Business process quality measurement using advances in static code analysis

Business process models play an important role in the life of a company. Resemblances between software programs and business processes inspired several researchers to adapt software metrics from the field of static code analysis to help designers to build more effective and understandable processes. This paper aims to add recent advances in software quality measurement such as benchmarking and ISO/IEC 25010 standard based quality models to business process quality measurement. These techniques were proved to be very useful in software engineering both for managers and developers; moreover, they can be easily adopted to business process workflows. We focused on a specific type of flowchart called event-driven process chain (EPC), because in an EPC the activities are very often managed by software systems and our assumption is that the quality of these software systems affects the quality of the EPC itself. The presented business process quality model also uses the quality and test coverage metrics of these software systems besides business process metrics

Generation of Formal Model Metrics for MOF based Domain Specific Languages

The assessment of quality in a software development process is vital for the quality of the final system. A number of approaches exist, which can be used to determine such quality properties. In a model-driven development process models are the primary artifacts. Novel technologies are needed in order to assess the quality of those artifacts. Often, the Object Constraint Language is used to formulate model metrics and to compute them automatically afterwards. This paper describes an approach for the generation of model metrics expressed as OCL statements based on a set of generic rules. These rules can be applied on any domain specific modeling languages for creating a basic set of metrics which can be tailored for the specific needs of a development process. The paper also briefly describes a prototype of a tool for the generation, computation, and management of these model metrics by using the Software Metrics Meta-model - SMM

Generation of Formal Model Metrics for MOF based Domain Specific Languages

The assessment of quality in a software development process is vital for the quality of the final system. A number of approaches exist, which can be used to determine such quality properties. In a model-driven development process models are the primary artifacts. Novel technologies are needed in order to assess the quality of those artifacts. Often, the Object Constraint Language is used to formulate model metrics and to compute them automatically afterwards. This paper describes an approach for the generation of model metrics expressed as OCL statements based on a set of generic rules. These rules can be applied on any domain specific modeling languages for creating a basic set of metrics which can be tailored for the specific needs of a development process. The paper also briefly describes a prototype of a tool for the generation, computation, and management of these model metrics by using the Software Metrics Meta-model - SMM

Towards Ontology-based SQA Recommender for Agile Software Development

Agility is heavily dependent on tacit knowledge, skilled and motivated employees, and frequent communications. Although, the Agile Manifesto claims fast and light software development process while maintaining high quality, it is however not very clear how current agile practices and methods attain quality under time pressure and unstable requirements. In this paper, we present an ontological approach for process-driven Quality Assurance support for agile software development. Challenges related to the role of Quality Assurance in agile projects are addressed by developing a process-driven recommender that provides tailored resources to user’s queries. The proposed ontological model embeds both conceptual and operational SQA knowledge about software processes and their requirements, including quality attributes, SQA measurements, SQA metrics and related SQA techniques and procedures

Enhancing Software Team Planning and Delivery Performance using Agile Driven Quality Measures: Approach, Results, and Recommendations

Implementing a performance-management program in an agile software-development organization is important to retain sight of software team performance as a whole as well as linking performance-management metrics to business value. The evaluation criteria for software engineers’ performance have been traditionally driven by metrics that don’t fit into agile-development principles. This research implements a measurement metric that aligns with agile-development core values and principles to evaluate engineers in a software engineering firm using the Scrum development method. The research focused on measuring and evaluating the productivity, development efficiency, social skills, team collaboration and breadth of knowledge. Observing the Productivity Index (PI), Actual Productivity for software Engineers (APSE), and Productivity Variance (PV) for individual software engineers and the development team at the end of each sprint helped the development team have a better understanding of its productivity levels in a matter that facilitated planning future sprints. In addition, this productivity measure helped early identification of productivity challenges encountered by several software engineers and productivity identification of productivity challenges encountered by several software engineers. Keywords: Agile development, software teams, process measurement, scrum, productivity, efficiency, software metrics, software project measuremen

Complexity metrics for measuring the understandability and maintainability of Business Process Models using Goal-Question-Metric (GQM)

