CLUBAS: An Algorithm and Java Based Tool for Software Bug Classification Using Bug Attributes Similarities

In this paper, a software bug classification algorithm, CLUBAS (Classification of Software Bugs Using Bug Attribute Similarity) is presented. CLUBAS is a hybrid algorithm, and is designed by using text clustering, frequent term calculations and taxonomic terms mapping techniques. The algorithm CLUBAS is an example of classification using clustering technique. The proposed algorithm works in three major steps, in the first step text clusters are created using software bug textual attributes data and followed by the second step in which cluster labels are generated using label induction for each cluster, and in the third step, the cluster labels are mapped against the bug taxonomic terms to identify the appropriate categories of the bug clusters. The cluster labels are generated using frequent and meaningful terms present in the bug attributes, for the bugs belonging to the bug clusters. The designed algorithm is evaluated using the performance parameters F-measures and accuracy. These parameters are compared with the standard classification techniques like Na?ve Bayes, Naive Bayes Multinomial, J48, Support Vector Machine and Weka’s classification using clustering algorithms. A GUI (Graphical User Interface) based tool is also developed in java for the implementation of CLUBAS algorithm.

Model-Driven Derivation of Domain Functional Requirements from Use Cases

Domain analysis is essential to core assets development in software product line engineering. Most existing approaches, however, depend on domain experts’ experience to analyze the commonality and variability of systems in a domain, which remains a manual and intensive process. This paper addresses the issue by proposing a model-driven approach to automating the domain requirements derivation process. The paper focuses on the match between the use cases of existing individual products and the domain functional requirements of a product line. By introducing a set of linguistic description dimensions to differentiate the sub-variations in a use case, the use case template is extended to model variability. To this end, a transformation process is formulated to sustain and deduce the information in use cases, and to match it to domain functional requirements. This paper also presents a prototype which implements the derivation as a model transformation described in a graphical model transformation language MOLA. This approach complements existing domain analysis techniques with less manual operation cost and more efficiency by automating the domain functional requirements development.

用Use Case表达架构观点之二

MIS部门的开发人员，也可能是ISV（Independent Software Vendor）承接到一个项目，需要为某公司既有的HR（Human Resource）系统新增电子签核的功能。最基本的一个功能．就是将原本是人工操作的请假业务流程，改为可以让员工填写的电子表单，填写完毕后系统即自动传送至直属主管供其签核，整个请假流程完全是计算机化．自动化。这也是属于业务流程再造的范畴，可以减轻人事部门的负担及节省成本。

Comparison of SETAM with Security Use Case and Security Misuse Case:A Software Security Testing Study

A software security testing behavior model,SETAM,was proposed in our previous work as the integrated model for describing software security testing requirements behavior,which is not only compatible with security functions and latent typical misuse behaviors,but also with the interaction of them.In this paper,we analyze the differences between SETAM with security use case and security misuse case in different types of security test requirements.To illustrate the effectiveness of SETAM,we compare them in a practical case study by the number of test cases and the number of faults detected by them.The results show that SETAM could decrease about 34.87% use cases on average,and the number of faults detected by SETAM increased by 71.67% in average,which means that our model can detect more faults with fewer test cases for software security testing.

USING PROBLEM-SOLVING SOFTWARE IN THE ESL CLASSROOM

This paper examines the possibilities for and implications of integrating problem-solving software into the foreign language classroom, and offers a one-hour lesson plan with the use of a piece of problemsolving software as an example.

Extended UML with Role Modeling

UML is widely accepted and applied by the international software industry. UML is a powerful language for Object oriented modeling, designing, and implementing software systems, but its Use Case method for requirement analysis and modeling software patterns has some explicit drawbacks. For more complete UML, this paper proposes the Role Use Case modeling and its glyphs, and provides an instance of requirement analysis using Role Use Case method. Uses the Role Model to modeling software pattern at knowledge level. This paper also extends the UML Meta Model and accentuates “RM before UML's class Modeling”.

