• DocumentCode
    3561593
  • Title

    A Case Study in Locating the Architectural Roots of Technical Debt

  • Author

    Kazman, Rick ; Yuanfang Cai ; Ran Mo ; Qiong Feng ; Lu Xiao ; Haziyev, Serge ; Fedak, Volodymyr ; Shapochka, Andriy

  • Author_Institution
    SEU/CMU, Univ. of Hawaii, Honolulu, HI, USA
  • Volume
    2
  • fYear
    2015
  • Firstpage
    179
  • Lastpage
    188
  • Abstract
    Our recent research has shown that, in large-scale software systems, defective files seldom exist alone. They are usually architecturally connected, and their architectural structures exhibit significant design flaws which propagate bugginess among files. We call these flawed structures the architecture roots, a type of technical debt that incurs high maintenance penalties. Removing the architecture roots of bugginess requires refactoring, but the benefits of refactoring have historically been difficult for architects to quantify or justify. In this paper, we present a case study of identifying and quantifying such architecture debts in a large-scale industrial software project. Our approach is to model and analyze software architecture as a set of design rule spaces (DRSpaces). Using data extracted from the project´s development artifacts, we were able to identify the files implicated in architecture flaws and suggest refactorings based on removing these flaws. Then we built economic models of the before and (predicted) after states, which gave the organization confidence that doing the refactorings made business sense, in terms of a handsome return on investment.
  • Keywords
    software architecture; software maintenance; DRSpaces; architecture roots; design rule spaces; large-scale industrial software project; large-scale software systems; software architecture flaws; software refactoring; technical debt; Business; Computer architecture; History; Microprocessors; Software engineering; Sonar detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (ICSE), 2015 IEEE/ACM 37th IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICSE.2015.146
  • Filename
    7202962