Estimating Complexity of Programs in Python Language

Software metrics determine the degree of maintainability of software products, which is one of the important factors that affect the quality of any kind of software. Furthermore, software metrics provide useful feedback to the designers to impact the decisions that are made during design, coding, architecture, or specification phases. Without such feedback, many decisions are made in ad hoc manner. Fenton defines measurement as the process by which numbers or symbols are assigned to attributes of entities in the real world in such a way as to describe them according to clearly defined unambiguous rules [6]. In software engineering software metrics are the only tools to control the quality of software. Furthermore, requirement to improve the software quality is the prime objective, which promoted the research projects on software metrics technology. It is always hard to control the quality if the code is complex. Complex codes always create problems to software community. It is hard to review, test, maintain as well as manage such codes. As a consequence, those handicaps increase the maintenance cost and the cost of the product. Due to these reasons, it is strongly recommended to control the complexity of the code from the beginning of the software development process. Software metrics help to achieve this goal. In fact, there are no strict rules, which can prove that code is good or bad. Several researchers proposed different criteria for developing the good and quality software. Although they consider the different aspect of the quality one thing is common in all the criteria i.e. the code should be agile [31]. Specially, in object oriented software developments, which have an extraordinary acceptance in last two decades, it is a must. In other words, the code should be written in such a way that it should be reused and adopted. If code is not agile then it is hard to replace (add or