Monitoring SOA Applications with SOOM Tools: A Competitive Analysis

Background: Monitoring systems decouple monitoring functionality from application and infrastructure layers and provide a set of tools that can invoke operations on the application to be monitored. Objectives: Our monitoring system is a powerful yet agile solution that is able to online observe and manipulate SOA (Service-oriented Architecture) applications. The basic monitoring functionality is implemented via lightweight components inserted into SOA frameworks thereby keeping the monitoring impact minimal. Methods/Approach: Our solution is software that hides the complexity of SOA applications being monitored via an architecture where its designated components deal with specific SOA aspects such as distribution and communication. Results: We implement an application-level and end-to-end monitoring with the end user experience in focus. Our tools are connected to a single monitoring system which provides consistent operations, resolves concurrent requests, and abstracts away the underlying mechanisms that cater for the SOA paradigm. Conclusions: Due to its flexible architecture and design our monitoring tools are capable of monitoring SOA application in Cloud environments without significant modifications. In comparisons with related systems we proved that our agile approaches are the areas where our monitoring system excels

Middle Tier Acquisition FY 2022 Budget Data Overview

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThis research uses publicly-released data from 2018 to 2021, consisting of budget submissions, program-related reporting, and contemporaneous press releases, to describe how services took the same novel authorities and developed Middle Tier Acquisitions (MTAs) with differing structures, risks, and results to date. We acknowledge the cultural and personality differences, and concentrate on the different approaches to scoping project technical uncertainty and systemic complexity to fit within MTA constraints.Approved for public release; distribution is unlimited

Agile challenges in practice: a thematic analysis

As agile is maturing and becoming more widely adopted, it is important that researchers are aware of the real-world challenges faced by practitioners and organisations. We undertook a thematic analysis of 193 agile challenges collected at a series of agile conferences and events during 2013 and 2014. Participants were mainly practitioners and business representatives along with some academics. The challenges were thematically analysed by separate authors, synthesised, and a list of seven themes and twenty-seven sub-themes was agreed. Themes were Organisation, Sustainability, Culture, Teams, Scale, Value and Misconceptions and shortcomings. We compare our findings against previous attempts to identify and categorise agile challenges. While most themes have persisted we found a shift of focus towards issues related to sustainability, business engagement and transformation, as well as misconceptions and shortcomings. We identify areas for further research and a need for more innovative methods of conveying academic research to industry and industrial problems to academi

The investigation on the best pracices of extreme programming (XP) quality implementation at UUMIT

Software engineering (SE) plays an important role for improving society‘s wellbeing through the use of high quality software. There is noted that most of the software projects are failed, due to missing or poor software development practices in software organizations. Due to this reason, having a good and sound software development methodology is crucial for software organization to satisfy stakeholder‘s requirements. One of the prevalent software development methodologies in SE is Extreme programming (XP) methodology. This methodology is an emerging SE approach, which is able to increase software quality and hence reducing software development time and cost. However, the level of application of this methodology among software developers in UUM IT centre is still unclear. Therefore, this study aims to investigate the application of XP practices in this centre. UUM IT was chosen as a case study because the role of this organization has changed to meet high demand among campus communities. Thus, research that focuses on the 12 XP practices of UUM IT is highly needed. This study was conducted using a semi–structured interview with five (5) experts from the UUM IT, to identify the successful implementation of the XP practices. The findings have shown that, most of the practices are used by UUM IT developers but need to improve. In contrast, some of the practices such as pair programming and test first programming are not used by the UUM IT developers. This is due to the nature and type of software projects involved, also because of the personality, experiences and the education level differences among developers. This study provides qualitative evident that can assist software project managers to guide them in improving software development practices for producing high quality software

