Code and data spatial complexity: two important software understandability measures

被引:0
|
作者
Chhabra, JK [1 ]
Aggarwal, KK
Singh, Y
机构
[1] Deemed Univ, Natl Inst Technol, Dept Comp Engn, Kurukshetra 136119, Haryana, India
[2] GGS Indraprastha Univ, Sch Informat Technol, Delhi 110006, India
关键词
code spatial complexity; data spatial complexity; understandability; software metrics; psychological complexity;
D O I
10.1016/S0950-5849(03)00033-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to maintain the software, the programmers need to understand the source code. The understandability of the source code depends upon the psychological complexity of the software, and it requires cognitive abilities to understand the source code. The individual needs to correlate the orientation and location of various entities with their processing, which requires spatial abilities. This paper presents two measures of spatial complexity, which are based on two important aspects of the program-code as well as data. The measures have been applied to 15 different software projects and results have been used to draw many conclusions. The validation of the results has been done with help of perfective maintenance data. Lower values of code as well as data spatial complexity denote better understandability of the source code. (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:539 / 546
页数:8
相关论文
共 50 条
  • [31] Data complexity measures in feature selection
    Okimoto, Lucas C.
    Lorena, Ana C.
    2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2019,
  • [32] DATA FOR SOFTWARE SYSTEMS IMPORTANT TO SAFETY
    WELBOURNE, D
    BESTER, NP
    GEC JOURNAL OF RESEARCH, 1995, 12 (01): : 50 - 57
  • [33] Can Complexity Measures and Instance Hardness Measures Reflect the Actual Complexity of Microarray Data?
    Al Hosni, Omaimah
    Starkey, Andrew
    MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE, LOD 2023, PT I, 2024, 14505 : 445 - 462
  • [34] Predicting the complexity of code changes using entropy based measures
    K. K. Chaturvedi
    P. K. Kapur
    Sameer Anand
    V. B. Singh
    International Journal of System Assurance Engineering and Management, 2014, 5 (2) : 155 - 164
  • [35] Predicting the complexity of code changes using entropy based measures
    Chaturvedi, K. K.
    Kapur, P. K.
    Anand, Sameer
    Singh, V. B.
    INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT, 2014, 5 (02) : 155 - 164
  • [36] RELATIONSHIP BETWEEN LINE OF CODE AND COMPLEXITY IN OPEN SOURCE SOFTWARE
    Ganpati, Anita
    Sharma, Aman Kumar
    Kalia, Arvind
    Singh, Hardeep
    4TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER THEORY AND ENGINEERING ( ICACTE 2011), 2011, : 801 - 804
  • [37] A Notional Understanding of the Relationship between Code Readability and Software Complexity
    Tashtoush, Yahya
    Abu-El-Rub, Noor
    Darwish, Omar
    Al-Eidi, Shorouq
    Darweesh, Dirar
    Karajeh, Ola
    INFORMATION, 2023, 14 (02)
  • [38] CODE: A Data Complexity Framework for Imbalanced Datasets
    Weng, Cheng G.
    Poon, Josiah
    NEW FRONTIERS IN APPLIED DATA MINING, 2010, 5669 : 16 - 27
  • [39] Software maintainability prediction by data mining of software code metrics
    Kaur, Arvinder
    Kaur, Kamaldeep
    Pathak, Kaushal
    2014 INTERNATIONAL CONFERENCE ON DATA MINING AND INTELLIGENT COMPUTING (ICDMIC), 2014,
  • [40] Measurement of object-oriented software spatial complexity
    Chhabra, JK
    Aggarwal, KK
    Singh, Y
    INFORMATION AND SOFTWARE TECHNOLOGY, 2004, 46 (10) : 689 - 699