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بجانی, صادق, کی منش, امیرحسین. (1402). ارائه روشی برای شناسایی موارد آزمون موثر در آزمون نرم‌افزار. پدافند الکترونیکی و سایبری, 11(2), 103-116.
صادق بجانی; امیرحسین کی منش. "ارائه روشی برای شناسایی موارد آزمون موثر در آزمون نرم‌افزار". پدافند الکترونیکی و سایبری, 11, 2, 1402, 103-116.
بجانی, صادق, کی منش, امیرحسین. (1402). 'ارائه روشی برای شناسایی موارد آزمون موثر در آزمون نرم‌افزار', پدافند الکترونیکی و سایبری, 11(2), pp. 103-116.
بجانی, صادق, کی منش, امیرحسین. ارائه روشی برای شناسایی موارد آزمون موثر در آزمون نرم‌افزار. پدافند الکترونیکی و سایبری, 1402; 11(2): 103-116.

ارائه روشی برای شناسایی موارد آزمون موثر در آزمون نرم‌افزار

پدافند الکترونیکی و سایبری
دوره 11، شماره 2 - شماره پیاپی 42، تیر 1402، صفحه 103-116    اصل مقاله (1022.64 K)
نوع مقاله: مقاله پژوهشی
نویسندگان
صادق بجانی* 1؛ امیرحسین کی منش2
1استادیار، دانشگاه جامع امام حسین (ع)، تهران، ایران
2دانشجوی کارشناسی ارشد، دانشگاه جامع امام حسین (ع)، تهران، ایران
تاریخ دریافت: 17 مهر 1401،  تاریخ بازنگری: 27 فروردین 1402،  تاریخ پذیرش: 27 اردیبهشت 1402 
چکیده
تولید داده آزمون، یکی از بخش‌های پرهزینه در آزمون نرم‌افزار است که با توجه به موارد آزمون طراحی‌شده، انجام می‌شود. مسئله‌ی طراحی موارد آزمون و سپس تولید داده آزمون بهینه، یکی از چالش‌های موجود در آزمون نرم‌افزار، ازجمله فن آزمون جهش است. آزمون جهش، این توانایی را دارد که کیفیت موارد آزمون را بسنجد و موارد آزمون باکفایت را مشخص نماید. بااین‌حال، برای انجام آزمون جهش، به مجموعه آزمونی نیاز است که بتواند کد منبع را به‌صورت حداکثری پوشش دهد و از این طریق، توانایی شناسایی خطاهای برنامه را داشته باشد. در این مقاله، از فنون پوشش کد، برای طراحی موارد آزمون و از الگوریتم فرا-ابتکاری FA-MABC برای تولید خودکار داده آزمون بهینه، استفاده می‌شود. نتایج این کار، مجموعه آزمونی است که می‌تواند حداکثر خطوط کد منبع را پوشش داده و آزمون کند. چنین مجموعه آزمونی، توانایی بالایی در شناسایی خطاهای برنامه دارد و در آزمون جهش، امتیاز بالایی کسب می‌کند. در روش پیشنهادی، برای رسیدن به موارد آزمون مؤثر، ابتدا موارد آزمون طراحی‌شده، در آزمون جهش اعمال می‌شوند و با استفاده از جدول جهش‌های خاموش‌شده، موارد آزمون مؤثر استخراج می‌شوند. نتایج ارزیابی، نشان می‌دهد که الگوریتم FA-MABC، موجب کاهش هزینه زمانی در تولید داده آزمون می‌شود و معیار پوشش «شرط اصلاح‌شده / تصمیم»، موجب افزایش امتیاز جهش می‌شود.
کلیدواژه‌ها
تولید خودکار داده آزمون بهینه؛ آزمون جهش؛ الگوریتم FA-MABC؛ پوشش کد؛ موارد آزمون مؤثر
عنوان مقاله [English]
A novel way to identify effective test-case in software testing
نویسندگان [English]
Sadegh Bejani1؛ Amir Hossein keymanesh2
1Assistant Professor, Imam Hossein University (AS), Tehran, Iran
2Master's student, Imam Hossein University (AS), Tehran, Iran
چکیده [English]
Test data generation is one of the costly parts of the software testing, which is performed according to the designed test cases. The problem of designing test cases and then generating optimized test data is one of the challenges of the software testing, including the mutation testing technique. mutation testing has the ability to measure the test cases quality and determine the adequate test cases. However, to perform mutation testing, you need a test set that provides the maximize Coverage of source code and thus have the ability to identify the program errors. In this work, we use code coverage techniques to design test cases and automatically generate optimized test data using the meta-heuristic FA-MABC algorithm. The results are a test suite that cover and test the maximum number of source code lines. Such test suite is more likely to identify errors and get a higher score in the mutation testing. In the proposed method to obtain effective test cases, first generated test cases are applied to mutation testing and then effective test cases are extracted using the Extinguished mutation table. The results of the evaluation show that the FA-MABC algorithm reduces the time of the test data generation, and “modified condition / decision coverage”, increases the mutation score.
کلیدواژه‌ها [English]
Automatically Generate Optimized Test Data, Mutation Testing, FA-MABC Algorithm, Code Coverage, Effective Test Cases
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