Quality metrics for assessing security-critical computer programs

Existing secure software development principles tend to focus on coding vulnerabilities, such as buffer or integer overflows, that apply to individual program statements, or issues associated with the run-time environment, such as component isolation. Here we instead consider software security from the perspective of potential information flow through a program’s object-oriented module structure. In particular, we define a set of quantifiable "security metrics" which allow programmers to quickly and easily assess the overall security of a given source code program or object-oriented design. Although measuring quality attributes of object-oriented programs for properties such as maintainability and performance has been well-covered in the literature, metrics which measure the quality of information security have received little attention. Moreover, existing securityrelevant metrics assess a system either at a very high level, i.e., the whole system, or at a fine level of granularity, i.e., with respect to individual statements. These approaches make it hard and expensive to recognise a secure system from an early stage of development. Instead, our security metrics are based on well-established compositional properties of object-oriented programs (i.e., data encapsulation, cohesion, coupling, composition, extensibility, inheritance and design size), combined with data flow analysis principles that trace potential information flow between high- and low-security system variables. We first define a set of metrics to assess the security quality of a given object-oriented system based on its design artifacts, allowing defects to be detected at an early stage of development. We then extend these metrics to produce a second set applicable to object-oriented program source code. The resulting metrics make it easy to compare the relative security of functionallyequivalent system designs or source code programs so that, for instance, the security of two different revisions of the same system can be compared directly. This capability is further used to study the impact of specific refactoring rules on system security more generally, at both the design and code levels. By measuring the relative security of various programs refactored using different rules, we thus provide guidelines for the safe application of refactoring steps to security-critical programs. Finally, to make it easy and efficient to measure a system design or program’s security, we have also developed a stand-alone software tool which automatically analyses and measures the security of UML designs and Java program code. The tool’s capabilities are demonstrated by applying it to a number of security-critical system designs and Java programs. Notably, the validity of the metrics is demonstrated empirically through measurements that confirm our expectation that program security typically improves as bugs are fixed, but worsens as new functionality is added.

Effect of temperature distribution on predicting quality of microwave dehydrated food

During food drying, many other changes occur simultaneously, resulting in an improved overall quality. Among the quality attributes, the structure and its corresponding color influence directly or indirectly other properties of food. In addition, these quality attributes are affected by process conditions, material components and the raw structure of the foodstuff. In this work, the temperature distribution within food materials during microwave drying has been taken into consideration to observe its role in color modification. In order to determine the temperature distribution of microwave-dried food (apple), a thermal imaging camera has been used. The image acquired from the digital camera has been analysed using image J software in order to get the color change of fresh and dried apple. The results show that temperature distribution plays an important role in determining the quality of the food. The thermal imaging camera was deployed to observe the temperature distribution within food materials during drying. It is clearly observed from the higher value of (ERGB =102) and the uneven color change that uneven temperature distribution can influence customer perceptions of the quality of dried food. Simulation of a mathematical model of temperature distribution during microwave drying can make it possible to predict the colour and texture of the microwaved food.

Porosity: Establishing the relationship between drying parameters and dried food quality [SpringerBriefs in Food, Health, and Nutrition]

The preservation technique of drying offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Variations in porosity are just one of the microstructural changes that take place during the drying of most food materials. Some studies found that there may be a relationship between porosity and the properties of dried foods. However, no conclusive relationship has yet been established in the literature. This paper presents an overview of the factors that influence porosity, as well as the effects of porosity on dried food quality attributes. The effect of heat and mass transfer on porosity is also discussed along with porosity development in various drying methods. After an extensive review of the literature concerning the study of porosity, it emerges that a relationship between process parameters, food qualities, and sample properties can be established. Therefore, we propose a hypothesis of relationships between process parameters, product quality attributes, and porosity.

Security metrics for object-oriented class designs

Measuring quality attributes of object-oriented designs (e.g. maintainability and performance) has been covered by a number of studies. However, these studies have not considered security as much as other quality attributes. Also, most security studies focus at the level of individual program statements. This approach makes it hard and expensive to discover and fix vulnerabilities caused by design errors. In this work, we focus on the security design of an object oriented application and define a number of security metrics. These metrics allow designers to discover and fix security vulnerabilities at an early stage, and help compare the security of various alternative designs. In particular, we propose seven security metrics to measure Data Encapsulation (accessibility) and Cohesion (interactions) of a given object-oriented class from the point of view of potential information flow.

