Finding Incremental Solutions for Evolving Requirements

被引:0
作者
Ernst, Neil A. [1 ]
Borgida, Alexander [2 ]
Jureta, Ivan [3 ]
机构
[1] Univ Toronto, Dept Comp Sci, Toronto, ON M5S 1A1, Canada
[2] Rutgers State Univ, Dept Comp Sci, New Brunswick, NJ USA
[3] Univ Namur, FNRS & Informat Management, Namur, Belgium
来源
2011 19TH IEEE INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE (RE) | 2011年
关键词
Requirements; evolution; incremental; knowledge-level;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This paper investigates aspects of the problem of software evolution resulting from top-level requirements change. In particular, while most research on design for software focuses on finding some correct solution, this ignores that such a solution is often only correct in a particular, and often short-lived, context. Using a logic-based goal-oriented requirements modeling language, the paper poses the problem of finding desirable solutions as the requirements change. Among other possible criteria of desirability, we consider minimizing the effort required to implement the new solution, which involves reusing parts of the old solution. In general, the solution of requirements problems is viewed as an exploration using a "requirements engineering knowledge base" (REKB), whose specification is formalized. The paper reports on experience implementing the REKB on top of a so-called "reason-maintenance system", and provides evidence that incremental solution finding is indeed more efficient.
引用
收藏
页码:15 / 24
页数:10
相关论文
共 31 条
  • [1] [Anonymous], 1993, Building problem solvers
  • [2] [Anonymous], P 8 INT JOINT C ART
  • [3] Baresi L., 2010, INT C REQ ENG SEP
  • [4] Automated analysis of feature models 20 years later: A literature review
    Benavides, David
    Segura, Sergio
    Ruiz-Cortes, Antonio
    [J]. INFORMATION SYSTEMS, 2010, 35 (06) : 615 - 636
  • [5] Pseudo-Boolean optimization
    Boros, E
    Hammer, PL
    [J]. DISCRETE APPLIED MATHEMATICS, 2002, 123 (1-3) : 155 - 225
  • [6] AN ASSUMPTION-BASED TMS
    DEKLEER, J
    [J]. ARTIFICIAL INTELLIGENCE, 1986, 28 (02) : 127 - 162
  • [7] Solving satisfiability problems with preferences
    Di Rosa, Emanuele
    Giunchiglia, Enrico
    Maratea, Marco
    [J]. CONSTRAINTS, 2010, 15 (04) : 485 - 515
  • [8] LINEAR-TIME ALGORITHMS FOR TESTING THE SATISFIABILITY OF PROPOSITIONAL HORN FORMULAE.
    Dowling, William F.
    Gallier, Jean H.
    [J]. Journal of Logic Programming, 1984, 1 (03): : 267 - 284
  • [9] TRUTH MAINTENANCE SYSTEM
    DOYLE, J
    [J]. ARTIFICIAL INTELLIGENCE, 1979, 12 (03) : 231 - 272
  • [10] Do viewpoints lead to better conceptual models? An exploratory case study
    Easterbrook, S
    Yu, E
    Aranda, J
    Fan, YT
    Horkoff, J
    Leica, M
    Qadir, RA
    [J]. 13th IEEE International Conference on Requirements Engineering, Proceedings, 2005, : 199 - 208