Communications software reverse engineering: A semi-automatic approach

被引:7
|
作者
Saleh, K
Boujarwah, A
机构
[1] Kuwait University, Dept. of Elec. and Comp. Engineering, Safat 13060
关键词
communications software engineering; Estelle; reverse engineering; tools;
D O I
10.1016/0950-5849(95)01061-0
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A large amount of existing data communications software was developed prior to the advances in software technology using informal and ad hoc techniques. As a result, developers are suffering during the maintenance of this software since the quality of both the software and the associated documentation is not acceptable. Moreover, the addition of features to this software is often leading to side-effects and unexpected interactions. Also, much of this software is missing a clear and formal service definition, or at least a formal statement about their mission. Design documents are either informal or incomplete and do not reflect the existing software, and test plans are either incomplete or not documented. Maintaining and expanding such software becomes unmanageable, very time-consuming and sometimes impossible. In this paper, we propose a reverse engineering method that can be applied to such informally developed communications software to facilitate the extraction of design choices and documentation in addition to the formal definition of the intended communication service. This method obtains a high-level abstraction of the communications software based on Estelle, an International Standardization Organization (ISO) standard specification language for protocols and for distributed systems in general. The application of this reverse engineering process will definitely increase the productivity of the protocol/software engineer. Morover, it will allow the revalidation and redesign of the extracted design and the derivation of more comprehensive test plans. An example is also provided to illustrate the application of the method.
引用
下载
收藏
页码:379 / 390
页数:12
相关论文
共 50 条
  • [1] Semi-automatic generation of textual exercises for software engineering education
    Huber, Florian
    Hagel, Georg
    PROCEEDINGS OF THE 2022 IEEE GLOBAL ENGINEERING EDUCATION CONFERENCE (EDUCON 2022), 2022, : 51 - 56
  • [2] A Semi-Automatic Approach for Extracting Software Product Lines
    Valente, Marco Tulio
    Borges, Virgilio
    Passos, Leonardo
    IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2012, 38 (04) : 737 - 754
  • [3] Semi-automatic improvement of software development methods
    Jankovic, Marko
    2013 IEEE SEVENTH INTERNATIONAL CONFERENCE ON RESEARCH CHALLENGES IN INFORMATION SCIENCE (RCIS), 2013,
  • [4] Semi-automatic approach for music classification
    Zhang, T
    INTERNET MULTIMEDIA MANAGEMENT SYSTEMS IV, 2003, 5242 : 81 - 91
  • [5] Semi-automatic ontology engineering using patterns
    Blomqvist, Eva
    SEMANTIC WEB, PROCEEDINGS, 2007, 4825 : 911 - 915
  • [6] Semi-Automatic Low cost 3D Laser scanning systems for reverse engineering
    Galantucci, L. M.
    Piperi, E.
    Lavecchia, F.
    Zhavo, A.
    3RD CIRP GLOBAL WEB CONFERENCE - PRODUCTION ENGINEERING RESEARCH ADVANCEMENT BEYOND STATE OF THE ART (CIRPE2014), 2015, 28 : 94 - 99
  • [7] Visual OntoBridge: Semi-automatic Semantic Annotation Software
    Grcar, Miha
    Mladenic, Dunja
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT II, 2009, 5782 : 726 - 729
  • [8] Argus: Hardware and Software System for Automatic or Semi-automatic Photo Taking
    Szecsi, Zsolt
    Simon, Karoly
    Szelyes, Levente
    IEEE 13TH INTERNATIONAL SYMPOSIUM ON INTELLIGENT SYSTEMS AND INFORMATICS (SISY), 2015, : 37 - 41
  • [9] SEMI-IMPLICIT SCHEME FOR SEMI-AUTOMATIC SEGMENTATION IN NATURASAT SOFTWARE
    Ambroz, Martin
    Kollar, Michal
    Mikula, Karol
    ALGORITMY 2020: 21ST CONFERENCE ON SCIENTIFIC COMPUTING, 2020, : 171 - 180
  • [10] CONVERSATIONS: SOFTWARE FOR THE SEMI-AUTOMATIC ANALYSIS OF CONVERSATIONAL STRUCTURE
    Climent, Sara badia
    Guerri, Guadalupe espinosa
    RLA-REVISTA DE LINGUISTICA TEORICA Y APLICADA, 2024, 62 (01): : 73 - 100