Showing papers in "Journal of Systems and Software in 2018"

TL;DR: This work systematically analyzes the industrial grey literature on microservices, to identify the technical/operational pains and gains of the microservice-based architectural style.

TL;DR: The definitions of smells, their causes as well as effects, and their detection mechanisms presented in the current literature are explored, and existing smell detection methods are classified into five groups — metrics, rules/heuristics, history, machine learning, and optimization-based detection.

TL;DR: A throughout study on the meaning, characteristics, and dynamic growth of GitHub stars is provided and a list of recommendations to open source project managers and GitHub users and Software Engineering researchers is provided.

TL;DR: This article proposes effective and practical machine learning deployment and maintenance approaches by utilization of research findings and industry best practices and obtained models for effort and duration estimation are intended to provide a decision support tool for organisations that develop or implement software systems.

TL;DR: It is found that the purpose of applying gamification in the SE field is mostly directly related to improving student engagement and, to a lesser extent, to improvingStudent knowledge, although other targets are the application of SE best practices and socialization.

TL;DR: This article presents the largest catalogue of test smells, along with the summary of guidelines/techniques and the tools to deal with those smells, to benefit the readers by serving as an “index” to the vast body of knowledge in this important area.

TL;DR: The goal of the present survey study is to identify the main challenges in the field of monitoring edge computing applications that are as yet not fully solved, to present a new taxonomy of monitoring requirements for adaptive applications orchestrated upon edge computing frameworks, and to discuss and compare the use of widely-used cloud monitoring technologies.

TL;DR: Part of this work is supported by the Brazilian funding agency FAPESP (Grant: 2017/06195- 9), and the Canadian NSERC through RGPIN2016-06640.

TL;DR: Most research has been conducted within the SWEBOK knowledge areas software engineering process, management, construction, design, and requirements, with the shift of focus towards process and management areas.

TL;DR: In this paper, the authors study what happens when developers are happy and unhappy while developing software and find consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts.

TL;DR: This method provides a test engineer with key insights into the software’s decision-making engine and how those decisions affect transitions between performance modes through adaptive, simulation-based testing of the autonomous system where each sample represents a simulated scenario.

TL;DR: The subject area of requirements engineering in agile context is mapped to identify the main topics that have been researched and to identify gaps to develop future researches and the obstacles that practitioners face when using agile requirements engineering are identified.

TL;DR: A state-of-the-art of Kanban research is provided, the reported benefits and challenges are identified in both the primary papers and experience reports, and opportunities for future KanbanResearch are identified.

TL;DR: To what extent app developers take user reviews into account, and whether addressing them contributes to apps’ success in terms of ratings is empirically investigated.

TL;DR: The empirical evaluations confirm that the domain specificity exploited in the SentiStrength-SE enables it to substantially outperform the existing domain-independent tools/toolkits in detecting sentiments in software engineering text.

TL;DR: The genetic algorithm-based energy-efficient clustering and routing approach GECR is presented, which achieved the best load balancing with the lowest variances in the loads on the cluster heads under different scenarios and was the most energy- efficient.

TL;DR: A systematic literature review of the existing techniques for threat analysis finds that the analysis procedure is not precisely defined, there is a lack of quality assurance of analysis outcomes and tool support and validation are limited.

TL;DR: The results show that, by using this model, different stakeholders could increase the system's success rate, and lower the rate of negative consequences, by raising awareness about architectural TD.

TL;DR: A hybrid service discovery approach is developed by integrating goal-based matching with two practical approaches: keyword-based and topic model-based, which shows the effectiveness of this approach on a real-world dataset.

TL;DR: A literature review addressing design and evaluation of tools for smart home control oriented to end users and an experimental study in which three tools were compared in order to identify the interaction mechanisms that end users appreciate most are presented.

TL;DR: It is argued that an effective software visualization should not only boost time and correctness but also recollection, usability, engagement, and other emotions, and it is called on researchers proposing new software visualizations to provide evidence of their effectiveness.

TL;DR: This study describes the constraints the students faced while applying agile practices in a university course taught at the University of Auckland and the modifications the students introduced to adapt agile practices to suit the university context, such as daily stand-ups with reduced frequency.

TL;DR: It is claimed that JMove is specially useful to provide recommendations for large methods by investigating the overlapping of the recommendations provided by JMove and three other recommenders (JDeodorant, inCode, and Methodbook) and validating J move and J deodorant recommendations with experts in two industrial-strength systems.

TL;DR: It is found that categorical models that rely on requirement and design phase metrics, and few continuous models including metrics from requirements phase are very successful, and most studies reported qualitative benefits of using ESDP models.

TL;DR: This paper presents an ARS approach based on clustering techniques using black-box information that can construct ARSs that attempt to make their neighboring test cases as diverse as possible and shows both enhanced probability of earlier fault detection, and higher effectiveness than random prioritization and method coverage TCP technique.

TL;DR: A novel anomaly detection algorithm is proposed that considers traces as sequence data and uses a probabilistic suffix tree based method to organize and differentiate significant statistical properties possessed by the sequences.

TL;DR: A novel approach to automatically identify third-party library usage patterns, i.e., collections of libraries that are commonly used together by developers, using a hierarchical clustering technique to group together software libraries based on external client usage.

TL;DR: In this paper, the authors investigated how Lean internal startup facilitates software product innovation in large companies and identified the enablers and inhibitors for Lean internal startups. But, they did not address the potential of applying the Lean startup approach in non-startup context.

TL;DR: A systematic literature review based on Evaluation Theory, a theory that generalizes six evaluation components, target, criteria, yardstick, data gathering techniques, synthesis techniques, and evaluation process, provides the relative strengths and weaknesses of the different CSEMs and offers a basis for researchers and decision makers to develop improvedCSEMs.

TL;DR: This work proposes large universe attribute based access control scheme with efficient decryption, which significantly reduces the time for the user to decrypt the ciphertext without the cloud computing server knowing the underlying plaintext and verifies the correctness of transformation done by the cloud Computing server.