The challenge of release planning

Jantunen, Sami; Lehtola, Laura; Gause, Donald C.; Dumdum, Uldarico Rex; Barnes, Raymond J.

doi:10.1109/iwspm.2011.6046202

Cited by 15 publications

(7 citation statements)

References 38 publications

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“…The focus of the majority of publications on release planning models are various kinds of mathematical models and simulations [22], which are ineffectual in complex industries [23]. Practitioners reported that these approaches are either too simple to generate a benefit or so difficult that they cannot reconstruct the whole process created [24] [25].…”

Section: Background and Related Workmentioning

confidence: 99%

Real-Life Challenges in Automotive Release Planning

Marner¹,

Theobald

Wagner

2019

Proceedings of the 2019 Federated Conference on Computer Science and Information Systems

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The use of agile software development is increasing, even in regulated domains like the automotive domain. At the same time, traditional sequential processes are still in use. Collaboration between agile and hybrid projects within these complex traditional product development processes is difficult. Especially the creation and synchronization of a qualification phase plan is challenging. Objective: The aim of this study is to provide insights into the state of the practice to understand challenges related to the combined use of agile and traditional paradigms in release planning in the automotive domain. Method: Based on semi-structured interviews, an online survey with 39 respondents was conducted at Dr. Ing. h. c. F. Porsche AG. Results: We present the challenges identified in release planning, such as lack of transparency regarding the status quo of related projects. Furthermore, we motivate how agile development methods could improve collaboration between projects in release planning. Conclusions: There are many challenges in the context of co-existing agile and traditional projects. We discuss how agile practices like daily standup or continuous integration could address the identified challenges.

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Section: Background and Related Workmentioning

confidence: 99%

Real-Life Challenges in Automotive Release Planning

Marner¹,

Theobald

Wagner

2019

Proceedings of the 2019 Federated Conference on Computer Science and Information Systems

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“…Size and complexity metrics are common among other metrics to predict software maintainability (Riaz et al 2009). Growing software size and complexity have made it increasingly difficult to select features to be implemented in the next product release and have challenged existing assumptions and approaches for release planning (Jantunen et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Effects of measurements on correlations of software code metrics

2019

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Context Software metrics play a significant role in many areas in the life-cycle of software including forecasting defects and foretelling stories regarding maintenance, cost, etc. through predictive analysis. Many studies have found code metrics correlated to each other at such a high level that such correlated code metrics are considered redundant, which implies it is enough to keep track of a single metric from a list of highly correlated metrics. Objective Software is developed incrementally over a period. Traditionally, code metrics are measured cumulatively as cumulative sum or running sum. When a code metric is measured based on the values from individual revisions or commits without consolidating values from past revisions, indicating the natural development of software, this study identifies such a type of measure as organic. Density and average are two other ways of measuring metrics. This empirical study focuses on whether measurement types influence correlations of code metrics. Method To investigate the objective, this empirical study has collected 24 code metrics classified into four categories, according to the measurement types of the metrics, from 11,874 software revisions (i.e., commits) of 21 open source projects from eight well-known organizations. Kendall's τ-B is used for computing correlations. To determine whether there is a significant difference between cumulative and organic metrics, Mann-Whitney U test, Wilcoxon signed rank test, and paired-samples sign test are performed. Results The cumulative metrics are found to be highly correlated to each other with an average coefficient of 0.79. For corresponding organic metrics, it is 0.49. When individual correlation coefficients between these two measure types are compared, correlations between organic metrics are found to be significantly lower (with p <0.01) than cumulative metrics. Our results indicate that the cumulative nature of metrics makes them highly correlated, implying cumulative measurement is a major source of collinearity between cumulative metrics. Another interesting observation is that correlations between metrics from different categories are weak.

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“…The traditional, plan-driven product and project management models do not suit the organizations of agile development, in which the scoping decisions are frequently made, and implementation is carried together with the requirements engineering process [13]. The efficient progress of the organizational growth towards achieving their objective cannot be achieved if the management process does not abide by the agile development [14].…”

Section: Introductionmentioning

confidence: 99%

Distributed cat modeling based agile framework for software development

Prakash

Viswanathan

2019

Sādhanā

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Software development is a challenging process that requires in-depth understanding and an effective model such that the developed software inherits good quality and reliability, and attains customer satisfaction towards achieving the goals successfully. The effectiveness of the software is enabled by modifying the operating modules of the software through a model, like agility. In this paper, the catastrophic and distributed computing models are integrated into the software development process. The proposed model is termed as a distributed cat model that is developed with the aim to handle the risk factors engaged in various developing stages of the agile model. The risk factors that affect the communication, planning, release, design, coding and testing modules of the agile modules are deeply learned and executed such that the risk factors are tackled by various modules present in the proposed distributed cat model. The effectiveness of the proposed model is analysed based on the performance metrics such as Index of Integration (IoI) and Usability Goals Achievement Metric (UGAM), for which five products, including the hotel management system, Customer Relationship Management system (CRM), rainfall prediction system, temperature monitoring system and meta-search system, are employed. The analysis is performed using the parameters like mean difference, variance, standard deviation and correlation coefficient. The result proves that the proposed model offers a great positive deviation contributing to high degree of performance in software development.

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The challenge of release planning

Cited by 15 publications

References 38 publications

Real-Life Challenges in Automotive Release Planning

Real-Life Challenges in Automotive Release Planning

Effects of measurements on correlations of software code metrics

Distributed cat modeling based agile framework for software development

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