Beyond Unit-Testing in Search-Based Test Case Generation: Challenges and Opportunities

2019 ◽  
Author(s):  
Annibale Panichella
Keyword(s):  
Test Case Generation ◽  
Test Case ◽  
Unit Testing ◽  
Challenges And Opportunities

scholarly journals Exploring Software Security Test Generation Techniques: Challenges and Opportunities

2021 ◽  
Vol 15 ◽  
pp. 107-121
Author(s):  
Mamdouh Alenezi ◽  
Mohammed Akour ◽  
Hamid Abdul Basit
Keyword(s):  
Test Generation ◽  
Software Security ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Current State ◽  
Development Life Cycle ◽  
Challenges And Opportunities ◽  
Software Development Life Cycle ◽  
Security Test

Ensuring the security of the software has raised concerns from the research community which triggered numerous approaches that tend to eliminate it. The process of ensuring the security of software includes the introduction of processes in the Software Development Life Cycle where one of them is testing after the software is developed. Manually testing software for security is a labor-intensive task. Therefore, it is required to automate the process of testing by generating test cases by automated techniques. In this paper, we review various software security test case generation approaches and techniques. We try to explore and classify the most eminent techniques for test case generation. The techniques are summarized and presented briefly to covers all researches work that has been done in the targeted classification. Moreover, this paper aims to depict the sound of security in the current state of the art of test case generation. The findings are summarized and discussed where the opportunities and challenges are revealed narratively. Although the paper intends to provide a comprehensive view of the research in test case generation, there was a noticeable lack in the test case generation from the security perspectives

scholarly journals Pengembangan sistem otomatisasi pembangkitan kasus uji dengan algoritma genetika dan test case generation method

Teknologi ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Moh Arsyad Mubarak Setyawan ◽  
Fajar Pradana ◽  
Bayu Priyambadha
Keyword(s):  
Software Testing ◽  
Directed Graph ◽  
Control Flow ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Unit Testing ◽  
Control Flow Graph ◽  
Population Number ◽  
Flow Graph

Pengujian perangkat lunak merupakan salah satu bagian penting dari pembuatan perangkat lunak. Pada pengujian perangkat lunak terdapat pengujian unit. Pengujian unit merupakan proses pengujian komponen yang berfokus untuk memverifikasi unit terkecil pada perancangan perangkat lunak. Pada tahap pengujian unit terdapat proses pembangkitan kasus uji. Selama ini, pembangkitan kasus uji dari suatu kode program dilakukan secara manual se-hingga membutuhkan waktu yang lama. Hal ini dikarenakan banyaknya kemungkinan jalur pada kode sumber yang akan diuji.  Dalam penelitian ini dibangun suatu sistem otomatis untuk membangkitkan kasus uji. Alur kerja sistem dimulai dari analisa kode sumber dengan Spoon Library, selanjutnya dibentuk CFG (Control Flow Graph) dan DDG (Dynamic Directed Graph). Dari DDG tersebut akan dibangkitkan jalur layak yang terdapat pada DDG, dengan menggunakan algoritma genetika diharapkan dapat mengoptimalkan penentuan jalur independen. Dari masing-masing jalur independen akan dibangkitkan kasus ujinya dengan metode test case generation. Pengujian akurasi sistem pada sistem otomatisasi pembangkit kasus uji dengan jumlah populasi 5, 10 dan 15 serta jumlah maksimum generasi 50, 100, 200 dan 250 dihasilkan jumlah populasi paling optimal yaitu 10 dan maksimum generasi optimal yaitu 200 dengan akurasi 93,33%. Pada jumlah populasi dan maksimum generasi sesudahnya tidak terjadi peningkatan akurasi yang signifikan. Tiap peningkatan jumlah populasi dan maksimum generasi dapat meningkatkan akurasi sistem.  Software testing is one of the most important part of making software. On the software testing there are unit testing. Unit Testing is a process for verifying component, focusing on the smallest unit of software design. In the unit testing phase contained test case generation process. During this time, the generation of test cases of a program code is done manually. In this study, constructed an automated system to generate test cases. The workflow system starts from the analysis of the source code with the library spoon and then create CFG (Control Flow Graph) and DDG (Dynamic Directed graph). From the DDG will be raised feasible path using a genetic algorithm. Furthermore, from fea-sible path sought independenth path which is a path base d on the level of uniqueness of the path to the other path. From each independenth path raised the test case with a test case generation method. Testing accuracy of the system on the automation system generating test cases with populations of 5,10 and 15 as well as the maximum number of generations 50, 100, 200 and 250 produced the most optimal population number is 15 and the most optimal maximum generation is 200 with accuracy 93.33%. Each increase in the number of population and maximum generation can improve the accuracy of the system. Level accuracy with population number over 10 and maximum generation over 200 has no increace accuracy significant.

A PERFORMANCE EVALUATION OF HEURISTICS-BASED TEST CASE GENERATION METHODS FOR SOFTWARE BRANCH COVERAGE

1996 ◽  
Vol 06 (04) ◽  
pp. 585-608 ◽  
Author(s):  
KAI H. CHANG ◽  
JAMES H. CROSS II ◽  
W.HOMER CARLISLE ◽  
SHIH-SUNG LIAO
Keyword(s):  
Performance Evaluation ◽  
Software Testing ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Unit Testing ◽  
Heuristic Rules ◽  
Generation System ◽  
Branch Coverage ◽  
Prototype Test

Software testing is an important step in the development of complex systems. The construction of test cases using traditional methods usually requires considerable manual effort. QUEST/Ada—Query Utility Environment for Software Testing of Ada, is a prototype test case generation system that uses various heuristics-based approaches to generate test cases. The system, which is designed for unit testing, generates test cases by monitoring the branch coverage progress and intelligently modifying existing test cases to achieve additional coverage. Three heuristics-based approaches along with a random test case generation method were studied to compare their branch coverage performance. Although some constraints are imposed by the prototype, the framework provides a useful foundation for further heuristics-based test case generation research. The design of the system, the heuristic rules used in the system, and an evaluation of each rule’s performance are presented.

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