X-ray diffraction analysis of cold-worked Cu-Ni-Si and Cu-Ni-Si-Cr alloys by Rietveld method

Cold worked and annealed supersaturated Cu-2.65Ni-0.6Si and Cu-2.35Ni-0.6Si-0.6Cr alloys were studied. The microstructural parameters evolution, including crystallite size, root mean square strain and dislocation density was analyzed using Materials Analysis Using Diffraction software （MAUD）. The parameters for both alloys have typical values of cold deformed and subsequently annealed copper based alloy. A net change of the crystallite size, root mean square strain and dislocation density values of the alloys aged at 450 °C for 2.5-3 h seems corresponding to the recovery and recrystallization processes. Addition of Cr as quaternary element did not lead to any drastic changes of post deformation or ageing microstructural parameters and hence of recovery-recrystallization kinetics.

ML-CLUBAS: A Multi Label Bug Classification Algorithm

In this paper, a multi label variant of CLUBAS [1] algorithm, ML-CLUBAS (Multi Label-Classification of software Bugs Using Bug Attribute Similarity) is presented. CLUBAS is a hybrid algorithm, and is designed by using text clustering, frequent term calculations and taxonomic terms mapping techniques, and is an example of classification using clustering technique. CLUBAS is a single label algorithm, where one bug cluster is exactly mapped to a single bug category. However a bug cluster can be mapped into the more than one bug category in case of cluster label matches with the more than one category term, for this purpose ML-CLUBAS a multi label variant of CLUBAS is presented in this work. The designed algorithm is evaluated using the performance parameters F-measures and accuracy, number of clusters and purity. These parameters are compared with the CLUBAS and other multi label text clustering algorithms.

Verification of Quality Requirement Method Based on the SQuaRE System Quality Model

For a purpose of suitable system product development and acquisition successfully, it is extremely important to specify the quality requirement for target system during system design phase, and developing or selecting a most suitable product finally from among the alternative candidate products. However, the quality requirements analysis is a very difficult matter because it is non-formulaic and demands much of product customer’s technical perceptiveness. Traditionally, analysis of quality requirements of a product has been conducted through questionnaires or interviews with customers based on survey investigator’s personal experience. This kind of lack of structure and incompleteness in the traditional approach introduced missing requirements and errors in prioritizing requirements to implement in the requirement analysis of a product. On the other hand, we have been working on developing the techniques (SQuaRE) for quality requirements and evaluation for system and software product for a long time in ISO/IECJTC1/SC7WG 6. For the purpose of specify the quality requirement of system product, the method of quantitative quality requirement definitions based on ISO/IEC9126 [1] quality model that includes six characteristics is widely recognized. However, independency among each quality characteristic is not sure and the suitability of method by using these six quality characteristics for quality requirement is not certified statistically. In this paper, we propose the concept of quality requirements definition method based on the SQuaRE quality models define in ISO/IEC25030 [2,3]. Also, this paper proposes the result of verification about effectiveness of quantitative quality requirement definition approach from the view point of six quality characteristics described in ISO/IEC9126.

通往弹性软件架构之路

本文节选自Ivar Jacobson所著《Aspect-Oriented Software Development with Use Cases》的中文译作《AOSD中文版——基于用例的面向方面软件开发》,书中系统地概括出如何基于用例来进行面向方面开发,覆盖了需求、分析、设计、实现和测试的所有环节,展示了如何使用UML对关注点和方面进行建模,以及如何基于用例枝术和面向方面技术来建立一个弹性的体系结构(限于篇幅,本章在原文的基础上有所删节)。

An experimental study on the conversion between IFPUG and UCP functional size measurement units

The use of functional size measurement(FSM) methods in software development organizations is growing during the years. Also, object oriented(OO) techniques have become quite a standard to design the software and, in particular, Use Cases is one of the most used techniques to specify functional requirements. Main FSM methods do not include specific rules to measure the software functionality from its Use Cases analysis. To deal with this issue some other methods like Kramer's functional measurement method have been developed. Therefore, one of the main issues for those organizations willing to use OO functional measurement method in order to facilitate the use cases count procedure is how to convert their portfolio functional size from the previously adopted FSM method towards the new method. The objective of this research is to find a statistical relationship for converting the software functional size units measured by the International Function Point Users Group(IFPUG) function point analysis(FPA) method into Kramer-Smith's use cases points(UCP) method and vice versa. Methodologies for a correct data gathering are proposed and results obtained are analyzed to draw the linear and non-linear equations for this correlation. Finally, a conversion factor and corresponding conversion intervals are given to establish the statistical relationship.