| 1. |
- Petersen, Kai, et al.
(author)
-
Choosing Component Origins for Software Intensive Systems: In-House, COTS, OSS or Outsourcing?-A Case Survey
- 2018
-
In: IEEE Transactions on Software Engineering. - : IEEE Computer Society. - 0098-5589 .- 1939-3520. ; 44:3, s. 237-261
-
Journal article (peer-reviewed)abstract
- The choice of which software component to use influences the success of a software system. Only a few empirical studies investigate how the choice of components is conducted in industrial practice. This is important to understand to tailor research solutions to the needs of the industry. Existing studies focus on the choice for off-the-shelf (OTS) components. It is, however, also important to understand the implications of the choice of alternative component sourcing options (CSOs), such as outsourcing versus the use of OTS. Previous research has shown that the choice has major implications on the development process as well as on the ability to evolve the system. The objective of this study is to explore how decision making took place in industry to choose among CSOs. Overall, 22 industrial cases have been studied through a case survey. The results show that the solutions specifically for CSO decisions are deterministic and based on optimization approaches. The non-deterministic solutions proposed for architectural group decision making appear to suit the CSO decision making in industry better. Interestingly, the final decision was perceived negatively in nine cases and positively in seven cases, while in the remaining cases it was perceived as neither positive nor negative.
|
|
| 2. |
- Tran, Hung Vinh, et al.
(author)
-
Performance of cognitive radio networks under interference constraints of multiple primary users
- 2016
-
In: 2016, 10th International Conference on Signal Processing and Communication Systems, ICSPCS 2016 - Proceedings. - : IEEE. - 9781509009411
-
Conference paper (peer-reviewed)abstract
- In this paper, we study the performance of point-to-point communication in spectrum sharing systems under the peak interference power constraint of multiple primary users. In particular, we assume that the channels undergo independent but not necessarily identically distributed Nakagami-m fading with integer values of fading severity parameter m. The cumulative distribution function and probability density function for the signal-to-noise ratio are derived. Based on these formulas, we obtain analytical expressions for the outage probability, the ergodic capacity, and the symbol error probability. Numerical results are also provided to investigate the impact of the peak interference power-to-noise ratio, the number of primary users, and fading parameters on the performance of the secondary network. © 2016 IEEE.
|
|
| 3. |
- Kabiri, Charles, et al.
(author)
-
Outage Probability of a Cognitive Cooperative Relay Network with Multiple Primary Users Under Primary Outage Constraint
- 2016
-
In: PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR COMMUNICATIONS (ATC). - : IEEE. - 9781509027118 - 9781509027101 ; , s. 38-42
-
Conference paper (peer-reviewed)abstract
- In this paper, we consider a cognitive cooperative relay network (CCRN) that utilizes a decode-and-forward relay in the presence of multiple primary users. Given this system setting, we study the effect of multiple primary transmitters (PU-Txs) and multiple primary user receivers (PU-Rxs) on the outage probability of the considered CCRN. Specifically, power allocation policies for the secondary user transmitter (SU-Tx) and the secondary relay (SR) are formulated, subject to the outage constraint which is imposed by the PU-Rxs as well as the peak transmit power limits given at the SU-Tx and SR. On the basis of these power allocation policies for the SU-Tx and SR, an expression for the outage probability of the CCRN is derived. Numerical examples are presented to show the effect of different system parameters on the outage probability of the CCRN.
|
|
| 4. |
- Louis, Sibomana, et al.
(author)
-
A Framework for Packet Delay Analysis of Point-to-Multipoint Underlay Cognitive Radio Networks
- 2017
-
In: IEEE Transactions on Mobile Computing. - : IEEE Computer Society. - 1536-1233 .- 1558-0660. ; 16:9, s. 2408-2421
-
Journal article (peer-reviewed)abstract
- This paper presents a queueing analytical framework for the performance evaluation of the secondary user (SU) packet transmission with service differentiation in a point-to-multipoint underlay cognitive radio network. The transmit power of the SU transmitter is subject to the joint outage constraint imposed by the primary user receivers (PU-Rxs) and the SU maximum transmit power limit. The analysis considers a queueing model for secondary traffic with multiple classes, and different types of arrival and service processes under a non-preemptive priority service discipline. The SU quality of service (QoS) is characterized by a packet timeout threshold and target bit error rate. Given these settings, analytical expressions of the packet timeout probability and average transmission time are derived for opportunistic and multicast scheduling. Moreover, expressions of the average packet waiting time in the queue and the total time in the system for each class of traffic are obtained. Numerical examples are provided to illustrate the secondary network performance with respect to various parameters such as number of PU-Rxs and SU receivers, SU packet arrival process, QoS requirements, and the impact of interference from the primary network to the secondary network.
|
|
| 5. |
- Louis, Sibomana, et al.
(author)
-
On the Outage Capacity of an Underlay Cognitive Radio Network
- 2015
-
In: 2015 9TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS). - : IEEE Press. ; , s. 1-7-
-
Conference paper (peer-reviewed)abstract
- In this paper, we consider a point-to-multipoint underlay cognitive radio network under the joint constraint of the primary user peak interference power and maximum transmit power limit of the secondary user (SU). Analytical expressions for the secondary outage capacity are obtained based on exact as well as approximate expressions of the first and second moments of the channel capacity. Numerical results are provided to assess the effect of the number of SU receivers and a given SU outage probability. We also evaluate the impact of the primary network parameters on the secondary network performance.
|
|
| 6. |
- Tran, Hung Vinh, et al.
