International Journal of Computer Applications (0975 – 8887) Volume 93 – No.7, May 2014 13 Automated Dynamic Slicing based UML Modeling for Phylogenetic Classification Divanshi Priyadarshni Wangoo CSE & IT Department ITM University, Gurgaon Haryana, India ABSTRACT This paper presents an efficient classification algorithm for categorizing evolutionary organisms using slicing techniques. Dynamic slicing excels in tracing out dependencies between executable statements. The nature of these dependencies aids in the determination of control statements in a program. Dynamic slicing technique imbibes the run time execution trace based on a slicing criterion. Dynamic slicing algorithms can trace both the backward and forward dependencies. The UML model is automatically generated from the source code to validate the forward and backward dynamic slicing algorithm. This paper shows the algorithmic implementation in NetBeans IDE 7.4. It provides a new platform for automated software engineering. The algorithm efficiently discovers the evolutionary relationship between organisms .Forward dynamic slicing algorithm helps in identifying the successors of the organisms and the backward dynamic slicing algorithm finds out the predecessors of the evolutionary organisms. Both the algorithms are based on dynamic slicing criterion at the run time execution trace. The integration of these phylogenetic algorithms deciphers the building complexity of the evolutionary organisms. It proves to have an advantageous classification encasement for jeopardized species. General Terms Dynamic slicing, Object-oriented. Keywords Forward Dynamic Slicing Algorithm (FDSA); Backward Dynamic Slicing Algorithm (BDSA); Phylogenetic System Dependence Graphs (PSDG); System Dependence Graph (SDG); Lines of Code (LOC); Software Development Lifecycle (SDLC). 1. INTRODUCTION Slicing techniques and its applications have evolved over years through the ongoing researches in different domain. Program slicing has varied with all new technological programming relevant fields. The new forms of slicing techniques have emerged from the profound dependencies as a result of executable commands. Slicing was basically practiced for programming languages that admitted the interactions among objects. Object interactions involve the message passing scheme with which one object can communicate with another object. All the object-oriented features like classes, objects, inheritance, abstraction, polymorphism, and encapsulation can be featured through various dependence graphs based on slicing methodology [1]. The programming statements of an object oriented language features versatile control flows that direct the implementation of the executable program file. By recognizing the dependent relations in the program code, the complex inheritance constructs can be verified with ease. Also, other programming jobs are simplified which becomes difficult with the intent of increasing Lines of Code (LOC). Slicing proficiencies can develop phyletic taxonomy of species by tracing the historical hierarchy of evolutionary organisms. It is necessary for the species requiring categorization to have their morphed mutable features inheritable form their predecessors. Historic integrality has an immense hereditary patterned system that recognizes the development of succeeding genesis. Thus, to make the taxonomical evolution traceable to a greater extent, slicing has been incorporated to discover the next future generation species. A taxonomic group is any organism bearing natural relations. These relations by law of nature are governed by dependent relationships between the organisms in the hierarchy. The organism’s existence comes from either the immediate predecessors or the older predecessors from which the immediate predecessor derives. The inheritance derivation is the framework for the ontogenetic species. This paper presents an efficacious dynamic slicing algorithm for the classification of birds. The advantage of classification algorithm amounts to precise knowledge of predecessors and successors of a particular species. The dynamic slicing technique is preferred as the implementation of the algorithm can be tested at the execution run time. This verifies the validity of the algorithms for large data sets involving numerous inheritance hierarchies. The species of birds have evolved over time from different predecessors that all have the same ontogenetic base of aves species. The evolution bases its ground on the dependence of features that one species develop from their immediate predecessors. The immediate predecessors may inherit different characteristics from any number of predecessors. This governs the hierarchical dependence that exists with the visible or behavioral characteristics shown by the species. Keeping in view the dependencies among the taxonomical community of species, the slicing methodology can be employed for the given group. The main criteria used for categorizing the species by slicing is by tracing the inheritance hierarchy of a given organism and applying the slicing algorithms for its predecessor or successor determination. This paper presents two algorithms based on dynamic slicing that yields the successors or predecessors of an organism. The algorithms are called Forward Dynamic Slicing Algorithm (FDSA) for computing the successors and Backward Dynamic Slicing Algorithm (BDSA) for the computation of the predecessors of a given species. The execution trace upshots are given which show the validation of the FDSA and BDSA algorithms for different inputs. Thus, the application of dynamic slicing algorithms aid in the production of more effective classification scheme and reduces the LOC’s of the programming code to an estimable track.