Security metrics for object-oriented designs

Several studies have developed metrics for software quality attributes of object-oriented designs such as reusability and functionality. However, metrics which measure the quality attribute of information security have received little attention. Moreover, existing security metrics measure either the system from a high level (i.e. the whole system’s level) or from a low level (i.e. the program code’s level). These approaches make it hard and expensive to discover and fix vulnerabilities caused by software design errors. In this work, we focus on the design of an object-oriented application and define a number of information security metrics derivable from a program’s design artifacts. These metrics allow software designers to discover and fix security vulnerabilities at an early stage, and help compare the potential security of various alternative designs. In particular, we present security metrics based on composition, coupling, extensibility, inheritance, and the design size of a given object-oriented, multi-class program from the point of view of potential information flow.

Board members’ contribution to strategic decision-making in small firms

This article explores how the boards of small firms actually undertake to perform strategic tasks. Board strategic involvement has seldom been investigated in the context of small firms. We seek to make a contribution by investigating antecedents of board strategic involvement. The antecedents are “board working style” and “board quality attributes”, which go beyond the board composition features of board size, CEO duality, the ratio of non-executive to executive directors and ownership. Hypotheses were tested on a sample of 497 Norwegian firms (from 5 to 30 employees). Our results show that board working style and board quality attributes rather than board composition features enhance board strategic involvement. Moreover, board quality attributes outperform board working style in fostering board strategic involvement

Effect of moisture and temperature distribution on dried food microstructure and porosity

Dehydration of food materials requires water removal from it. This removal of moisture prevents the growth and reproduction of microorganisms that cause decay and minimizes many of the moisture-driven deterioration reactions (Brennan, 1994). However, during food drying, many other changes occur simultaneously resulting in a modified overall quality (Kompany et al., 1993). Among the physical attributes of dried food material porosity and microstructure are the important ones that can dominant other quality of dried foods (Aguilera et al., 2000). In addition, this two concerned quality attributes affected by process conditions, material components and raw structure of food stuff. In this work, temperature moisture distribution within food materials during microwave drying will be taken into consideration to observe its participation on the microstructure and porosity of the finished product. Apple is the selective materials for this work. Generally, most of the food materials are found in non-uniformed moisture contained condition. To develop non uniform temperature distribution, food materials have been dried in a microwave oven with different power levels (Chua et al., 2000). First of all, temperature and moisture model is simulated by COMSOL Multiphysics. Later on, digital imaging camera and Image Pro Premier software have been deployed to observation moisture distribution and thermal imaging camera for temperature distribution. Finally, Microstructure and porosity of the food materials are obtained from scanning electron microscope and porosity measuring devices respectively . Moisture distribution and temperature during drying influence the microstructure and porosity significantly. Specially, High temperature and moisture contained regions show less porosity and more rupture. These findings support other literatures of Halder et al. (2011) and Rahman et al (1990). On the other hand, low temperature and moisture regions depict uniform microstructure and high porosity. This work therefore assists in better understanding of the role of moisture and temperature distribution to a prediction of micro structure and porosity of dried food materials.

Fractal dimension of dried foods : a correlation between microstructure and porosity

The quality of dried food is affected by a number of factors including quality of raw material, initial microstructure, and drying conditions. The structure of the food materials goes through deformations due to the simultaneous effect of heat and mass transfer during the drying process. Shrinkage and changes in porosity, microstructure and appearance are some of the most remarkable features that directly influence overall product quality. Porosity and microstructure are the important material properties in relation to the quality attributes of dried foods. Fractal dimension (FD) is a quantitative approach of measuring surface, pore characteristics, and microstructural changes [1]. However, in the field of fractal analysis, there is a lack of research in developing relationship between porosity, shrinkage and microstructure of different solid food materials in different drying process and conditions [2-4]. Establishing a correlation between microstructure and porosity through fractal dimension during convective drying is the main objective of this work.

