Avoiding Some Common Preprocessing Pitfalls with Feature Queries

被引:0
|
作者
Jarzabek, Stan [1 ]
Xue, Yinxing [1 ]
Zhang, Hongyu [2 ]
Lee, Youpeng [2 ]
机构
[1] Natl Univ Singapore, Dept Comp Sci, Singapore 117548, Singapore
[2] Tsinghua Univ, Sch Software, Beijing, Peoples R China
关键词
preprocessing; product variants; reuse; variation mechanisms;
D O I
10.1109/APSEC.2009.61
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Preprocessors (e.g., cpp) provide simple means to manage software product variants by including/excluding required feature code to/from base program. Feature-related customizations occur at variation points in base program marked with preprocessing directives. Problems emerge when the number of inter-dependent features grows, and each feature maps to many variation points in many base program components. Component-based and architecture-centric techniques promoted by a Software Product Line approach to reuse help us contain the impact of some features in small number of base components. Still, accommodating other features into product variants requires fine granular code changes in many components, at many variation points. Fine granular code level changes are often handled by preprocessors, which becomes a source of well-known complications during component customization for reuse. In this paper, we show how some of the common preprocessing problems can be alleviated with a query-based environment that assists programmers in analysis of features handled with preprocessor's directives. We describe problems of preprocessing that can be aided by tool like ours, and problems that we believe are inherent in approaches that attempt to manage features in the base code.
引用
收藏
页码:283 / +
页数:2
相关论文
共 50 条
  • [21] Avoiding common pitfalls when clustering biological data
    Ronan, Tom
    Qi, Zhijie
    Naegle, Kristen M.
    SCIENCE SIGNALING, 2016, 9 (432)
  • [22] SOME COMMON NEUROLOGIC PITFALLS
    SMITH, BH
    POSTGRADUATE MEDICINE, 1962, 31 (06) : 546 - &
  • [23] Demand Queries with Preprocessing
    Feige, Uriel
    Jozeph, Shlomo
    AUTOMATA, LANGUAGES, AND PROGRAMMING (ICALP 2014), PT I, 2014, 8572 : 477 - 488
  • [24] PREPROCESSING PREDICATES AND QUERIES
    SUN, XH
    KAMEL, N
    INFORMATION SYSTEMS, 1992, 17 (06) : 465 - 475
  • [25] Avoiding common pitfalls in machine learning omic data science
    Teschendorff, Andrew E.
    NATURE MATERIALS, 2019, 18 (05) : 422 - 427
  • [26] Challenges in research on phytochemicals: Avoiding some potential pitfalls
    Sorkin, Barbara
    Hopp, D.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2017, 254
  • [27] Avoiding 5 Common Pitfalls of Simulation Design in Medical Education
    Soffler, Morgan I.
    Ricotta, Daniel N.
    Hayes, Margaret M.
    Shapiro, Carl J.
    ACADEMIC MEDICINE, 2021, 96 (01) : 157
  • [28] Observational studies: practical tips for avoiding common statistical pitfalls
    Sterrantino, Anna Freni
    LANCET REGIONAL HEALTH - SOUTHEAST ASIA, 2024, 25
  • [29] The methodology of cost-effectiveness analysis: Avoiding common pitfalls
    Elliott, SL
    Harris, AH
    MEDICAL JOURNAL OF AUSTRALIA, 1997, 166 (12) : 636 - 639
  • [30] ETHICS IN FAMILY-LAW PRACTICE - AVOIDING COMMON PITFALLS
    MIRMAN, DM
    TRIAL, 1993, 29 (09): : 70 - 70