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    Author 1
    Altaf Hussain
    Department of Computer Science and BI Khushal Khan Khattak University, Karak, Pakistan
    Summary
    Altaf Hussain holds a Bachelor of Science in Computer Science from the University of Agriculture-Peshawar, Pakistan (2016) and a Master of Science in Computer Science from Khushal Khan Khattak University, Karak-Pakistan (2023). He has actively contributed to research in blockchain, differential privacy, and Federated Learning, particularly focusing on data privacy and security innovations. He has published research articles, showcasing his pioneering work in these areas. His interests span a broad spectrum, including Data Security,Network Security, Artificial Intelligence, Computer Networks, Machine Learning, and Deep Learning. His work is driven for enhancing secure and accurate digital ecosystems through cutting-edge technologies.
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    Free Access | Research Article | 12 November 2024
    Improving Effort Estimation Accuracy in Software Development Projects Using Multiple Imputation Techniques for Missing Data Handling
    by
    Shahida Hayat
    ,
    Wajahat Akbar
    ,
    Tariq Hussain
    ,
    Muhammad Inam Ul Haq
    ,
    Altaf Hussian
    ,
    Irshad Khalil
    ,
    Muhammad Nawaz Khan
    ,
    Samsonova Diana
    IECE Transactions on Intelligent Systematics | Volume 1, Issue 3: 190-202, 2024 | DOI:10.62762/TIS.2024.751418
    Abstract
    The challenge of accurately estimating effort for software development projects is critical for project managers (PM) and researchers. A common issue they encounter is missing data values in datasets, which complicates effort estimation (EE). While several models have been introduced to address this issue, none have proven entirely effective. The Analogy-Based Effort Estimation (ABEE) model is the most widely used approach, relying on historical data for estimation. However, the common practice of deleting cases or cells with missing observations results in a reduction of statistical power and negatively impacts the performance of ABEE, leading to inefficiencies and biases. This study employ... More >
    Graphical Abstract
    Improving Effort Estimation Accuracy in Software Development Projects Using Multiple Imputation Techniques for Missing Data Handling