Better abstractions for reusable components & architectures

Software architecture (SA) is a crucial component of Model Driven Engineering (MDE), since it eases the communication and reuse of designs and components. However, existing languages (e.g., UML, AADL, SysML) are lacking many needed features. In particular, they provide rudimentary support for connectors, a first-class element in the components and connectors (C&C) architectural view and one of the most reusable architectural elements. This is unfortunate, since the difficult properties that need to be guaranteed for complex systems are mainly the non-functional properties, like throughput, security and dependability, which are greatly influenced by the employed connectors. This work reviews the basic abstractions of the C&C view of SA and examines extra architectural elements which can support the detailed, explicit and separate description of behaviour, interaction and control logic

Social Computing for Software Engineering: a Mapping Study.

There is a continual growth in the use of social computing within a breadth of business domains; such as marketing, public engagement and innovation management. Software engineering research, like other similar disciplines, has re- cently started to harness the power of social computing throughout the various development phases; from requirements elicitation to validation and maintenance and for the various methods of development and structures of development teams. However, despite this increasing effort, we still lack a clear picture of the current status of this research. To address that lack of knowledge, we conduct a systematic mapping study on the utilisation of social computing for software engineering. This will inform researchers and practitioners about the current status and progress of the field including the areas of current focus and the geographical and chronological distribution of the research. We do the mapping across a diversity of dimensions including the activities of software engineering, the types of research, the characteristics of social computing and the demographic attributes of the published work. Our study results show a growing interest in the field, mainly in academia, and a general trend toward developing designated social com- puting platforms and utilising them in mainly four software engineering areas; management, coding, requirements engineering, and maintenance and enhancement

Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18

Towards safer composition

Determining whether a set of features can be composed, or safe composition, is a hard problem in software product line engineering because the number of feature combinations can be exponential. We argue that synergies between current approaches to safe composition should be exploited and propose a combined approach. At the heart of our proposal is a merge operation that creates a behavioural description for the entire product family from a feature diagram and descriptions of individual feature behaviour. As a result, we intend to verify more efficiently safe composition for an exponential number of feature combinations

Presentation of the paper "Interaction design principles in WYRED platform" in HCII 2017

This is the presentation of the paper entitled “Interaction design principles in WYRED platform” in the Emerging interactive systems for education session at the HCI International 2017 Conference, held in Vancouver, Canada, 9 - 14 July 2017. This work presents the requirements elicitation phase for the WYRED platform. WYRED (netWorked Youth Research for Empowerment in the Digital society) is a European H2020 Project that aims to provide a framework for research in which children and young people can express and explore their perspectives and interests in relation to digital society, but also a platform from which they can communicate their perspectives to other stakeholders effectively through innovative engagement processes. The requirement elicitation is a basic step to design the interactive mechanism to build up the needed social dialog among the involved stakeholders. In order to set up the right interactive tasks, not only functional requirements are elicited, the non-functional requirements play a key role in this project, specially regarding to ensure the security and privacy of the underage people that will be presented in the development of this project

Genetic Improvement for Code Obfuscation

Genetic improvement (GI) is a relatively new area of software engineering and thus the extent of its applicability is yet to be explored. Although a growing interest in GI in recent years started with the work on automatic bug fixing, the area flourished when results on optimisation of non-functional software properties, such as efficiency and energy consumption, were published. Further success of GI in transplanting functionality from one program to another leads to a question: what other software engineering areas can benefit from the use of genetic improvement techniques? We propose to utilise GI for code obfuscation

Amortising the Cost of Mutation Based Fault Localisation using Statistical Inference

Mutation analysis can effectively capture the dependency between source code and test results. This has been exploited by Mutation Based Fault Localisation (MBFL) techniques. However, MBFL techniques suffer from the need to expend the high cost of mutation analysis after the observation of failures, which may present a challenge for its practical adoption. We introduce SIMFL (Statistical Inference for Mutation-based Fault Localisation), an MBFL technique that allows users to perform the mutation analysis in advance against an earlier version of the system. SIMFL uses mutants as artificial faults and aims to learn the failure patterns among test cases against different locations of mutations. Once a failure is observed, SIMFL requires either almost no or very small additional cost for analysis, depending on the used inference model. An empirical evaluation of SIMFL using 355 faults in Defects4J shows that SIMFL can successfully localise up to 103 faults at the top, and 152 faults within the top five, on par with state-of-the-art alternatives. The cost of mutation analysis can be further reduced by mutation sampling: SIMFL retains over 80% of its localisation accuracy at the top rank when using only 10% of generated mutants, compared to results obtained without sampling

A Survey of Genetic Improvement Search Spaces

Genetic Improvement (GI) uses automated search to improve existing software. Most GI work has focused on empirical studies that successfully apply GI to improve software's running time, fix bugs, add new features, etc. There has been little research into why GI has been so successful. For example, genetic programming has been the most commonly applied search algorithm in GI. Is genetic programming the best choice for GI? Initial attempts to answer this question have explored GI's mutation search space. This paper summarises the work published on this question to date