Ant Colony Optimization Based Algorithm for Test Path Generation Problem with Negative Constraints

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F25%3A00563694" target="_blank" >RIV/60162694:G42__/25:00563694 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21230/24:00378799

Result on the web

<a href="https://ieeexplore.ieee.org/xpl/conhome/9724650/proceeding" target="_blank" >https://ieeexplore.ieee.org/xpl/conhome/9724650/proceeding</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/QRS62785.2024.00075" target="_blank" >10.1109/QRS62785.2024.00075</a>

Result language

angličtina

Original language name

Ant Colony Optimization Based Algorithm for Test Path Generation Problem with Negative Constraints

Original language description

Path-based testing is an established method for creating test cases comprising sequences of steps executed in a System Under Test (SUT). Several algorithms for generating the test sequences (paths) that satisfy various test coverage criteria determining their properties are published in the literature. However, existing path-based testing techniques have limited applicability in numerous practical cases, such as when executing a particular test step in the test further excludes the execution of another test step. More complex exclusion requirements (further denoted negative constraints) exist in real systems, depending on the number of executions of a particular test step. In the paper, we discuss two possible negative constraints, namely, (1) the complete exclusion of a step as a consequence of the execution of a particular previous step and (2) the requirement to include a particular step maximally once in one test path, when another step was executed previously. We present a novel ant-colony-optimization (ACO) principle-based algorithm, accepting a SUT model based and a set of negative constraints, and computing a set of test paths while maximizing edge coverage and satisfying the given set of negative constraints. We compare the results of the ACO-based algorithm with those returned by a baseline, an alternative algorithm that excludes specific test paths from a set of test paths satisfying edge coverage, and, for reference, with results returned by an algorithm that generates test paths that satisfy edge coverage. Evaluated on 152 problem instances, the presented ACO-based algorithm outperformed the baseline in the average length of test paths (representing the testing costs) lower by 32.62%. Also, the ratio of edge coverage satisfaction in the set of test paths computed by the ACO-based algorithm is better by 3.41% compared to the baseline.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

50900 - Other social sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

IEEE International Conference on Software Quality Reliability and Security

ISBN

979-8-3503-6563-4

ISSN

2693-9185

e-ISSN

2693-9177

Number of pages

12

Pages from-to

701-712

Publisher name

IEEE COMPUTER SOC

Place of publication

—

Event location

Cambridge, ENGLAND

Event date

Jul 1, 2024

Type of event by nationality

CST - Celostátní akce

UT code for WoS article

001327094200065