Azri Azmi

A software traceability model to support software testing documentation

Software Documentation is one of the key quality factors in software development. However, many developers are still putting less effort and less priority on documentation. To them writing documentation during project development is very tedious and time consuming. As a result, the documentation tends to be significantly outdated, poor quality and difficult to access that will certainly lead to poor software maintenance. Current studies have proved that the key point to this problem is software traceability. Traceability relates to an ability to trace all related software components within a software system that includes requirements, test cases, test results and other artefacts. This research reveals some issues related to current software traceability and attempts to suggest a new software traceability model that focuses on software test documentation for test management. This effort leads to a new software test documentation generation process model based on software engineering standards.

Test Management Traceability Model to Support Software Testing Documentation

Software Documentation is one of the key quality factors in software development. However, many developers are still putting less effort and less priority on documentation. To them writing documentation during project development is very tedious and time consuming. As a result, the documentation tends to be significantly out-dated, poor quality and difficult to access that will certainly lead to poor software maintenance. Current studies have proved that the key point to this problem is software traceability. Traceability relates to an ability to trace all related software components within a software system that includes requirements, test cases, test results and other artefacts. This research reveals some issues related to current software traceability and attempts to suggest a new software traceability model that focuses on software test documentation for test management. This effort leads to a new software test documentation generation process model based on software engineering standards.

Analyzing Traffic Accident and Casualty Trend Using Data Visualization

Motor vehicle is the backbone of the modern transportation system worldwide. However, the excessive number of motor vehicles tend to cause traffic accidents leading to numerous casualties. Analyzing existing works on this area, this study has identified prime reasons behind traffic accidents and casualties. They include driving over the speed limit, Age of drivers and pedestrians, environmental condition, location and road types. It has also reviewed and identified several data visualization methods and visualization techniques that have been proposed by many researchers. The objective of this research endeavour is to identify the factors behind traffic accidents, determine the techniques that are used to visualize data, develop a dashboard using data visualization tools to visualize traffic accident trend and to evaluate the functionality of the dashboard which is developed on United Kingdom’s (UK) traffic accident dataset from 2014 to 2016. Upon performing data cleaning, pre-processing and filtering, the raw data has been converted into cleaned, filtered and processed data to create a coherent and properly linked data model. Then, using the Power BI visualization tool, various interactive visualizations have been produced that illustrated several significant trends in accident and casualties. The visualization trend revealed that between 2014 to 2016, majority of the accidents in the UK occurred in the urban area, in the single carriageway, on the dry road surface, under the daylight with fine weather, and when the speed limit was below 30 mph. This research may assist UK’s traffic management authority to identify the underlying factors behind the traffic accident and to detect the traffic accident and casualty trend in order to take necessary steps to reduce casualties in traffic accidents.

Data Quality Issues in Big Data: A Review

Data with good quality has precedence when analyzing and using big data to deduce value from such tremendous volume of data in today’s business environments. Decisions and insights derived from poor data has a negative and unpredictable consequences to organizations. At present, due to the lack of comprehensive and intensive research in the field of data quality, especially large data, there is an urgent need to address this issue by researchers to reach the optimal way to estimate and evaluate the quality of large data. Thus, enabling institutions to make rational decisions based on evaluation outputs. In this paper, the current research on the quality of large data was reviewed and summarized by exploring the basic characteristics of large data. The main challenges facing the quality of information were also discussed in the context of large data. Some of the initiatives suggested by the researchers to evaluate the quality of the data have been highlighted. Finally, we believe that the results of these reviews will enhance the conceptual measurements of the large data quality and produce a concrete groundwork for the future by creating an integrated data quality assessment and evaluation models using the suitable algorithms.

A study of authentication protocols for security of mobile RFID (M-RFID) system

Radio-frequency identification (RFID) uses electromagnetic fields for wireless communication that automatically recognized target devices with no physical interaction with the purpose of information transmission. The RFID system composed of transponder or tag, interrogator and back-end host system. The services of mobile RFID (M-RFID) networks can be setup by consolidating with current wireless networking for mobile devices and RFID networks whereby these services are aiming for individual and private users using Mobile smart phone or PDA. Even though these systems have the benefits of RFID and mobile technology, it also promotes crucial security and privacy issues. M-RFID inherits all issues that exist in the traditional RFID system, for example, replay attack, denial of service, spoofing, traceability and impersonation. However the severity of these issues intensifies because M-RFID reader is used in the wireless environment with agility in movement and greater scanning zone. Therefore, many security protocols developed to support the security and privacy problems arise in M-RFID systems. Among the famous security protocol for the system is the ultralightweight authentication protocols and this survey focus on the study of these protocols. These protocols are not capable of fulfilling all the security and privacy requirements especially in the mobile wireless environments. As in most of the literatures that described and proposed for the security and privacy authentication protocol of M-RFID, they proved that designing a security and privacy authentication protocol is still a demanding and challenging activities. Although many authentication protocols have been developed over the years, none can be considered as perfect and supreme. Based on the review of the authentication protocols, the well-chosen protocol always depends on the context and scenario for the security and privacy efficiency requirements of the M-RFID system.

A change impact analysis tool: integration between static and dynamic analysis techniques

Accepting too many software change requests could contribute to expense and delay in project delivery. On the other hand rejecting the changes may increase customer dissatisfaction. Software project management might use a reliable estimation on potential impacted artifacts to decide whether to accept or reject the changes. In software development phase, an assumption that all classes in the class artifact are completely developed is impractical compared to software maintenance phase. This is due to some classes in the class artifact are still under development or partially developed. This paper is a continuous effort from our previous work on combining between static and dynamic analysis techniques for impact analysis. We have converted the approach to an automated tool and call it a CIAT (Change Impact Analysis Tool). The significant achievements of the tool are demonstrated through an extensive experimental validation using several case studies. The experimental analysis shows improvement in the accuracy over current impact analysis results.

Formulating a Software Traceability Model for Integrated Test Documentation: a Case Study

Software Documentation is a key of quality factor in software development but many among developers failed to produce document during their project. The purpose of documentation is to aid the developers in understanding the project. Unfortunately, the documentation is out dated, poor quality, difficult to access and therefore cannot be trusted. The key point of the problems is software traceability. This research is trying to develop a model of software traceability that can generate a software testing documentation to support test management. This will led to new software testing documentation generation process model based on software engineering standards. Information retrieval technique will be utilized to trace link between software artefacts.