مقایسه روش های طبقه بندی در تخمین تلاش توسعه نرم افزار
محورهای موضوعی : سامانه های پردازشی و ارتباطی چند رسانه ای هوشمند
صادق انصاری پور
1
(دانشگاه عقیق، شاهین شهر، اصفهان)
تقی جاودانی گندمانی
2
(عضو هیات علمی، دانشگاه شهرکرد)
کلید واژه: تخمین تلاش نرم افزار, طبقه بندی, یادگیری ماشین, مهندسی نرم افزار, داده کاوی,
چکیده مقاله :
نادرست بودن تخمین هزینه نرم افزار یکی از دلایل مهم ناامیدی متخصصان نرم افزار و محققان تخمین هزینه بوده است و علیرغم تلاش های فراوانی که برای بهبود آن انجام شده است اما هنوز هم دقت تخمین پایین است. عدم تجزیه و تحلیل مناسب در ابتدای شروع به کار پروژه و همچنین عدم به روز آن در حین انجام پروژه یکی از مهم ترین دلایل شکست پروژه ها محسوب می شود. اگر چه زمانی که یک پروژه‌ها بسته می‌شوند، بازخورد های آن ایجاد می‌شود، اما اگر تخمین‌ها و واقعیات ثبت‌شده با پروژه انجام‌شده به طور کامل مطابقت نداشته باشند، آنگاه نمی توان انتظار تخمین دقیقی را داشت. بنابراین جمع آورده داده های پروژه بر اساس ویژگی های مشخص امری ضروری است و در اینجاست که می توان به نقش پررنگ پروژه های انجام شده در گذشته و مجموعه داده هایی که می توان با استفاده از آنها ایجاد نمود پی برد. در این مطالعه سعی بر این است که به بررسی نقش روش های مختلف طبقه بندی در تخمین تلاش نرم افزار بپردازیم.
Introduction: The main goal of software companies is to provide solutions in various fields to better meet the needs of customers. The process of successful modeling depends on finding the right and accurate requirements. However, the key to successful development for adapting and integrating different developed parts is the importance of selecting and prioritizing the requirements that will advance the workflow and ultimately lead to the creation of a quality product. Validation is the key part of the work, which includes techniques that confirm the accuracy of a set of requirements for building a solution that leads to the project's business objectives. Requirements change during the project, and managing these changes is important to ensure the accuracy of the software built for stakeholders. In this research, we will discuss the process of checking and validating the software requirements.Method: Requirement extraction is conducted by means of discovery, review, documentation, and understanding of user needs and limitations of a system. The results are presented in the form of products such as text requirements descriptions, use cases, processing diagrams, and user interface prototypes.Findings: Data mining and recommender systems can be used to increase the necessary needs, however, another method. of social networks and joint filtering can be used to create requirements for large projects to identify needs.Discussion: In the area of product development, requirements engineering approaches focus exclusively on requirement development. There are challenges in the development process due to the existence of human resources. If the challenges are not seen well at this stage, it will be extremely expensive after the software production. Therefore, in this regard, errors should be minimized and they should be identified and corrected as soon as possible. Now, with the investigations carried out, one of the key issues in the field of requirements is the discussion of validation, which first confirms that the requirements are able to be implemented in a set of characteristics according to the system description, and secondly, a set of essential characteristics. such as complete, consistent, according to standard criteria, non-contradiction of requirements, absence of technical errors, and lack of ambiguity in requirements. In fact, the purpose of validation is to ensure the result that a sustainable and renewable product is created according to the requirements.
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