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Transpiling Programming Computable Functions to Answer Set Programs Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Enhancing POI Testing Through the Use of Additional Information

Authors : Sergio Pérez, Salvador Tamarit

Published in: Functional and Constraint Logic Programming

Publisher: Springer International Publishing

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Abstract

Recently, a new approach to perform regression testing has been defined: the point of interest (POI) testing. A POI, in this context, is any expression of a program. The approach receives as input a set of relations between POIs from a version of a program and POIs from another version, and also a sequence of entry points, i.e. test cases. Then, a program instrumentation, an input test case generation and different comparison functions are used to obtain the final report which indicates whether the alternative version of the program behaves as expected, e.g. it produces the same outputs or it uses less CPU/memory. In this paper, we present a method to improve POI testing by including additional context information for a certain type of POIs. Concretely, we use this method to obtain an enhanced tracing of calls. Additionally, it enables new comparison modes and a categorization of unexpected behaviours.

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previous chapter Runtime Verification in Erlang by Using Contracts
next chapter Synthesizing Set Functions
Footnotes
1
Although current implementation of POI testing does not still support auto-generation of observation points, it is a key feature that will be part of next release.
 
2
The occurrence argument (2 in the example) can be omitted, selecting in that case the first occurrence of the variable in the indicated line.
 
3
More information about Erlang and how we implemented a POI tester for this language are further discussed in Sect. 4.
 
4
Steps (ii) and (iii) could also be executed in parallel. Here, for the sake of simplicity, we only consider the sequential execution of these steps.
 
5
Note that a trace consists of a sequence of values since a variable can be evaluated several times. Each evaluation is represented by an element of the sequence.
 
6
The observed UnBs are represented and identified using literals, e.g. the atom greater could be used to represent an UnB that occurs when an expression is evaluated to a greater value in the new version than in the old one. The UnB representations are defined during the comparison process as it is then when the UnBs are found.
 
7
All functions presented in Sect. 3 are written in pseudocode. In a particular implementation, all functions should be implemented in the target language.
 
8
We use the notation ai(key) to refer to access some specific information previously stored in the ai mapping. In this case ai(args) represent the arguments of a POI placed in a function call.
 
9
The function presented in Fig. 5, does not make use of parameters TEO, TEN and History to define the message content. However, more complex functions that treat the information stored in these parameters can be defined to obtain a more elaborated message, like the one shown in Fig. 7.
 
10
Function get_ai is defined as https://static-content.springer.com/image/chp%3A10.1007%2F978-3-030-16202-3_5/482311_1_En_5_IEq13_HTML.gif .
 
11
All free variables used in the rule are represented as \(\mathtt {fv_{*}}\). Each one of these free variables is unique and different to all the original variables of the module.
 
12
In our implementation, the Erlang module secer_api provides a list of implemented functions to easily select any execution mode.
 
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Metadata
Title
Enhancing POI Testing Through the Use of Additional Information
Authors
Sergio Pérez
Salvador Tamarit
Copyright Year
2019
Book
Functional and Constraint Logic Programming

Print ISBN: 978-3-030-16201-6

Electronic ISBN: 978-3-030-16202-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-16202-3_5

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