Efficient Software Cost Estimation Using Artificial Intelligence: Incorporating Hybrid Fuzzy Modelling

1. Introduction

Software cost estimation involves predicting the expenses associated with developing a software system, encompassing effort, time, and required resources. These estimates are vital for planning, design, coding, testing, and maintenance phases. Crucial for project planning and management, accurate estimations empower stakeholders to make informed decisions on budgeting, resource allocation, and scheduling, thereby ensuring project success. While numerous software tools employing diverse algorithms and approaches exist to aid in cost estimation, challenges persist in the estimation process.Top of Form

There are numerous factors contributing the complexity of software cost estimation as listed below:

• 1.

  Uncertain and imprecise parameters: Few parameters defining software projects are inherently uncertain. Ambiguous project requirements, wide scope, and changing technology throughout the project makes it difficult to estimate costs accurately.

• 2.

  Enhanced Complexity: Software projects are generally involves multiple technologies, dependencies, and stakeholders. In depth understanding of the complexities involved can contribute to better estimation process.

• 3.

  Missing Related Data: Unavailability of sufficient historical data for related projects makes it challenging to accurately estimate costs based on past experiences.

• 4.

  Dynamicity of Requirements: As the project progresses, stakeholder’s understanding about the need enhances which may result in changing requirements. Estimating costs for projects with evolving requirements can be challenging.

• 5.

  External Cost drivers: There are various external factors, also known as cost drivers, such as experience of personnel involved, technological advancements, system requirements etc. which impact cost estimation for software projects.

• 6.

  Availability of different Estimation Techniques: Different estimation techniques have different strengths and weaknesses, and selecting the right technique is crucial for accurate estimation.

• 7.

  Communication: Effective communication with stakeholders is essential for accurate cost estimation. Misunderstandings or lack of communication may lead to incorrect assumptions and inaccurate estimates.

In order to meet these challenges, researchers are working on incorporating Artificial Intelligence (AI) techniques to meet the offered challenges as stated above and enhance the accuracy and performance of estimation models.AI and ML offers multiple benefits to software development and estimation. AI has the capability to automate the process of code generation and assist bug detection resulting in optimized performance of software development process. For instance, a McKinsey study revealed that integrating AI into development processes can yield significant reductions in both software development costs and time. Additionally, AI can facilitate Predictive Analytics and Data-Driven Development, entailing the analysis of extensive datasets from software development, including code repositories, version control systems, and project management tools. By offering insights and predictions, these analytical approaches enable developers to make informed, data-driven decisions and enhance their development practices for improved results.