Recommender Systems for DevOps

The software development life cycle (SDLC) for a developer has increased in complexity and scale. With the advent of DevOps processes, the gap between development and operations teams reduced significantly. Developers are now expected to perform different roles from coding to operational support in the new model of software development. This...

A study of bugs found in the Ansible configuration management system

Research that focuses on examining software bugs is critical when developing tools for preventing and for fixing software issues. Previous work in this area has explored other types of systems, such as bugs of compilers and security issues stemming from open source systems hosted on public repositories. This paper explores the bugs within the...

KPI by proxy

Metrics are widely used in the software engineering industry and can serve as Key Performance Indicators (KPIs), which are used by management to make informed decisions and understand the performance of the organisation. Many companies measure themselves against industry-standard metrics, in addition to their own set of metrics. This thesis aims...

Log-based software monitoring: A systematic mapping study

Modern software development and operations rely on monitoring to understand how systems behave in production. The data provided by application logs and runtime environment are essential to detect and diagnose undesired behavior and improve system reliability. However, despite the rich ecosystem around industry- ready log solutions, monitoring...

A Cloud-Based DevOps Toolchain for Efficient Software Development

In the traditional software development life cycle, development and operation are divided into different departments. The conflict between departments and, besides, the lack of automation usually leads to low software development efficiency and slow software delivery. Thus, the concept of DevOps is introduced, which combines different...

Monitoring-aware IDEs

It has become a common practice for software developers to analyse monitoring data as a means to understand issues, trends and performance of large-scale software systems. The combination of this practice with the software development workflow can however be cumbersome at times. One recent effort into evaluating the effects of integrating...

Increasing Operational Awareness using Monitoring-Aware IDEs

It is important to detect problems fast and to have a clear overview of what is happening within a system after deployment to maximize the uptime and functional quality of the system. Therefore it is necessary to increase the awareness that developers have of errors and logs. Increasing the awareness that developers have of errors and logs has a...

Software Analytics in Continuous Delivery: A Case Study on Success Factors

Background: During the period of one year, ING developed an approach for software analytics within an environment of a large number of software engineering teams working in a Continuous Delivery as a Service setting. Goal: Our objective is to examine what factors helped and hindered the implementation of software analytics in such an environment...

Strong Agile Metrics: Mining Log Data to Determine Predictive Power of Software Metrics for Continuous Delivery Teams

ING Bank, a large Netherlands-based internationally operating bank, implemented a fully automated continuous delivery pipeline for its software engineering activities in more than 300 teams, that perform more than 2500 deployments to production each month on more than 750 different applications. Our objective is to examine how strong metrics for...

Continuous Delivery Practices in a Large Financial Organization

Continuous Delivery is an agile software develop- ment practice in which developers frequently integrate changes into the main development line and produce releases of their software. An automated Continuous Integration infrastructure builds and tests these changes. Claimed advantages of CD include early discovery of (integration) errors,...