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Automatically Identifying Calling-Prone Higher-Order Functions of Scala Programs to Assist Testers

Xu, Yi-Sen ; Jia, Xiang-Yang ; Wu, Fan ; Li, Lingbo ; Xuan, Ji-Feng

Journal of computer science and technology, 2020-11, Vol.35 (6), p.1278-1294 [Periódico revisado por pares]

Singapore: Springer Singapore

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  • Título:
    Automatically Identifying Calling-Prone Higher-Order Functions of Scala Programs to Assist Testers
  • Autor: Xu, Yi-Sen ; Jia, Xiang-Yang ; Wu, Fan ; Li, Lingbo ; Xuan, Ji-Feng
  • Assuntos: Algorithms ; Artificial Intelligence ; Computer programming ; Computer Science ; Data Structures and Information Theory ; Functional programming ; Information Systems Applications (incl.Internet) ; Prediction models ; Programming languages ; Redundancy ; Regular Paper ; Resource scheduling ; Software Engineering ; Source code ; Theory of Computation
  • É parte de: Journal of computer science and technology, 2020-11, Vol.35 (6), p.1278-1294
  • Descrição: For the rapid development of internetware, functional programming languages, such as Haskell and Scala, can be used to implement complex domain-specific applications. In functional programming languages, a higher-order function is a function that takes functions as parameters or returns a function. Using higher-order functions in programs can increase the generality and reduce the redundancy of source code. To test a higher-order function, a tester needs to check the requirements and write another function as the test input. However, due to the complex structure of higher-order functions, testing higher-order functions is a time-consuming and labor-intensive task. Testers have to spend an amount of manual effort in testing all higher-order functions. Such testing is infeasible if the time budget is limited, such as a period before a project release. In practice, not every higher-order function is actually called. We refer to higher-order functions that are about to be called as calling-prone ones. Calling-prone higher-order functions should be tested first. In this paper, we propose an automatic approach, namely P hof , which predicts whether a higher-order function of Scala programs will be called in the future, i.e., identifying calling-prone higher-order functions. Our approach can assist testers to reduce the number of higher-order functions of Scala programs under test. In P hof , we extracted 24 features from source code and logs to train a predictive model based on known higher-order function calls. We empirically evaluated our approach on 4 832 higher-order functions from 27 real-world Scala projects. Experimental results show that P hof based on the random forest algorithm and the Synthetic Minority Oversampling Technique Processing strategy (SMOTE) performs well in the prediction of calls of higher-order functions. Our work can be used to support the scheduling of limited test resources.
  • Editor: Singapore: Springer Singapore
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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