SANTO: Social Aerial NavigaTion in Outdoors

In recent years, the advances in remote connectivity, miniaturization of electronic components and computing power has led to the integration of these technologies in daily devices like cars or aerial vehicles. From these, a consumer-grade option that has gained popularity are the drones or unmanned aerial vehicles, namely quadrotors. Although until recently they have not been used for commercial applications, their inherent potential for a number of tasks where small and intelligent devices are needed is huge. However, although the integrated hardware has advanced exponentially, the refinement of software used for these applications has not beet yet exploited enough. Recently, this shift is visible in the improvement of common tasks in the field of robotics, such as object tracking or autonomous navigation. Moreover, these challenges can become bigger when taking into account the dynamic nature of the real world, where the insight about the current environment is constantly changing. These settings are considered in the improvement of robot-human interaction, where the potential use of these devices is clear, and algorithms are being developed to improve this situation. By the use of the latest advances in artificial intelligence, the human brain behavior is simulated by the so-called neural networks, in such a way that computing system performs as similar as possible as the human behavior. To this end, the system does learn by error which, in an akin way to the human learning, requires a set of previous experiences quite considerable, in order for the algorithm to retain the manners. Applying these technologies to robot-human interaction do narrow the gap. Even so, from a bird's eye, a noticeable time slot used for the application of these technologies is required for the curation of a high-quality dataset, in order to ensure that the learning process is optimal and no wrong actions are retained. Therefore, it is essential to have a development platform in place to ensure these principles are enforced throughout the whole process of creation and optimization of the algorithm. In this work, multiple already-existing handicaps found in pipelines of this computational gauge are exposed, approaching each of them in a independent and simple manner, in such a way that the solutions proposed can be leveraged by the maximum number of workflows. On one side, this project concentrates on reducing the number of bugs introduced by flawed data, as to help the researchers to focus on developing more sophisticated models. On the other side, the shortage of integrated development systems for this kind of pipelines is envisaged, and with special care those using simulated or controlled environments, with the goal of easing the continuous iteration of these pipelines.Thanks to the increasing popularity of drones, the research and development of autonomous capibilities has become easier. However, due to the challenge of integrating multiple technologies, the available software stack to engage this task is restricted. In this thesis, we accent the divergencies among unmanned-aerial-vehicle simulators and propose a platform to allow faster and in-depth prototyping of machine learning algorithms for this drones

From Ad-Hoc Data Analytics to DataOps

The collection of high-quality data provides a key competitive advantage to companies in their decision-making process. It helps to understand customer behavior and enables the usage and deployment of new technologies based on machine learning. However, the process from collecting the data, to clean and process it to be used by data scientists and applications is often manual, non-optimized and error-prone. This increases the time that the data takes to deliver value for the business. To reduce this time companies are looking into automation and validation of the data processes. Data processes are the operational side of data analytic workflow.DataOps, a recently coined term by data scientists, data analysts and data engineers refer to a general process aimed to shorten the end-to-end data analytic life-cycle time by introducing automation in the data collection, validation, and verification process. Despite its increasing popularity among practitioners, research on this topic has been limited and does not provide a clear definition for the term or how a data analytic process evolves from ad-hoc data collection to fully automated data analytics as envisioned by DataOps.This research provides three main contributions. First, utilizing multi-vocal literature we provide a definition and a scope for the general process referred to as DataOps. Second, based on a case study with a large mobile telecommunication organization, we analyze how multiple data analytic teams evolve their infrastructure and processes towards DataOps. Also, we provide a stairway showing the different stages of the evolution process. With this evolution model, companies can identify the stage which they belong to and also, can try to move to the next stage by overcoming the challenges they encounter in the current stage

Understanding Interaction and Communication Challenges Present in Software Engineering

Researchers have largely identified that interactions and communications pose major challenges in software development, especially when extracting requirements. However, they have not appreciated the sources and the depth of them, thus approaching them with mechanisms that have not (fully) achieved the desired objectives. In this position, we claim that such challenges can be explained using three major theories coming from social sciences: the theory of verbal and nonverbal communication, systemic theory, and democratic theory. We also argue that some of the successful practices of agile methods can be explained in terms of these theories. Finally, we stipulate that a full appreciation of these theories can result in a significant leap forward in the discipline, identifying new mechanisms that can help to overcome the mentioned challenges, understanding fully what we are doing and wh

Impediments in Transitioning to Agile Time-boxing Testing Efforts

In agile framework, the system is developed in sprints. Some value-based products for the customers are created with completion of work in a sprint. There are firm dates of commencement and end in sprints, and duration of each sprint is normally equal. During a sprint, any change in scope or resources cannot be made. But sometimes it becomes difficult to follow this rule on account of the business needs. This time-boxing approach is seen responsible to cause more hindrance than propel organizations towards time-efficient development of products. This type of project demands a much more flexible time-line as compared to standard agile project management practices of ‘Sprint’ used for creating cost-effective products within time. Similar problems are faced by the organizations transitioning from traditional method to agile practices. From different sources of research it is found the transition could not be smooth in all cases and sometimes was unable to achieve the expected business growth due to various factors. A number of options and approaches are discussed for helping an organization transitioning from traditional to agile methodology but any unique and full-proof approach cannot be arrived at. Ultimately it becomes a question: can we overcome difficulty in time-boxing approach with discrepancies in testing efforts and get a systematic and tabulated solution of the problem in transitioning to agile? Through this research having limitations the answer in all respect cannot be reached. The question is left with ample scope for further research by future researchers as well