Enhancing Search-based Testing with Testability Transformations for Existing APIs

被引:18
|
作者
Arcuri, Andrea [1 ,2 ]
Galeotti, Juan P. [3 ,4 ,5 ]
机构
[1] Kristiania Univ Coll, Prinsens Gate 7-9, N-0152 Oslo, Norway
[2] Oslo Metropolitan Univ, Prinsens Gate 7-9, N-0152 Oslo, Norway
[3] Univ Buenos Aires, Fac Ciencias Exactas & Nat, Dept Computat, Buenos Aires, DF, Argentina
[4] CONICET UBA, ICC, Buenos Aires, DF, Argentina
[5] Pabellon 1,Ciudad Univ,Intendente Guiraldes 2160, Buenos Aires, DF, Argentina
基金
欧洲研究理事会;
关键词
SBST; test generation; testability transformation; system testing; REST; TEST DATA GENERATION; SYMBOLIC EXECUTION; SOFTWARE; SUITE;
D O I
10.1145/3477271
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Search-based software testing (SBST) has been shown to be an effective technique to generate test cases automatically. Its effectiveness strongly depends on the guidance of the fitness function. Unfortunately, a common issue in SBST is the so-called flag problem, where the fitness landscape presents a plateau that provides no guidance to the search. In this article, we provide a series of novel testability transformations aimed at providing guidance in the context of commonly used API calls (e.g., strings that need to be converted into valid date/time objects). We also provide specific transformations aimed at helping the testing of REST Web Services. We implemented our novel techniques as an extension to EvoMaster, an SBST tool that generates system-level test cases. Experiments on nine open-source REST web services, as well as an industrial web service, show that our novel techniques improve performance significantly.
引用
收藏
页数:34
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