V D Shanmukha Mitra supervised by Dr. Raghu Babu Reddy Y received his Master of Science in Computer Science and Engineering (CSE). Here’s a summary of his research work on Measuring Software Development Waste in Open-Source Software Projects:

Software product development can often result in generation of Software Development Waste (SDW) at any stage of the software development life cycle. SDW is defined as any resource-consuming activity that does not add value to the client or the organization developing the software. SDW impacts a software project’s overall efficiency and productivity as the project scale and size increase. For example, developers may need to rework implementations that cater to ambiguous feature stories, sometimes artifacts may not go into production resulting in unused artifacts, etc. Post COVID-19 pandemic, software development processes were profoundly impacted. Many organizations are either working in predominantly remote or hybrid work models. Traditional practices, reliant on in-person interactions and co-located teams, were disrupted as organizations adapted to new, virtual environments. This transition led to adopting various communication and collaboration tools, fundamentally altering how software development was executed and perceived. The work setup required teams to navigate productivity, communication, and workflow management challenges, reshaping established development practices. Our research examined the effects of the pandemic induced work-from-home situation (PWS) on the production and handling of SDW. Starting with a multi-year study, we surveyed 615 participants and interviewed 31 from the software industry across eight countries specializing in various domains. We observed a rise in SDWs and identified a new type of SDW, along with other wastes reclassified into existing waste types. Additionally, we found that teams need more direct measures of SDW and rely instead on proxy measures such as productivity and delivery times. The lack of definitive measures to monitor and manage SDW is a concern. The rising adoption of open-source software (OSS) has prompted an examination of the causes of software development waste (SDW) within OSS and the appropriate metrics for its measurement. The pandemic reshaped practices, fostering more collaborative and flexible approaches accelerating OSS adoption. This shift provides a foundation to investigate the influence of these developments on software development waste. To address this gap, we propose four measures, namely Stale Forks (SF), Project Diversification Index (PDI), PR Rejection Rate (PRR), Backlog Inversion Index (BII), and the Feature Fulfillment Rate (FFR) visualization to potentially identify unused artifacts, building the wrong feature/product, mismanagement of backlog types of SDW. We applied these measures to ten open-source projects. We observe that OpenCV has 0.85%, a small percentage of active forks, and 95.79%, a high percentage of backup forks, indicating many unused artifacts. Meanwhile, the low stale fork value at 1.43% indicates fewer unused artifacts. Rustlings has a high number of potentially stale (26.11%) and stale forks (10.02%), indicating a high percentage of unused artifacts. The PDI ranges from 0.0143 for Rust in one repository to 2.18 for bootstrap, indicating the rate at which the project’s plan differs from user expectations and how much it aligns with those expectations, respectively. The repository Rustlings has the lowest unused artifact count with a PRR rate of 0.22, while angular and react-native are on the opposite side of the spectrum with values of 6.59 and 19.35, respectively. The project bootstrap has a ‘0’ on its BII, with kubernetes showing the highest value at 3.37. Finally, the FFR visualization shows variations in ‘backlog management’ practices among the different projects. 

February 2025