Increasing amount of data the organizations worldwide have at their disposal lead to the need to structure, organize and present the information obtained from it. That is because, in today's rapid-changing business environment, managers and executives need to be able to gain crucial insights about the ongoing project in as little time as possible. Recently, energy efficiency has become a greater field of research, and companies started concentrating on monitoring energy-related metrics. In addition, many of them have built their own internal tools (dashboards) to do just this. However, one of the major drawbacks of building specialized tools is the lack of adaptability. That is, they are often tailored to only one person (e.g. CEO), or a small group of them (e.g. board of directors, managers). Furthermore, the combination of metrics that is displayed to them does not change over time. This is a problem because most likely there exists a better metric combination that would allow users to get the crucial insights faster. To fill this gap, our ongoing research focuses on making the dashboards adaptable to multiple roles within the organization while optimizing for a certain goal. In some scenarios the dashboard's goal may be to detect defects, in others it may be to generate the most profit. As our primary research interest is to amplify energy efficiency, we have chosen that to be our dashboard's goal. Our previous work suggests that in order to handle compound metrics at scale it is needed to represent the dashboard as a complex system. This paper presents the design and the architecture of our proposed solution synergizing the notions from complexity theory, software architecture and user experience (UX) design.
Most of the currently used software development metrics are concentrated on the latter stages like development and testing. However, early revealing of errors during the SDLC(Software Development Life Cycle) tremendously affects the efficiency of the team work by spending more time on prevention and less on correction in later stages. Furthermore, reworking in later stages increase the cost of quality, lead to extra waste of time of the development team. The objective of this review is to examine the classification of the existing SDLC(Software Development Life Cycle) early phases and define the set of software process quality metrics. Based on the SRL research protocol, we selected the most relevant studies from overall 200 publications by the use of search keywords and inclusion/exclusion criteria for quality assessment of primary studies. This systematic literature review yields the correlation of cost, time and software product quality with the SDLC stages.
With the growing need for software-driven devices in modern life, the pervasive necessity of energy efficiency is also rising dramatically. Considering the importance of energy-efficient software in the IT-sphere, many companies started to search and uncover ways for minimizing energy loss. We study the software development process in terms of energy consumption. This depends on various factors that have to be monitored continuously. In this paper, we propose the Innometrics framework for monitoring the software development process and analyzing the profiles of energy consumption by user devices. The motivating idea of the project is to provide crucial insights and to clarify which development activities are the main drivers behind the energy consumption.
The current situation when using tight time frames and frequently changing requirements when creating software dictates the need to create a system for monitoring energy consumption at any stage of production of a software product. At the first stage, we need to evaluate the state-of-the-art on this topic. To this goal, we conducted a systematic literature review. During the review more than 500 studies were observed and 124 of them were selected for detailed analysis. Among these papers, 169 metrics were derived and assessed from the point of their applicability within invasive software development process analysis. The study demonstrates the relevance of the questions posed and shows the immaturity of the area. There is no evolutionary study and the possibility of assessment at any stage of the development of a software product. The data show the importance and relevance of technical work and the importance of its further development.
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