Traveling through Dakota: experiences with an object-oriented program analysis system

Â Abstract. Reverse Engineering of Object Oriented Code to Class Design Using Graph Data Structure. This time the software engineering methodology still follows the process of standard system development consisting of four phases of the system initialization, system analysis, system design, and system implementation. The phases occur sequentially so that the implementation is always done after the design is complete. This research is developing software Code Converter (COCON) to automate the conversion of object-oriented code to class design using graph data structures. COCON only requires an object-oriented code file as input and produce results in the form of a file containing a list of classes and relations between classes that read from input file. COCON help users to find out the class design of object-oriented code and becomes the basis for drawing class diagrams of object-oriented code.Â Keywords: reverse engineering, class design, relation, OOP, graphÂ Abstrak. Pada saat ini metodologi rekayasa perangkat lunak masih mengikuti proses pengembangan sistem yang standar yang terdiri dari empat fase yakni inisialisasi sistem, analisis sistem, desain sistem dan implementasi sistem. Keempat fase tersebut terjadi secara berurutan sehingga fase implementasi selalu dilakukan setelah fase desain selesai. Penelitian ini membangun perangkat lunak Code Converter (COCON) yang berfungsi untuk mengotomasi konversi kode program berorientasi objek ke desain kelas dengan struktur data graf. COCON hanya membutuhkan sebuah berkas kode program berorientasi objek sebagai masukan dan memberikan hasil berupa sebuah berkas yang berisi daftar kelas dan relasi antar kelas yang dibaca dari berkas masukan. COCON membantu pengguna untuk mengetahui desain kelas dari kode program berorientasi objek dan menjadi dasar dalamÂ penggambaran diagram kelas dari kode berorientasi objek.Â Kata Kunci: rekayasa pembalikan, desain kelas, relasi, PBO, graf

Download Full-text

Analisis Penerapan Fuzzy Inference System (FIS) Dengan Metode Mamdani Pada Sistem Prediksi Mahasiswa Non Aktif (Studi Kasus AMIK Tunas Bangsa Pematangsiantar)

10.31227/osf.io/hgmyc ◽

2018 ◽

Author(s):

Anjar Wanto

Keyword(s):

Fuzzy Inference System ◽

Fuzzy Inference ◽

Object Oriented ◽

Inference System ◽

Analysis System ◽

Object Oriented Analysis

AMIK Tunas Bangsa merupakan Perguruan Tinggi di Pematangsiantar yang sedang berkembang. Banyaknya Mahasiswa yang kuliah membuat kesulitan dalam menangani pengolahan data keaktifan Mahasiswa. Seiring pelaksanaannya muncul masalah-masalah, salah satunya adalah banyaknya mahasiswa yang non aktif. Tingginya tingkat keberhasilan mahasiswa dan rendahnya tingkat kegagalan mahasiswa dapat mencerminkan kualitas suatu perguruan tinggi. Penelitian secara statistik telah banyak dilakukan untuk hal tersebut. Padapenelitian ini dikembangkan suatu sistem yang akan memprediksi mahasiswa Non Aktif menggunakan OOAD (Object Oriented Analysis System) dan Fuzzy Inference system (FIS) dengan menggunakan variabel input. OOAD (Object Oriented Analysis System) terbagi atas empat tahapan, yaitu analisis, desain, implementasi dan testing. Untuk perhitungan data digunakan Fuzzy Inference system (FIS) melalui tahapan fuzzifikasi, inferensi, dan defuzzifikasi. Prediksi dilakukan dengan cara memasukkan parameter-parameter yang ada sehingga diperoleh kesimpulan seberapa besar tingkat mahasiswa non aktif tersebut.

Download Full-text

Heavy Driving Drum Parametric Modeling Analysis System Development

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.130-134.641 ◽

2011 ◽

Vol 130-134 ◽

pp. 641-645

Author(s):

Yong Cun Guo ◽

Zhu Fen Wang ◽

Kun Hu ◽

Gang Cheng

Keyword(s):

Parametric Design ◽

System Development ◽

Object Oriented ◽

Parametric Modeling ◽

Visual Design ◽

Design Parameters ◽

Belt Conveyor ◽

Modeling Analysis ◽

Analysis System ◽

The Right

Using the APDL (ANSYS Parametric Design Language) and combining the object-oriented visual design interface of VB, the parametric analysis and modeling system of belt conveyor driving drum is established. With the system, the designers only need to enter the right design parameters to generate the driving drum model and the corresponding post-processing results instead of the repetitive work. It improves efficiency and provides a basis for designing the suitable driving drum. The correctness and feasibility of the system was verified by analyzing examples.

Download Full-text

Object Oriented Software Testing with Genetic Programming and Program Analysis

Computer Engineering ◽

10.4018/978-1-61350-456-7.ch414 ◽

2012 ◽

pp. 992-1006

Author(s):

Arjan Seesing ◽

Hans-Gerhard Gross

Keyword(s):

Genetic Programming ◽

Software Testing ◽

Program Analysis ◽

Heuristic Search ◽

Optimization Problem ◽

Object Oriented ◽

Programming Approach ◽

Test Cases ◽

Procedural Code ◽

To Come

Testing is a difficult and costly activity in the development of object-oriented programs. The challenge is to come up with a sufficient set of test scenarios, out of the typically huge volume of possible test cases, to demonstrate correct behavior and acceptable quality of the software. This can be reformulated as a search problem to be solved by sophisticated heuristic search techniques such as evolutionary algorithms. The goal is to find an optimal set of test cases to achieve a given test coverage criterion. This chapter introduces and evaluates genetic programming as a heuristic search algorithm which is suitable to evolve object-oriented test programs automatically to achieve high coverage of a class. It outlines why the object paradigm is different to the procedural paradigm with respect to testing, and why a genetic programming approach might be better suited than the genetic algorithms typically used for testing procedural code. The evaluation of our implementation of a genetic programming approach, augmented with program analysis techniques for better performance, indicates that object-oriented software testing with genetic programming is feasible in principle. However, having many adjustable parameters, evolutionary search heuristics have to be fined-tuned to the optimization problem at hand for optimal performance, and, therefore, represent a difficult optimization problem in their own right.

Download Full-text