoring of denial of service attacks to maintain data reliability. Several experiments have been carried out to demonstrate that PDRPMR reduces the amount of storage space used by one third to two-thirds compared to typical 3-replicas replication strategies, which in turn reduces the cost of storage.

A Systematic Literature Mapping of Risk Analysis of Big Data in Cloud Computing Environment

This paper investigates previous literature that focusses on the three elements: risk assessment, big data and cloud. We use a systematic literature mapping method to search for journals and proceedings. The systematic literature mapping process is utilized to get a properly screened and focused literature. With the help of inclusion and exclusion criteria, the search of literature is further narrowed. Classification helps us in grouping the literature into categories. At the end of the mapping, gaps can be seen. The gap is where our focus should be in analysing risk of big data in cloud computing environment. Thus, a framework of how to assess the risk of security, privacy and trust associated with big data and cloud computing environment is highly needed.

Development of scenario management and requirements tool (SMaRT): towards supporting scenario-based requirements engineering methodology

Scenario-based methodology has been applied in analyzing real world experience into representation in software environment. Nonetheless, capturing, documenting and managing scenarios are extremely labour-intensive. Hence, the generic aims of this project are to investigate, explore and analyze requirements management process towards supporting scenario-based requirements approach. Based on our analysis of the existing RE or Requirements Management (RM) tools, most of the tools had less focus or missing some significant RE features to facilitate scenario-based methodology. We analyzed all the relevant features and developed a prototype i.e. Scenario-based Requirements Tool (SMaRT) to demonstrate how scenario-based approach can be implemented to further supports scenario-based RE methodology and covers most of the RE process i.e. elicitation, analysis and negotiation, documentation, validation, and management. SMaRT improves the RE tool features i.e. project and requirements management, document generation and validation function to further support scenario-based RE methodology and covers most of the RE process i.e. elicitation, analysis, negotiation, documentation, validation, and management.

An Analysis of Ambiguity Detection Techniques for Software Requirements Specification (SRS)

Ambiguity is the major problem in Software Requirements Specification (SRS) documents because most of the SRS documents are writ-ten in natural language and natural language is generally ambiguous. There are various types of techniques that have been used to detect ambiguity in SRS documents. Based on an analysis of the existing work, the ambiguity detection techniques can be categorized into three approaches: (1) manual approach, (2) semi-automatic approach using natural language processing, (3) semi-automatic approach using machine learning. Among them, one of the semi-automatic approaches that uses the Naive Bayes (NB) text classification technique obtained high accuracy and performed effectively in detecting ambiguities in SRS.

A Proposed Resistance-to-Time Converter with Switching Impulse Calibrators for Application in Resistive Bridge Sensors

Received Dec 04, 2017 Revised Jan 11, 2018 Accepted Apr 15, 2018 Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.A Weblogs contains the history of User Navigation Pattern while user accessing the websites. The user navigation pattern can be analyzed based on the previous user navigation that is stored in weblog. The weblog comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The aim of the research is to identifying the interested user behavior and not interested user behavior based on classification. The process of identifying user interest, it consists of Modified Span Algorithm and Personalization Algorithm based on the classification algorithm user prediction can be analyzed. The research work explores to analyze user prediction behavior based on user personalization that is captured from weblogs.Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.

A Survey of Schema Matching Research using Database Schemas and Instances

Schema matching is considered as one of the essential phases of data integration in database systems. The main aim of the schema matching process is to identify the correlation between schema which helps later in the data integration process. The main issue concern of schema matching is how to support the merging decision by providing the correspondence between attributes through syntactic and semantic heterogeneous in data sources. There have been a lot of attempts in the literature toward utilizing database instances to detect the correspondence between attributes during schema matching process. Many approaches based on instances have been proposed aiming at improving the accuracy of the matching process. This paper set out a classification of schema matching research in database system exploiting database schema and instances. We survey and analyze the schema matching techniques applied in the literature by highlighting the strengths and the weaknesses of each technique. A deliberate discussion has been reported highlights on challenges and the current research trends of schema matching in database. We conclude this paper with some future work directions that help researchers to explore and investigate current issues and challenges related to schema matching in contemporary databases.