Data Mining - Concepts and Techniques.

物件導向軟體之架構(Object-Oriented Software Construction)探討

Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

Model transformations are touted to play a key role in Model Driven DevelopmentTM. Although well-established standards for creating metamodels such as the Meta-Object Facility exist, there is currently no mature foundation for specifying transformations among models. We propose a framework for the classification of several existing and proposed model transformation approaches. The classification framework is given as a feature model that makes explicit the different design choices for model transformations. Based on our analysis of model transformation approaches, we propose a few major categories in which most approaches fit.

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Feature-based survey of model transformation approaches

Code clones are similar program structures recurring in variant forms in software system(s). Several techniques have been proposed to detect similar code fragments in software, so-called simple clones. Identification and subsequent unification of simple clones is beneficial in software maintenance. Even further gains can be obtained by elevating the level of code clone analysis. We observed that recurring patterns of simple clones often indicate the presence of interesting higher-level similarities that we call structural clones. Structural clones show a bigger picture of similarity situation than simple clones alone. Being logical groups of simple clones, structural clones alleviate the problem of huge number of clones typically reported by simple clone detection tools, a problem that is often dealt with postdetection visualization techniques. Detection of structural clones can help in understanding the design of the system for better maintenance and in reengineering for reuse, among other uses. In this paper, we propose a technique to detect some useful types of structural clones. The novelty of our approach includes the formulation of the structural clone concept and the application of data mining techniques to detect these higher-level similarities. We describe a tool called clone miner that implements our proposed technique. We assess the usefulness and scalability of the proposed techniques via several case studies. We discuss various usage scenarios to demonstrate in what ways the knowledge of structural clones adds value to the analysis based on simple clones alone.

A Data Mining Approach for Detecting Higher-Level Clones in Software

Cloning in software systems is known to create problems during software maintenance. Several techniques have been proposed to detect the same or similar code fragments in software, so-called simple clones. While the knowledge of simple clones is useful, detecting design-level similarities in software could ease maintenance even further, and also help us identify reuse opportunities. We observed that recurring patterns of simple clones - so-called structural clones - often indicate the presence of interesting design-level similarities. An example would be patterns of collaborating classes or components. Finding structural clones that signify potentially useful design information requires efficient techniques to analyze the bulk of simple clone data and making non-trivial inferences based on the abstracted information. In this paper, we describe a practical solution to the problem of detecting some basic, but useful, types of design-level similarities such as groups of highly similar classes or files. First, we detect simple clones by applying conventional token-based techniques. Then we find the patterns of co-occurring clones in different files using the Frequent Itemset Mining (FIM) technique. Finally, we perform file clustering to detect those clusters of highly similar files that are likely to contribute to a design-level similarity pattern. The novelty of our approach is application of data mining techniques to detect design level similarities. Experiments confirmed that our method finds many useful structural clones and scales up to big programs. The paper describes our method for structural clone detection, a prototype tool called Clone Miner that implements the method and experimental results.

Detecting higher-level similarity patterns in programs

XVCL (XML-based Variant Configuration Language) is a meta-programming technique and tool that provides effective reuse mechanisms [2]. XVCL is an open source software (http://fxvcl.sourceforge.net) developed at the National University of Singapore. Being a modem and versatile version of Bassett's frames [1], a technology that has achieved substantial gains in industry, the underlying principles of the XVCL have been thoroughly tested in practice. Unlike original frames, XVCL blends with contemporary programming paradigms and complements other design techniques. XVCL uses "composition with adaptation" rules to generate a specific program from generic, reusable meta-components. Program generation rules are 100% transparent to a programmer, who retains full control over fine-tuning the generated code. Despite its simplicity, XVCL can effectively manage a wide range of program variants from a compact base of metacomponents, structured for effective reuse.

XVCL: XML-based variant configuration language

and using CASE tools in industrial software projects. We also investigated common tool adoption practices. We examined CASE technology from the perspective of technical and non-technical issues involved in software development. Our main conclusion is that current CASE tools are far too oriented on software modeling and construction methods, while other factors that matter to programmers receive little attention. We imagine the creative, problem-solving aspects of software development and perception of a software project from a process, rather than method, perspective. We observed that method-centered CASE tools are not attractive enough to the users. To better meld into the software development practice, CASE tools should adopt a programmer’s mental model of software projects. In particular, CASE tools should support soft aspects of software development as well as rigorous modeling, provide a natural process-oriented development framework rather than a method-oriented one, and play a more active role in software development than current CASE tools. Separation of development methods from other aspects that contribute to successful software projects does not benefit CASE users, whether programmers or project managers. In this article, we analyze problems that impede wide adoption of CASE tools and propose remedies to some of the problems. We direct this article to managers involved in CASE tool adoption, CASE tool users, and CASE tool developers. Although we focus on CASE tools that support software development according to some methods (such as structured analysis/design or an object-oriented method), we believe our observations apply to other types of software tools, too.

The case for user-centered CASE tools

Code clones are similar code fragments that occur at multiple locations in a software system. Detection of code clones provides useful information for maintenance, reengineering, program understanding and reuse. Several techniques have been proposed to detect code clones. These techniques differ in the code representation used for analysis of clones, ranging from plain text to parse trees and program dependence graphs. Clone detection based on lexical tokens involves minimal code transformation and gives good results, but is computationally expensive because of the large number of tokens that need to be compared. We explored string algorithms to find suitable data structures and algorithms for efficient token based clone detection and implemented them in our tool Repeated Tokens Finder (RTF). Instead of using suffix tree for string matching, we use more memory efficient suffix array. RTF incorporates a suffix array based linear time algorithm to detect string matches. It also provides a simple and customizable tokenization mechanism. Initial analysis and experiments show that our clone detection is simple, scalable, and performs better than the previous well-known tools.

Stan Jarzabek

Papers

A Data Mining Approach for Detecting Higher-Level Clones in Software

Detecting higher-level similarity patterns in programs

XVCL: XML-based variant configuration language

The case for user-centered CASE tools

Efficient token based clone detection with flexible tokenization