77,281 research outputs found
Traceability for Model Driven, Software Product Line Engineering
Traceability is an important challenge for software organizations. This is true for traditional software development and even more so in new approaches that introduce more variety of artefacts such as Model Driven development or Software Product Lines. In this paper we look at some aspect of the interaction of Traceability, Model Driven development and Software Product Line
Analysis of Software Binaries for Reengineering-Driven Product Line Architecture\^aAn Industrial Case Study
This paper describes a method for the recovering of software architectures
from a set of similar (but unrelated) software products in binary form. One
intention is to drive refactoring into software product lines and combine
architecture recovery with run time binary analysis and existing clustering
methods. Using our runtime binary analysis, we create graphs that capture the
dependencies between different software parts. These are clustered into smaller
component graphs, that group software parts with high interactions into larger
entities. The component graphs serve as a basis for further software product
line work. In this paper, we concentrate on the analysis part of the method and
the graph clustering. We apply the graph clustering method to a real
application in the context of automation / robot configuration software tools.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301
Towards standardisation of no fault found taxonomy
There is a phenomenon which exists in complex engineered systems, most notably those which are electrical or electronic which is the inability to diagnose faults reported during operation. This includes difficulties in detecting the same reported symptoms with standard testing, the inability to correctly localise the suspected fault and the failure to diagnose the problem which has resulted in maintenance work. However an inconsistent terminology is used in connection with this phenomenon within both scientific communities and industry. It has become evident that ambiguity, misuse and misunderstanding have directly compounded the issue. The purpose of this paper is to work towards standardisation of the taxonomy surrounding the phenomena popularly termed No Fault Found, Retest Okay, Cannot Duplicate or Fault Not Found amongst many others. This includes discussion on how consistent terminology is essential to the experts within organisation committees and, to the larger group of users, who do not have specialised knowledge of the field
Ways of Applying Artificial Intelligence in Software Engineering
As Artificial Intelligence (AI) techniques have become more powerful and
easier to use they are increasingly deployed as key components of modern
software systems. While this enables new functionality and often allows better
adaptation to user needs it also creates additional problems for software
engineers and exposes companies to new risks. Some work has been done to better
understand the interaction between Software Engineering and AI but we lack
methods to classify ways of applying AI in software systems and to analyse and
understand the risks this poses. Only by doing so can we devise tools and
solutions to help mitigate them. This paper presents the AI in SE Application
Levels (AI-SEAL) taxonomy that categorises applications according to their
point of AI application, the type of AI technology used and the automation
level allowed. We show the usefulness of this taxonomy by classifying 15 papers
from previous editions of the RAISE workshop. Results show that the taxonomy
allows classification of distinct AI applications and provides insights
concerning the risks associated with them. We argue that this will be important
for companies in deciding how to apply AI in their software applications and to
create strategies for its use
Structured Review of the Evidence for Effects of Code Duplication on Software Quality
This report presents the detailed steps and results of a structured review of code clone literature. The aim of the review is to investigate the evidence for the claim that code duplication has a negative effect on code changeability. This report contains only the details of the review for which there is not enough place to include them in the companion paper published at a conference (Hordijk, Ponisio et al. 2009 - Harmfulness of Code Duplication - A Structured Review of the Evidence)
A Taxonomy for a Constructive Approach to Software Evolution
In many software design and evaluation techniques, either the software evolution problem is not systematically elaborated, or only the impact of evolution is considered. Thus, most of the time software is changed by editing the components of the software system, i.e. breaking down the software system. The software engineering discipline provides many mechanisms that allow evolution without breaking down the system; however, the contexts where these mechanisms are applicable are not taken into account. Furthermore, the software design and evaluation techniques do not support identifying these contexts. In this paper, we provide a taxonomy of software evolution that can be used to identify the context of the evolution problem. The identified contexts are used to retrieve, from the software engineering discipline, the mechanisms, which can evolve the software software without breaking it down. To build such a taxonomy, we build a model for software evolution and use this model to identify the factors that effect the selection of software evolution\ud
mechanisms. Our approach is based on solution sets, however; the contents of these sets may vary at different stages of the software life-cycle. To address this problem, we introduce perspectives; that are filters to select relevant elements from a solution set. We apply our taxonomy to a parser tool to show how it coped with problematic evolution problems
- …