ارائه راهکاری مبتنی بر الگوریتم یادگیری معلم و دانش آموز به منظور کاهش موارد آزمون رگرسیون

نوع مقاله : مقاله کامپیوتر

نویسندگان

1 دانشیار، دانشکده رایانه، دانشگاه علوم و فنون هوایی شهید ستاری، تهران، ایران.

2 کارشناسی ارشد، گروه مهندسی کامپیوتر، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران

چکیده

هدف انتخاب موارد آزمون این است که بتوان زیر مجموعه­ای انتخاب شود که قابلیت بالقوه شناسایی خطاهای ناشی از تغییرات را داشته باشد. به عبارتی هدف روش‌های انتخاب موارد آزمون، کاهش تعداد موارد آزمون بعد از تغییر کد است و بر روی شناسایی بخش­های اصلاح شده برنامه تمرکز دارد. روش‌های هوشمند مانند رگرسیون، دقت آزمون را در پروژه‌های نرم افزاری بهبود می‌بخشند و استفاده از الگوریتم­های بهینه سازی در یافتن مقدار بهینه موارد آزمون می­تواند از نظر زمان و سرعت هم مفید واقع شود. در این مقاله تکنیکی برای کاهش موارد آزمون رگرسیون مبتنی برروش بهینه سازی معلم- دانش آموز ارائه می­شود.  این روش از دو مرحله معلم( فاز آموزش) و دانش آموز ( فاز یادگیری) روی مجموعه آزمون تشکیل شده و بر اساس پارامترهای مختلف پیاده‌سازی گردیده است. نتایج آزمایش­ها نشان داد که استفاده از الگوریتم معلم- دانش آموز، زمان لازم برای کاهش موارد آزمون رگرسیون را تا حدی بهبود می­بخشد، هر چند که جواب قطعی را به ما نمی‌دهد و جوابی نزدیک به بهینه را خواهد داد. نتایج حاصل از اجرای رویکرد پیشنهادی با روش­های قبلی انتخاب موارد آزمون مقایسه شده و مشاهده شد که میانگین زمان اجرای موارد آزمون انتخابی، توسط آن بهتر است

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Provide a Solution Based on Teacher and Student Learning Algorithm to Reduce Regression Test Cases

نویسندگان [English]

  • Mahmood Deypir 1
  • Amirhossein Mohammadpour 2
1 Associate Professor, Faculty of Computer Engineering, Shahid Sattari Aeronautical University of Science and Technology, Tehran, Iran
2 MSc, Department Of Computer Engineering, South Tehran Branch, Faculty of Technical and Engineering, Islamic Azad University, Tehran, Iran.
چکیده [English]

The aim of selecting test items is to choose a subset that has the potential to detect errors due to changes within the software. In other words, the purposes of test selection methods is to reduce the number of test cases after changing the code and focus on identifying the modified parts of the program. Intelligent methods such as regression improve the accuracy of tests in software projects, and the use of optimization algorithms to find the optimal amount of test cases can be useful in terms of time and speed, and according to research by examining and optimizing this algorithm in the system. In this paper, a technique for reducing regression test cases based on teacher-student optimization method was presented. This method was studied in two stages of teacher (education phase) and student (learning phase) on the test set and was implemented with different parameters. The experimental results showed that the use of the teacher-student algorithm reduces the time required for the reduction parameters of the regression test to some extent, although it does not give us a definite answer and will give a near-optimal answer. Also, the results of teacher-student algorithm were compared with previous approaches of regression test case reduction. Experimental results show better average execution time for test case selection. 
.

کلیدواژه‌ها [English]

  • Software test
  • Optimization
  • Regression test
  • Teacher and student Learning algorithm

مراجع

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مدل سازی در مهندسی
دوره 22، شماره 78
در حال تکمیل شدن
آبان 1403
صفحه 1-15

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سابقه مقاله

  • تاریخ دریافت: 24 تیر 1402
  • تاریخ بازنگری: 01 آذر 1402
  • تاریخ پذیرش: 10 بهمن 1402

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