Definition, implementation and validation of energy code smells: an exploratory study on an embedded system

Optimizing software in terms of energy efficiency is one of the challenges that both research and industry will have to face in the next few years.We consider energy efficiency as a software product quality characteristic, to be improved through the refactoring of appropriate code pattern: the aim of this work is identifying those code patterns, hereby defined as Energy Code Smells, that might increase the impact of software over power consumption. For our purposes, we perform an experiment consisting in the execution of several code patterns on an embedded system. These code patterns are executed in two versions: the first one contains a code issue that could negatively impact power consumption, the other one is refactored removing the issue. We measure the power consumption of the embedded device during the execution of each code pattern. We also track the execution time to investigate whether Energy Code Smells are also Performance Smells. Our results show that some Energy Code Smells actually have an impact over power consumption in the magnitude order of micro Watts. Moreover, those Smells did not introduce a performance decreas

Subjective Quality Assessment of the Impact of Buffer Size in Fine-Grain Parallel Video Encoding

Fine-Grain parallelism is essential for real-time video encoding performance. This usually implies setting a fixed buffer size for each encoded block. The choice of this parameter is critical for both performance and hardware cost. In this paper we analyze the impact of buffer size on image subjective quality, and its relation with other encoding parameters. We explore the consequences on visual quality, when minimizing buffer size to the point of causing the discard of quantized coefficients for highest frequencies. Finally, we propose some guidelines for the choice of buffer size, that has proven to be heavily dependent, in addition to other parameters, on the type of sequence being encoded. These guidelines are useful for the design of efficient realtime encoders, both hardware and software

Relationship Determinants between AI Technology Adoption Behavior and Performance of Software Enterprises

With the continuous progress of science and technology, the arrival of artificial intelligence subverts the traditional industries. Enterprises urgently need to carry out technological innovation to reduce costs. The introduction of artificial intelligence technology can reduce workload and improve development efficiency for software enterprises. Reduce operating costs. This paper takes the software enterprise as the research object, takes the artificial intelligence as the independent variable and the software development cost as the dependent variable. The hypothesis is proposed through the four intermediate variables of development efficiency, management innovation, product quality, labor force and the degree of introduction of artificial intelligence. A total of 332 valid questionnaires were collected by using electronic questionnaires. The sample data are analyzed by Smartpls 3.0 software, and the data are analyzed by Algorithm, Bootstrapping, cross multiplication, structural equation and other methods. The results show that AI has a significant positive impact on software development cost, a significant positive impact on product quality, a significant positive impact on labor force, a significant positive impact on development efficiency, a significant positive impact on management innovation, and a significant positive impact on software development cost. Labor has a significant positive impact on software development costs. Development efficiency has a significant positive impact on software development cost. Management innovation has a significant positive impact on software development cost. Product quality plays an intermediary role between the introduction of artificial intelligence and the cost of software development. Development efficiency also plays an intermediary role between the introduction of artificial intelligence and the cost of software development. From the research, we know that the introduction of AI can enrich the theories of process reengineering, process optimization and management decision-making, and can also find the factors that affect output performance from the perspective of technological innovation to provide reference for future research

Analysis of the Effect of Academic Service Quality on Student Loyalty Through Student Satisfaction and Organizational Performance

This research aims to analyze the significant influence of quality academic services to student loyalty with student satisfaction and organizational performance as intervening. The sample in this study as many as 40 people, data collection using questionnaires, and then analyzed with SEM PLS using smart software PLS 3.0. Based on the results of the analysis show that the quality of academic services affects student loyalty, the quality of academic services has no impact on organizational performance. The quality of academic services influences student satisfaction. Student satisfaction influences organizational performance. Student satisfaction has no effect on student loyalty. Organizational performance influences student loyalty. Student satisfaction does not mediate the effect of academic service quality. Student satisfaction does not mediate the effect of academic service quality on student loyalty. Organizational performance mediates the effect of student satisfaction on student loyalty. Student satisfaction and organizational performance do not mediate the impact of academic service quality on student loyalty, and organizational performance does not mediate the effect of academic service quality on student loyalt

Understanding the Determinantsof Project Performance: Empirical Evidencesfrom Software Houses of Pakistan

Thisstudy is investigating the effects of project quality, project risk and project governance on project performance. Moreover, this study investigatesthe moderation effect of project leadership on these relationships. Data is collected from 354 respondents of software houses and structural equation modeling (SEM) technique is utilized for data analysis. Results suggest that project quality, project risk and project leadership have positive significant impact on project performance while project governance does not have significant impact on project performance. Significant moderation effect of project leadership on the relationship between project quality and project performance is proved but project leadership has no moderation effect on the relationship between project governance, project risk and project performance. The findings of the study provide significant insights forsoftware houses ofPakistan to formulate strategies in order to develop a governance framework and enhance project performance in IT project management

Impact of Requirement Gathering Techniques on Software Development

Requirement of any software project plays an important role throughout the development life cycle. It affects the system cost, effort, time estimation, system development, software   quality measures and ultimate software performance. There are many requirement gathering techniques deployed for this purpose. Some of these techniques are if good in one picture, at the same time these techniques do not provide better results in another one. In the small size software industries in underdeveloped countries, these techniques varies for the same environment. This research analyses the five common requirements gathering techniques that include interviews, questionnaires, joint application development, request for proposals and prototyping. This paper statistically analyse that the impact of these on software development. Keywords: Requirement gathering, Software performance, Software quality, Requirement analysis