ICSE

The need for application-level intelligence cannot be easily satisfied with existing architectures or methodologies that separate methods and tools for application developers and data scientists. We aim, therefore, to develop a framework (an ...

In this paper we present a novel software analytics infrastructure supporting for a combination of three requirements to serve software practitioners in utilising data-driven decision making: (1) Real-time insight: streaming software analytics unify ...

One challenge in big data analytics is the lack of tools to manage the complex interactions among code, data and parameters, especially in the common situation where all these factors can change a lot. We present our preliminary experience with DataLab, ...

Online-activity-generated digital traces provide opportunities for novel services and unique insights as demonstrated in, for example, research on mining software repositories. The inability to link these traces within and among systems, such as Twitter,...

The recent growing interest on highly-available data-intensive applications sparked the need for flexible and portable storage technologies, e.g., NoSQL databases. Unfortunately, the lack of standard interfaces and architectures for NoSQLs makes it ...

In big data software engineering, the schema flexibility of NoSQL document stores is a major selling point: When the document store itself does not actively manage a schema, the data model is maintained within the application. Just like object-...

Big Data technologies are rapidly becoming a key enabler for modern industries. However, the entry costs inherent to "going Big" are considerable, ranging from learning curve, renting/buying infrastructure, etc. A key component of these costs is the ...

This article articulates the requirements for an effective big data value engineering method. It then presents a value discovery method, called Eco-ARCH (Eco-ARCHitecture), tightly integrated with the BDD (Big Data Design) method for addressing these ...

Acquirers, system builders, and other stakeholders of big data systems need to define requirements, develop and evaluate solutions, and integrate systems together. A reference architecture enables these software engineering activities by standardizing ...

Elasticity is a key component of modern cloud environments and monitoring is an essential part of this process. Monitoring demonstrates several challenges including gathering metrics from a variety of layers (infrastructure, platform, application), the ...

As businesses become increasingly reliant on big data analytics, it becomes increasingly important to test the choices made within the data miners. This paper reports lessons learned from the BigSE Lab, an industrial/university collaboration that ...

The number and variety of cyber-attacks is rapidly increasing, and the rate of new software vulnerabilities is also rising dramatically. The cybersecurity community typically reacts to attacks after they occur. Being reactive is costly and can be fatal, ...

While the domain of big data is anticipated to affect many aspects of human endeavour, there are numerous challenges in building big data applications among which is how to address big data characteristics in quality requirements. In this paper, we ...