Open In App

Automation Estimation Tools

Improve
Improve
Like Article
Like
Save
Share
Report

The decomposition technique and empirical estimation model are available as part of a range of software tools. Such automated estimation tools are helpful in estimating cast and effort and conducting “what-if” analysis for important project variables, such as delivery data or staffing. All automated estimation tools display the same general characteristics, and all perform the following generic functions-

  1. Sizing of Project Deliverable : Estimated the size of one or more work products i.e., external representation of software, software itself, distributed functionality, descriptive information, all are approximate first.
  2. Selecting Project Activities : The required process framework is selected and the software engineering project is specified.
  3. Predicting Staffing Levels : The number of people available is specified. This is an important task, because the relationship between the people available and work is highly inauspicious.
  4. Predicting Software Effort : The estimation tool related to the use of some models from the size of project deliverable to the effort required (from producing them).
  5. Predicting Software Cost : Software costs can be calculated by assigning labor rates to project activities.
  6. Predicting Software Schedules : Having knowledge of effort, staffing level and project activities, a draft schedule can be produced by allocating lober in software engineering activities based on the recommended model for effort distribution.

Here are the few automation estimation tools:

  1. Time monitoring tools: Programmes such as Harvest or Toggl assist keep track of how much time is spent on activities, but they also offer insights into previous information, which helps make future estimations more accurate.
  2. Tools for Test Automation: Tools such as Selenium or Appium automate the testing process during the testing phase.
  3. Tools for Continuous Integration/Continuous Deployment (CI/CD): These tools facilitate a more efficient and error-free release process while also accelerating development.
  4. Planning and Estimation Tools: Together estimating the amount of work needed for projects or user stories is made easier by tools like Planning Poker.
  5. Requirements Management Tools: Software such as IBM Engineering connects the process of gathering, monitoring and maintaining project requirements is automated with requirements management systems.
  6. Machine Learning-Based Estimation Tools: Based on previous information, team performance and other project criteria, these tools use machine learning algorithms to generate more precise and based on fact estimations.
  7. Tools for Resource Management: Applications such as Resource Guru facilitate effective team resource scheduling and management.
  8. Code Review Tools: By evaluating code for quality, security and maintainability, tools such as Code Climate can automate certain steps in the code review process.

Applying different estimation tools to the same project data results in a relatively large change in the predicted results. Furthermore, more important, the estimated values are after significant different than the actual values. This reinforces the notion that the output of the estimation devices should be used as a data point from which the estimated are made. Automated estimation from these data estimates the model projects, costs, staff trading implemented by the tool and, in some cases, the development schedule and the effort required to meet the associated risk. WICOMO (Wang Institute Cost Model) developed at the Wang institute, and DECplan developed by digital equipment corporation are automated estimation tools that are based on

COCOMO

. Each device needs to provide the user with preliminary 20 c estimated. These approximations are classified by programming language and type (i.e., customized code, reused code, new code). the user also specifies the value for the cost driver attributes. Each of the tools produces an estimated project duration (in months), effort in staff-month, average staffing per month, average productivity in LOC/pm, and cost per month. SLIM is an automated costing system based on the Rayleigh Putnam model SLIM applies the Putnam software model, linear programming, statistical simulation, and program evaluation and review technique, or

PERT techniques

to derive software project estimates. Once the software size is established, SLIM calculates the size deviation, a sensitivity profile that indicates the possible deviation of cost and effort, and a consistency with the data collected for software systems of similar size the inspection. The planner can implement a linear programming analysis that considers development costs on both cost and effort and month-by month distribution of effort and a consistency check with data collected for software systems of similar size.


Last Updated : 15 Nov, 2023
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads