A new cohesion metric and restructuring technique for object oriented paradigm

When software systems grow large during maintenance, they may lose their quality and become complex to read, understood and maintained. Developing a software system usually requires teams of developers working in concert to provide a finished product in a reasonable amount of time. What that means is many people may read each component of the software system such as a class in object oriented programming environment

An Introduction to Slice-Based Cohesion and Coupling Metrics

This report provides an overview of slice-based software metrics. It brings together information about the development of the metrics from Weiser’s original idea that program slices may be used in the measurement of program complexity, with alternative slice-based measures proposed by other researchers. In particular, it details two aspects of slice-based metric calculation not covered elsewhere in the literature: output variables and worked examples of the calculations. First, output variables are explained, their use explored and standard reference terms and usage proposed. Calculating slice-based metrics requires a clear understanding of ‘output variables’ because they form the basis for extracting the program slices on which the calculations depend. This report includes a survey of the variation in the definition of output variables used by different research groups and suggests standard terms of reference for these variables. Our study identifies four elements which are combined in the definition of output variables. These are the function return value, modified global variables, modified reference parameters and variables printed or otherwise output by the module. Second, slice-based metric calculations are explained with the aid of worked examples, to assist newcomers to the field. Step-by-step calculations of slice-based cohesion and coupling metrics based on the vertices output by the static analysis tool CodeSurfer (R) are presented and compared with line-based calculations

Code extraction algorithms which unify slicing and concept assignment

One approach to reverse engineering is to partially automate subcomponent extraction, improvement and subsequent recombination. Two previously proposed automated techniques for supporting this activity are slicing and concept assignment. However, neither is directly applicable in isolation; slicing criteria (sets of program variables) are simply too low level in many cases, while concept assignment typically fails to produce executable subcomponents. This paper introduces a unification of slicing and concept assignment which exploits their combined advantages, while overcoming their individual weaknesses. Our 'concept slices' are extracted using high level criteria, while producing executable subprograms. The paper introduces three ways of combining slicing, and concept assignment and algorithms for each. The application of the concept slicing algorithms is illustrated with a case study from a large financial organisation

An Extended Stable Marriage Problem Algorithm for Clone Detection

Code cloning negatively affects industrial software and threatens intellectual property. This paper presents a novel approach to detecting cloned software by using a bijective matching technique. The proposed approach focuses on increasing the range of similarity measures and thus enhancing the precision of the detection. This is achieved by extending a well-known stable-marriage problem (SMP) and demonstrating how matches between code fragments of different files can be expressed. A prototype of the proposed approach is provided using a proper scenario, which shows a noticeable improvement in several features of clone detection such as scalability and accuracy.Comment: 20 pages, 10 figures, 6 table

Identifying Extract Class and Extract Method Refactoring Opportunities Through Analysis of Variable Declarations and Uses

For small software systems, with perhaps a few thousand lines of code, software structure is largely an esthetic issue. When software systems grow large, including perhaps a million or more lines of source code, their structures become much more important. Developing a large system requires teams of developers working in concert to provide a finished product in a reasonable amount of time. That means that many people will read each component to use, test or modify towards accomplishing new features. In the software development life cycle, the maintenance phase is a dominant stage that impacts production cost of the system dramatically. This is mainly because, for a successful system, the maintenance phase lasts until the system\u27s retirement and includes crucial operations such as enhancing performance, fixing newly discovered bugs and adopting/expending the software to meet new user requirements. Moreover, a software component may be modified or fixed by someone who is not the original author of that component. In this case, all the operations conducted during maintenance or initial development may lead to insertion of code into a unit that may be unrelated to the original design concept of that unit. As software systems become large and complex they grow too long to read and understand completely by a single person. After their initial implementations, maintenance operations tend to make the system even less maintainable, increasing the time and effort needed for future maintenance. In this research, we are interested in finding ways to successfully detect code defects and propose solutions to increase the overall maintainability of software systems that are larger than any one person can completely comprehend from its code alone. This process of refactoring software impacts the total production cost of the system positively by improving the quality of software code such as its comprehensibility and readability. To reduce the total development cost for a system, we suggest three main re-factorings. These novel forms of refactoring techniques aim to eliminate code defects such as large classes and long methods. The main goal of these re-factorings is to create smaller and cohesive software units with clear intentions to improve the maintainability of software. We provide analysis and visualization tools to help a user identify candidate code fragments to be extracted as separate unites. With these automation tools, developers do not have to manually inspect a foreign code base to detect possible refactoring opportunities. Through the visual representations we provide, one can observe all suggested re-factorings effectively on large scale software systems and decide whether a particular refactoring needs to be applied. To show the effectiveness of our techniques, we also provide some experiments conducted using these tools and techniques both on our own project\u27s source code and other open-source projects

PROGRAM SLICING TECHNIQUES AND ITS APPLICATIONS

Program understanding is an important aspect in Software Maintenance and Reengineering. Understanding the program is related to execution behaviour and relationship of variable involved in the program. The task of finding all statements in a program that directly or indirectly influence the value for an occurrence of a variable gives the set of statements that can affect the value of a variable at some point in a program is called a program slice. Program slicing is a technique for extracting parts of computer programs by tracing the programs’ control and data flow related to some data item. This technique is applicable in various areas such as debugging, program comprehension and understanding, program integration, cohesion measurement, re-engineering, maintenance, testing where it is useful to be able to focus on relevant parts of large programs. This paper focuses on the various slicing techniques (not limited to) like static slicing, quasi static slicing, dynamic slicing and conditional slicing. This paper also includes various methods in performing the slicing like forward slicing, backward slicing, syntactic slicing and semantic slicing. The slicing of a program is carried out using Java which is a object oriented programming language