تولید خودکار آزمایه مبتنی بر توصیف رفتاری قاعده‌محور
محورهای موضوعی : مهندسی برق و کامپیوترعلی حبیبی 1 , رامتین خسروی 2 *
1 - دانشکده مهندسی برق و کامپیوتر، دانشکدگان فنی، دانشگاه تهران، تهران، ایران،
2 - دانشکده مهندسی برق و کامپیوتر، دانشکدگان فنی، دانشگاه تهران، تهران، ایران،
کلید واژه: آزمون مبتنی بر مدل, آزمون جستجومحور, توصیف صوری,
چکیده مقاله :
با رشد روزافزون استفاده از نرم‌افزارها در کاربردهای ایمنی- بحرانی نظیر صنعت خودرو، صنایع دفاعی و صنایع پزشکی، کسب سطوح بالای اطمینان از کیفیت این نرم‌افزارها امری ضروری است. آزمون مبتنی بر مدل به عنوان یک روش تولید خودکار آزمایه از طرفی با پوشش‌دادن یک توصیف صوری از کارکرد سامانه اطمینانی نسبی ایجاد می‌کند که سناریوهای مختلف اجرای برنامه آزموده می‌شوند و از طرف دیگر با خودکارسازی تولید این آزمایه‌ها هزینه تولید آزمون را به شکل چشم‌گیری کاهش می‌دهد. در این پژوهش یک چارچوب آزمون مبتنی بر مدل ارائه شده که از یک مدل قاعده‌محور استفاده می‌کند و بر اساس دو معیار پوشش قاعده و پوشش شرط فعال قاعده توانایی تولید آزمایه دارد. برای تولید آزمایه، این چارچوب از یک رویکرد جستجومحور مبتنی بر الگوریتم ژنتیک استفاده می‌کند. روش پیشنهادی امکان تعریف یک سامانه با فضای حالت بزرگ و تولید آزمایه از آن را ارائه می‌دهد. این چارچوب با انجام مطالعه موردی روی یک نرم‌افزار نهفته صنعتی ارزیابی شده و نتایج ارزیابی‌ها نشان از کاربردی‌بودن آن در مسائل واقعی در صنعت دارند.
With the increasing use of software in safety-critical applications, such as the automotive, defense, and medical industries, achieving high levels of assurance regarding the quality of these software systems is essential. Model-based testing is an automated test-case generation method that, on one hand, provides relative assurance by covering a formal description of the system’s behavior, ensuring that various execution scenarios of the program are tested. On the other hand, by automating the generation of these test cases, it significantly reduces the cost of test production. In this research, a model-based testing framework is presented that utilizes a rule-based model and can generate test cases based on two criteria: rule coverage and active rule condition coverage. To generate test cases, this framework employs a search-based approach using a genetic algorithm. The proposed method enables the definition of a system with a large state space and the generation of test cases for it. The framework has been evaluated through a case study on an embedded industrial software, and the evaluation results demonstrate its applicability to real-world problems in the industry.
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