Automated testing for Java programs using JPF-based test case generation

Monpratarnchai, Supasit; Fujiwara, Shoichiro; Katayama, Asako; Uehara, Tadahiro

doi:10.1145/2557833.2560575

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…The data were collected from the subjects only at one time instead of collecting several times. In this experiment, the number of subjects was ten (10).…”

Section: Resultsmentioning

confidence: 99%

“…By default, APA necessitates test data to execute dynamic testing on students' program [1]. In software testing, manually or unsystematically generating test data is laborious, prone to errors, demanding, an expensive, and feasible task in practice [10]. Dealing with these concerns, some methods to realize automated test data generations have been proposed in the industry [11]- [16].…”

Section: Introductionmentioning

confidence: 99%

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Automated Test Cases and Test Data Generation for Dynamic Structural Testing in Automatic Programming Assessment Using MC/DC

Romli

Sarker

Omar

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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Automatic Programming Assessment (or APA) is known as a method to assist educators in executing automated assessment and grading on students' programming exercises and assignments. Having to execute dynamic testing in APA, providing an adequate set of test data via a systematic process of test data generation is necessarily essential. Though researches respecting to software testing have proposed various significant methods to realize automated test data generation, it occurs that recent studies of APA rarely utilized these methods. Merely some of the limited studies appeared to resolve this circumstance, yet the focus on realizing test set and test data covering more thorough dynamic-structural testing are still deficient. Thus, we propose a method that utilizes MC/DC coverage criteria to support more thorough automated test data generation for dynamic-structural testing in APA (or is called DyStruc-TDG). In this paper, we reveal the means of deriving and generating test cases and test data for the DyStruc-TDG method and its verification concerning the reliability criteria (or called positive testing) of test data adequacy in programming assessments. This method offers a significant impact on assisting educators dealing with introductory programming courses to derive and generate test cases and test data via APA regardless of having knowledge of designing test cases mainly to execute structural testing. As regards to this, it can effectively reduce the educators' workload as the process of manual assessments is typically prone to errors and promoting inconsistency in marking and grading.

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“…The data were collected from the subjects only at one time instead of collecting several times. In this experiment, the number of subjects was ten (10).…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated Test Cases and Test Data Generation for Dynamic Structural Testing in Automatic Programming Assessment Using MC/DC

Romli

Sarker

Omar

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

View full text Add to dashboard Cite

show abstract

“…In software testing research, various studies propose automated methods for test data generation [29][30][31][32][33][34][35][36][37][38][39]. Despite the potentials of the proposed methods in providing the most efficient way to generate test data for large-scale projects, researches in APA seldom adopt these methods.…”

Section: Introductionmentioning

confidence: 99%

Improving the Reliability and Validity of Test Data Adequacy in Programming Assessments

2015

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Automatic Programming Assessment (or APA) has recently become a notable method in assisting educators of programming courses to automatically assess and grade students’ programming exercises as its counterpart; the typical manual tasks are prone to errors and lead to inconsistency. Practically, this method also provides an alternative means of reducing the educators’ workload effectively. By default, test data generation process plays an important role to perform a dynamic testing on students’ programs. Dynamic testing involves the execution of a program against different inputs or test data and the comparison of the results with the expected output, which must conform to the program specifications. In the software testing field, there have been diverse automated methods for test data generation. Unfortunately, APA rarely adopts these methods. Limited studies have attempted to integrate APA and test data generation to include more useful features and to provide a precise and thorough quality program testing. Thus, we propose a framework of test data generation known as FaSt-Gen covering both the functional and structural testing of a program for APA. Functional testing is a testing that relies on specified functional requirements and focuses the output generated in response to the selected test data and execution, Meanwhile, structural testing looks at the specific program logic to verify how it works. Overall, FaSt-Gen contributes as a means to educators of programming courses to furnish an adequate set of test data to assess students’ programming solutions regardless of having the optimal expertise in the particular knowledge of test cases design. FaSt-Gen integrates the positive and negative testing criteria or so-called reliable and valid test adequacy criteria to derive desired test data and test set schema. As for the functional testing, the integration of specification-derived test and simplified boundary value analysis techniques covering both the criteria. Path coverage criterion guides the test data selection for structural testing. The findings from the conducted controlled experiment and comparative study evaluation show that FaSt-Gen improves the reliability and validity of test data adequacy in programming assessments.

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Design of Test Data Generation Method for Dynamic- Functional Testing in Automatic Programming Assessment Using Flower Pollination Algorithm

Mokhtar

Romli

et al. 2022

Advances on Intelligent Informatics and Computing

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Automated testing for Java programs using JPF-based test case generation

Cited by 8 publications

References 3 publications

Automated Test Cases and Test Data Generation for Dynamic Structural Testing in Automatic Programming Assessment Using MC/DC

Automated Test Cases and Test Data Generation for Dynamic Structural Testing in Automatic Programming Assessment Using MC/DC

Improving the Reliability and Validity of Test Data Adequacy in Programming Assessments

Design of Test Data Generation Method for Dynamic- Functional Testing in Automatic Programming Assessment Using Flower Pollination Algorithm

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