Determination of effective moisture diffusivity of banana using thermogravimetric analysis

Drying has been extensively used as a food preservation procedure. The longer life attained by drying is however accompanied by huge energy consumption and deterioration of quality. Moisture diffusivity is an important factor that is considered essential to understand for design, analysis, and optimization of drying processes for food and other materials. Without an accurate value of moisture diffusivity, drying kinetics, energy consumption, quality attributes such as shrinkage, texture, and microstructure cannot be predicted properly. However, moisture diffusivities differ due to variation of composition and microstructure of foodstuff and drying variables. For a particular food, it changes with many factors including moisture content, water holding capacity, process variables and physiochemical attributes of food. Published information on moisture diffusivities of banana is inadequate and sometimes inconsistent due to lack of precise repeatable analysis techniques. In this work, the effective moisture diffusivity of banana was determined by Thermogravimetric Analysis (TGA), which ensures precise measurements and reproduction of experiments. A TGA Q500 V20.13 Build 39 was deployed to obtain the drying curve of the food material. It was found that effective moisture diffusivity ranged from 6.63 x10-10 to 1.03 x10-9 and 1.34 x10-10 to 6.60 x10-10 for isothermal at 70 0C and non-isothermal process respectively.These values are consistent with the value of moisture diffusivity found in the literature.

Identifying satisfaction factors in tertiary education: The case of an information systems program

This paper introduces a modified Kano approach to analysing and classifying quality attributes that drive student satisfaction in tertiary education. The approach provides several benefits over the traditional Kano approach. Firstly, it uses existing student evaluations of subjects in the educational institution instead of purpose-built surveys as the data source. Secondly, since the data source includes qualitative comments and feedback, it has the exploratory capability to identify emerging and unique attributes. Finally, since the quality attributes identified could be tied directly to students’ detailed feedback, the approach enables practitioners to easily translate the results into concrete action plans. In this paper, the approach is applied to analysing 26 subjects in the information systems school of an Australia university. The approach has enabled the school to uncover new quality attributes and paves the way for other institutions to use their student evaluations to continually understand and addressed students’ changing needs.

Prediction of shrinkage and porosity during drying: Considering both material properties and process conditions

Drying of food materials offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Shrinkage and variations in porosity are the common micro and microstructural changes that take place during the drying of mostly the food materials. Although extensive research has been carried out on the prediction of shrinkage and porosity over the time of drying, no single model exists which consider both material properties and process condition in the same model. In this study, an attempt has been made to develop and validate shrinkage and porosity models of food materials during drying considering both process parameters and sample properties. The stored energy within the sample, elastic potential energy, glass transition temperature and physical properties of the sample such as initial porosity, particle density, bulk density and moisture content have been taken into consideration. Physical properties and validation have been made by using a universal testing machine ( Instron 2kN), a profilometer (Nanovea) and a pycnometer. Apart from these, COMSOL Multiphysics 4.4 has been used to solve heat and mass transfer physics. Results obtained from models of shrinkage and porosity is quite consistent with the experimental data. Successful implementation of these models would ensure the use of optimum energy in the course of drying and better quality retention of dried foods.

What student attributes affect experience of PBL in Virtual Space?

Some Engineering Faculties are turning to the problem-based learning (PBL)paradigm to engender necessary skills and competence in their graduates. Since, at the same time, some Faculties are moving towards distance education, questions are being asked about the effectiveness of PBL for technical fields such as Engineering when delivered in virtual space. This paper outlines an investigation of how student attributes affect their learning experience in PBL courses offered in virtual space. A frequency distribution was superimposed on the outcome space of a phenomenographical study on a suitable PBL course to investigate the effect of different student attributes on the learning experience. It was discovered that the quality, quantity, and style of facilitator interaction had the greatest impact on the student learning experience. This highlights the need to establish consistent student interaction plans and to set, and ensure compliance with, minimum standards with respect to facilitation and student interactions.

The influence of family ownership on the quality of accounting information

This article explores the quality of accounting information in listed family firms. The authors exploit the features of the Italian equitymarket characterizd by high ownership concentration across all tpes of firms to disentangle the effects of family ownership from other major block holders on the quality of accounting information. The findings document that family firms convey financial information of higher quality compared to the nonfamily peers. Furthermore the authors provide evidence that the determinants of accounting quality differ across family and nonfamily firms.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Triangular Linguistic Fuzzy based performance measurement model for supply chain to assess leanness attributes

Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.