Productivity trends in incremental and iterative software development

Tan, Thomas; Li, Qi; Boehm, Barry; Yang, Ye; He, Mei; Moazeni, Ramin

doi:10.1109/esem.2009.5316044

Cited by 38 publications

(19 citation statements)

References 18 publications

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“…Inconsistencies have been noted in prior studies of software measurement data [4], [32], [39]. Tan et al [39] discovered inconsistencies when they studied a data set said to represent productivity trends in incremental and iterative software development.…”

Section: )mentioning

confidence: 99%

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A Taxonomy of Data Quality Challenges in Empirical Software Engineering

Bosu

MacDonell

2013

2013 22nd Australian Software Engineering Conference

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Section: )mentioning

confidence: 99%

“…Tan et al [39] discovered inconsistencies when they studied a data set said to represent productivity trends in incremental and iterative software development. These inconsistencies included size and effort data that did not match from report to report.…”

Section: )mentioning

confidence: 99%

A Taxonomy of Data Quality Challenges in Empirical Software Engineering

Bosu

MacDonell

2013

2013 22nd Australian Software Engineering Conference

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“…Iterative software development methods are used by many organizations to reduce development risks and to deliver software projects on time [22,23]. Design and prototype testing are integral parts of the iterative implementation strategy.…”

Section: Iterative Implementation and Design And Prototype Testingmentioning

confidence: 99%

Developing an Interactive Intervention Planner - A Systems Engineering Perspective

Fabry

Vanherpe

Feral

et al. 2013

International Journal of Advanced Robotic Systems

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Intervention planning is crucial for maintenance operations in particle accelerator environments with ionizing radiation, during which the radiation dose received by maintenance workers should be reduced to a minimum.In this context, we discuss the development of a new software tool and the entailed methodology, including the visualization aspects. The software tool integrates interactive exploration of a scene depicting an accelerator facility augmented with residual radiation level simulations, with the visualization of intervention data such as the followed trajectory and maintenance tasks.Its conception allows for future inclusion of measurements performed by mobile robotic devices. In this work, we explore the systems engineering life cycle of the development process of an interactive intervention planner, which includes the needs analysis, specification explicitation, conceptual mathematical modelling, iterative implementation, design and prototype testing and usability testing.

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“…[ Maxwell et al, 1996, Tan et al, 2009 [ Boehm, 2000, Krishnan, 1998, Tan et al, 2009, Vosburgh et al, 1984 [Fenton and Pfleeger, 1997] Reuse. Several studies have found that reuse impacts positively on the productivity.…”

Section: Product Factorsmentioning

confidence: 99%

“…According to Tan et al [2009], software architecture drives productivity variation, since a well-planned and organized architecture tends to increase productivity. On the other hand, a deficient architecture will result in productivity decrease because of the needed re-architecting to bring the project back on track.…”

Section: Product Factorsmentioning

confidence: 99%

Productivity of agile teams: an empirical evaluation of factors and monitoring processes

Melo¹

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Lower cost and shorter time-to-market expectations are the major drivers of software productivity improvements. To manage productivity effectively, it is important to identify the most relevant difficulties and develop strategies to cope with them. Agile methods, including Extreme Programming and Scrum, have evolved as approaches to simplify software development process, potentially leading to better productivity. They aim to shorten development time and handle the inevitable changes resulting from market dynamics.Although the industry has extensively adopted agile methods, little research has empirically examined the software development agility construct regarding its dimensions, determinants, and effects on software development performance. Understanding this construct could help determine where to concentrate management efforts (and related financial resources) from a practical standpoint and where to focus research efforts from an academic perspective.Considerable research has been directed at identifying factors that have a significant impact on software development productivity. In general, the studied productivity factors were related to product, personnel, project, process, or organizational issues. Continuously evaluating productivity factors is important, as factors may change under new software engineering practices. However, little research has investigated the major factors influencing agile team productivity.The goal of this thesis was to explore productivity definitions, factors, and monitoring in agile teams and to improve the practice based on the collected evidence and gained knowledge. This thesis presents five novel contributions: C1 -Empirical verification of the importance of productivity for companies adopting agile methods and its perceived benefits; C2 -Rationale for the definition of productivity in the context of agile methods; C3 -Empirical verification of agile team productivity factors; C4 -A conceptual framework for agile team productivity factors and their impact; C5 -A team productivity monitoring process considering adaptability and an evaluation of the usefulness of agile team productivity metrics.

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Productivity trends in incremental and iterative software development

Abstract: In an investigating study to trace the productivity changes of a commercial software project, which uses incremental and iterative development model, we 've

Cited by 38 publications

References 18 publications

A Taxonomy of Data Quality Challenges in Empirical Software Engineering

A Taxonomy of Data Quality Challenges in Empirical Software Engineering

Developing an Interactive Intervention Planner - A Systems Engineering Perspective

Productivity of agile teams: an empirical evaluation of factors and monitoring processes

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