Subjective evaluation of software evolvability using code smells:: An empirical study

被引:105
|
作者
Mantyla, Mika V. [1 ]
Lassenius, Casper [1 ]
机构
[1] Aalto Univ, Helsinki, Finland
关键词
code smells; subjective evaluation; perceived evaluation; maintainability; evolvability; code metrics; software metrics; human factors;
D O I
10.1007/s10664-006-9002-8
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This paper presents the results of an empirical study on the subjective evaluation of code smells that identify poorly evolvable structures in software. We propose use of the term software evolvability to describe the ease of further developing a piece of software and outline the research area based on four different viewpoints. Furthermore, we describe the differences between human evaluations and automatic program analysis based on software evolvability metrics. The empirical component is based on a case study in a Finnish software product company, in which we studied two topics. First, we looked at the effect of the evaluator when subjectively evaluating the existence of smells in code modules. We found that the use of smells for code evaluation purposes can be difficult due to conflicting perceptions of different evaluators. However, the demographics of the evaluators partly explain the variation. Second, we applied selected source code metrics for identifying four smells and compared these results to the subjective evaluations. The metrics based on automatic program analysis and the human-based smell evaluations did not fully correlate. Based upon our results, we suggest that organizations should make decisions regarding software evolvability improvement based on a combination of subjective evaluations and code metrics. Due to the limitations of the study we also recognize the need for conducting more refined studies and experiments in the area of software evolvability.
引用
收藏
页码:395 / 431
页数:37
相关论文
共 50 条
  • [31] An Empirical Study on Code Smells Co-occurrences in Android Applications
    Hamdi, Oumayma
    Ouni, Ali
    AlOmar, Eman Abdullah
    Mkaouer, Mohamed Wiem
    2021 36TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING WORKSHOPS (ASEW 2021), 2021, : 26 - 33
  • [32] Code Smells Detection and Visualization of Software Systems
    Lee, Shin-Jie
    Lin, Xavier
    Lo, Li Hsiang
    Chen, Yu-Cheng
    Lee, Jonathan
    INTELLIGENT SYSTEMS AND APPLICATIONS (ICS 2014), 2015, 274 : 1763 - 1771
  • [33] The Smelly Eight: An Empirical Study on the Prevalence of Code Smells in Quantum Computing
    Chen, Qihong
    Camara, Ruben
    Campos, Jose
    Souto, Andre
    Ahmed, Iftekhar
    2023 IEEE/ACM 45TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ICSE, 2023, : 358 - 370
  • [34] On the Diffusion of Test Smells in Automatically Generated Test Code: An Empirical Study
    Palomba, Fabio
    Di Nucci, Dario
    Panichella, Annibale
    Oliveto, Rocco
    De Lucia, Andrea
    2016 IEEE/ACM 9TH INTERNATIONAL WORKSHOP ON SEARCH-BASED SOFTWARE TESTING (SBST), 2016, : 5 - 14
  • [35] An Empirical Study on the Occurrences of Code Smells in Open Source and Industrial Projects
    Rahman, Md. Masudur
    Satter, Abdus
    Joarder, Md. Mahbubul Alam
    Sakib, Kazi
    PROCEEDINGS OF THE16TH ACM/IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT, ESEM 2022, 2022, : 289 - 294
  • [36] ConcernReCS Finding Code Smells in Software Aspectization
    Alves, Pericles
    Santana, Diogo
    Figueiredo, Eduardo
    2012 34TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE), 2012, : 1463 - 1464
  • [37] On The Relation of Test Smells to Software Code Quality
    Spadini, Davide
    Palomba, Fabio
    Zaidman, Andy
    Bruntink, Magiel
    Bacchelli, Alberto
    PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME), 2018, : 1 - 12
  • [38] A Systematic Literature Review on Empirical Analysis of the Relationship Between Code Smells and Software Quality Attributes
    Amandeep Kaur
    Archives of Computational Methods in Engineering, 2020, 27 : 1267 - 1296
  • [39] A Systematic Literature Review on Empirical Analysis of the Relationship Between Code Smells and Software Quality Attributes
    Kaur, Amandeep
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2020, 27 (04) : 1267 - 1296
  • [40] Object Oriented Metrics Based Empirical Model for Predicting “Code Smells” in Open Source Software
    Kaur S.
    Singh S.
    Journal of The Institution of Engineers (India): Series B, 2023, 104 (01) : 241 - 257