Business Process Models (BPMs), often modeling language such as UML activity between the created using stakeholders in the can provide us a diagrams, Event- Driven Process Chains Markup Language (EPML) and Yet Another Workflow Language (YAWL), serve as a base for communication that adequate software development process. In order to fulfill this purpose, they should be easy to understand and easy to maintain. For this reason, it is useful to have measures information about understandability and maintainability of the BPM. Although there are hundreds of software complexity measures that have been described and published by many researchers over the last few decades, measuring the complexity of business process models is a rather new area of research with only a small number of contributions. In this paper, we provide a comprehensive report on how existing complexity metrics of software were adapted in order to analyze the current business process models complexity. We also proposed a Goal- Question-Metric (GQM) framework for measuring the understandability and maintainability of BPMs

A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space

We are developing a system for human-robot communication that enables people to communicate with robots in a natural way and is focused on solving problems in a shared space. Our strategy for developing this system is fundamentally data-driven: we use data from multiple input sources and train key components with various machine learning techniques. We developed a web application that is collecting data on how two humans communicate to accomplish a task, as well as a mobile laboratory that is instrumented to collect data on how two humans communicate to accomplish a task in a physically shared space. The data from these systems will be used to train and fine-tune the second stage of our system, in which the robot will be simulated through software. A physical robot will be used in the final stage of our project. We describe these instruments, a test-suite and performance metrics designed to evaluate and automate the data gathering process as well as evaluate an initial data set.Comment: 2017 AAAI Fall Symposium on Natural Communication for Human-Robot Collaboratio

An Experimental Study of A Design-driven, Tool-based Development Approach

International audienceDesign-driven software development approaches have long been praised for their many benefits on the development process and the resulting software system. This paper discusses a step towards assessing these benefits by proposing an experimental study that involves a design-driven, tool-based development approach. This study raises various questions including whether a design-driven approach improves software quality and whether the tool-based approach improves productivity. In examining these questions, we explore specific issues such as the approaches that should be involved in the comparison, the metrics that should be used, and the experimental framework that is required

Undulate : A framework for data-driven software engineering enabling soft computing

Context. Especially web-facing software systems enable the collection of usage data at a massive scale. At the same time, the scale and scope of software processes have grown substantively. Automated tools are needed to increase the speed and quality of controlling software processes. The usage data has great potential as a driver for software processes. However, research still lacks constructs for collecting, refining and utilising usage data in controlling software processes.Objective. The objective of this paper is to introduce a framework for data-driven software engineering. The UNDULATE framework covers generating, collecting and utilising usage data from software processes and business processes supported by the software produced. In addition, we define the concepts and process of extreme continuous experimentation as an exemplar of a software engineering process.Method. We derive requirements for the framework from the research literature, with a focus on papers inspired by practical problems. In addition, we apply a multilevel modelling language to describe the concepts related to extreme continuous experimentation.Results. We introduce the UNDULATE framework and give requirements and provide an overview of the processes of collecting usage data, augmenting it with additional dimensional data, aggregating the data along the dimensions and computing different metrics based on the data and other metrics.Conclusions. The paper represents significant steps inspired by previous research and practical insight towards standardised processes for data-driven software engineering, enabling the application of soft computing and other methods based on artificial intelligence.Peer reviewe

Metrics and Visualizations for Managing Value Creation in Continuous Software Engineering

Digitalized society is built on top of software. The supplier of a software system delivers valuable new features to the users of the system in small increments in a continuous manner. To achieve continuous delivery of new features, new versions of software are delivered in rapid cycles. The goal is to get timely feedback from the stakeholders of the system in order to deliver business value.The development team needs timely information of the process to be able to improve it. A demonstrative overview of the process helps to get better understanding about the development process. Moreover, the development team is often willing to get retrospective information of the process in order to improve it and to maintain the flow of continuous value creation.The team uses various tools in the daily software engineering activities. The tools generate vast amount of data concerning the development process. For instance, issue management and version control systems hold detailed information on the actual development process. Mining software repositories provides a data-driven view to the development process.In this thesis, novel metrics and visualizations were built on top of the data. The developed artifacts help to understand and manage the value creation process. With this novel, demonstrative information, lean continuous improvement of the development process is made possible. With the novel metrics and visualizations, the development organization can get such new information on the process which is not easily available otherwise.The new information the metrics and visualizations provide help to different stakeholders of the project to get insight of the development process. The automatically generated data reflects the actual events in the development. The novel metrics and visualizations provide a practical tool for management purposes and continuous software process improvement