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  • 标题:A Metrics Suite for Variable CategorizationtTo Support Program Invariants
  • 本地全文:下载
  • 作者:P.Radhika Raju ; A.Ananda Rao
  • 期刊名称:International Journal of Software Engineering & Applications (IJSEA)
  • 印刷版ISSN:0976-2221
  • 电子版ISSN:0975-9018
  • 出版年度:2014
  • 卷号:5
  • 期号:5
  • 页码:65
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Invariants are generally implicit. Explicitly stating program invariants, help programmers to identifyprogram properties that must be preserved while modifying the code. Existing dynamic techniques detectinvariants which includes both relevant and irrelevant/unused variables and thereby relevant andirrelevant invariants involved in the program. Due to the presence of irrelevant variables and irrelevantinvariants, speed and efficiency of techniques are affected. Also, displaying properties about irrelevantvariables and irrelevant invariants distracts the user from concentrating on properties of relevantvariables. To overcome these deficiencies only relevant variables are considered by ignoring irrelevantvariables. Further, relevant variables are categorized as design variables and non-design variables. Forthis purpose a metrics suite is proposed. These metrics are validated against Weyuker’s principles andapplied on RFV and JLex open source software. Similarly, relevant invariants are categorized as designinvariants, non-design invariants and hybrid invariants. For this purpose a set of rules are proposed. Thisentire process enormously improves the speed and efficiency of dynamic invariant detection techniques.
  • 关键词:Program invariants; Design variables; Non-design variables; Metrics; Invariants.
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