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Showing 3 results for Software
A three- stage algorithm for software cost and time estimation in fuzzy environment
Eng Fateme Zare Baghabad, Dr Hassan Khademi Zare,
Volume 26, Issue 3 (9-2015)
Abstract

In this paper an efficient three- stage algorithm is developed for software production cost and time estimation. First stage includes a hybrid model composed of COCOMO and Function Points methods to increase estimation accuracy. Second stage encompasses paired comparisons matrix of analytical hierarchy process to determine amount of any resources consumed in each step of software production by experts’ opinions. Third stage concludes cost and time tables of production scheduling by using Work break structure (WBS) and network models of project control. In whole of all stages of this paper, triangular fuzzy numbers are used to express uncertainty existed in succession and repetition of each production step, time of beginning, ending, the duration of each task and costs of them. Retrieved results examined by 30 practical projects conclude accuracy of 93 percent for time estimation and 92 percent for cost one. Also suggested algorithm is more accurate than COCOMOІІ 2000 algorithm as 50 percent based on examined problems.

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The State-of-the-art Hybrid Approaches in Regression Testing
Muhammad Asim Siddique,
Volume 34, Issue 4 (12-2023)
Abstract
 
Software testing is the process of assessing the functionality of a software program. The software testing process checks for inaccuracies, gaps and whether the application outcome matches desired expectations before the software is installed and goes into production. Normally in large organizations, the development team allocates a high portion of estimated development time, cost and efficiency for regression testing to assure software testing quality assurance. The quality of developed software relies upon three factors time, efficiency and testing technique used for regression testing. Regression testing is an important component of software testing and maintenance, taking up a significant share of the total testing time, efficiency and resources organizations use in testing techniques. The key to successful regression testing using Test Case Prioritization (TCP), Test case Selection (TCS) and Test Case Minimization (TCM) is maximizing the test cases' effectiveness while considering the limited resources available. Regression testing introduced numerous techniques for (TCP, TCS, TCM) to maximize the efficiency based on Average Percentage Fault Detection (APFD). In recent studies, the TCP and TCS techniques can give the highest APFD score. However, each TCP and TCS approacshow limitations, such as high execution cost, time, efficiency, and lack of information. TCP and TCS approaches that can cover multiple test suite variables (time, cost, efficiency) remained inefficient. Thus, there is a need for a hybrid TCP and TCS technique to be developed to search for the best method that gives a high APFD score while having good coverage of test cases relevant to the cost and execution time to improve efficiency. The proposed hybrid test case selection and prioritization technique will exclude similar & faulty test cases to reduce test size. The proposed hybrid technique has several advantages, including reduced execution time and improved fault detection ability. The proposed hybrid Enhanced Test Case Selection and Prioritization Algorithm ( ETCSA) is a promising approach to select only modified test suites to improve efficiency. However, the efficiency of the proposed technique may depend on the specific criteria for selecting only modified test cases and the software's characteristics. The hybrid technique aims to define an ideal ranking order of test cases, allowing for higher coverage and early fault detection with reduced test suite size. This study reviews TCP and TCS hybrid techniques to reduce testing time, cost and improve efficiency for regression testing. Each TCS and TCP technique in regression testing has identified apparent standards, benefits, and restrictions.

Integrated Delphi-Interpretive Structural Modeling for Sustainable Green Software Development
Zahra Taherikhonakdar, Hamed Fazlollahtabar,
Volume 35, Issue 2 (6-2024)
Abstract
These days, industries, individuals and organizations are highly dependent on software. Software plays an important role in our daily life. They use in embedded systems, databases, computers, mobiles etc.  Great demand for ICT cause environmental problem and endanger the future sustainability.  In this case, sustainable development has become a hot research topic in software engineering community. Sustainability as a software quality is a general term. Therefore, there is a chance that software developers mislead about develops sustainable software. Therefore, there are some questions that should be answered to help practitioners to develop sustainable software: how developers could develop green and sustainable software? What requirements should be considered to reach green and sustainable software? Which non-functional requirement has an effect on each sustainability dimension?   In this paper, we selected 20 non-functional requirements out of 60. It was identified the effective non-functional requirements in green and sustainable software development by using Delphi method then via interpretive structural modeling (ISM). The study aimed to pave the way for software eco-labeling and help users to choose the green and sustainable one. Also, provide software developers with guideline to develop green and sustainable software by identifying effective non-functional requirements. This would lead to the sustainable future and green environment.

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