(author)
-
On Throughput and Quality of Experience in Cognitive Radio Networks
- 2016
-
In: 2016 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE. - : IEEE. - 9781467398145
-
Conference paper (peer-reviewed)abstract
- In this paper, a performance analysis for cognitive radio networks (CRNs) under the outage probability constraint of the primary user and peak transmit power constraint of the secondary user is conducted. Given an automatic repeat request protocol, analytical expressions for the packet delay and throughput of the CRN are derived. Most importantly, these expressions can be used to understand the quality of experience on web services which are assumed to be offered by the considered CRN.
|
|
| 7. |
- Afzal, Wasif, et al.
(author)
-
Towards benchmarking feature subset selection methods for software fault prediction
- 2016
-
In: Computational Intelligence and Quantitative Software Engineering. - Berlin, Heidelberg : Springer. - 9783319259642 - 9783319259628 ; , s. 33-58
-
Book chapter (peer-reviewed)abstract
- Despite the general acceptance that software engineering datasets often contain noisy, irrele- vant or redundant variables, very few benchmark studies of feature subset selection (FSS) methods on real-life data from software projects have been conducted. This paper provides an empirical comparison of state-of-the-art FSS methods: information gain attribute ranking (IG); Relief (RLF); principal com- ponent analysis (PCA); correlation-based feature selection (CFS); consistency-based subset evaluation (CNS); wrapper subset evaluation (WRP); and an evolutionary computation method, genetic programming (GP), on five fault prediction datasets from the PROMISE data repository. For all the datasets, the area under the receiver operating characteristic curve—the AUC value averaged over 10-fold cross- validation runs—was calculated for each FSS method-dataset combination before and after FSS. Two diverse learning algorithms, C4.5 and na ̈ıve Bayes (NB) are used to test the attribute sets given by each FSS method. The results show that although there are no statistically significant differences between the AUC values for the different FSS methods for both C4.5 and NB, a smaller set of FSS methods (IG, RLF, GP) consistently select fewer attributes without degrading classification accuracy. We conclude that in general, FSS is beneficial as it helps improve classification accuracy of NB and C4.5. There is no single best FSS method for all datasets but IG, RLF and GP consistently select fewer attributes without degrading classification accuracy within statistically significant boundaries.
|
|
| 8. |
- Carlson, Jan, et al.
(author)
-
A Context Model for Architectural Decision Support
- 2016
-
In: Proceedings - 2016 1st International Workshop on Decision Making in Software ARCHitecture, MARCH 2016. - : IEEE Press. - 9781509025732 ; , s. 9-15
-
Conference paper (peer-reviewed)abstract
- Developing efficient and effective decision making support includes identifying means to reduce repeated manual work and providing possibilities to take advantage of the experience gained in previous decision situations. For this to be possible, there is a need to explicitly model the context of a decision case, for example to determine how much the evidence from one decision case can be trusted in another, similar context. In earlier work, context has been recognized as important when transferring and understanding outcomes between cases. The contribution of this paper is threefold. First, we describe different ways of utilizing context in an envisioned decision support system. Thereby, we distinguish between internal and external context usage, possibilities of context representation, and context inheritance. Second, we present a systematically developed context model comprised of five types of context information, namely organization, product, stakeholder, development method & technology, and market & business. Third, we exemplary illustrate the relation of the context information to architectural decision making using existing literature.
|
|
| 9. |
- Cicchetti, Antonio, et al.
(author)
-
Towards Software Assets Origin Selection Supported by a Knowledge Repository
- 2016
-
In: Proceedings - 2016 1st International Workshop on Decision Making in Software ARCHitecture, MARCH 2016. - : IEEE Computer Society. - 9781509025732 ; , s. 22-29
-
Conference paper (peer-reviewed)abstract
- Software architecture is no more a mere system specification as resulting from the design phase, but it includes the process by which its specification was carried out. In this respect, design decisions in component-based software engineering play an important role: They are used to enhance the quality of the system, keep the current market level, keep partnership relationships, reduce costs, and so forth. For non trivial systems, a recurring situation is the selection of an asset origin, that is if going for in-house, outsourcing, open-source, or COTS, when in the need of a certain missing functionality. Usually, the decision making process follows a case-by-case approach, in which historical information is largely neglected: hence, it is avoided the overhead of keeping detailed documentation about past decisions, but it is hampered consistency among multiple, possibly related, decisions.The ORION project aims at developing a decision support framework in which historical decision information plays a pivotal role: it is used to analyse current decision scenarios, take well-founded decisions, and store the collected data for future exploitation. In this paper, we outline the potentials of such a knowledge repository, including the information it is intended to be stored in it, and when and how to retrieve it within a decision case.
|
|
| 10. |
- Enoiu, Eduard Paul, et al.
(author)
-
Mutation-based test generation for PLC embedded software using model checking
- 2016
-
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer. - 9783319474427 ; , s. 155-171
-
Conference paper (peer-reviewed)abstract
- Testing is an important activity in engineering of industrial embedded software. In certain application domains (e.g., railway industry) engineering software is certified according to safety standards that require extensive software testing procedures to be applied for the development of reliable systems. Mutation analysis is a technique for creating faulty versions of a software for the purpose of examining the fault detection ability of a test suite. Mutation analysis has been used for evaluating existing test suites, but also for generating test suites that detect injected faults (i.e., mutation testing). To support developers in software testing, we propose a technique for producing test cases using an automated test generation approach that operates using mutation testing for software written in IEC 61131-3 language, a programming standard for safety-critical embedded software, commonly used for Programmable Logic Controllers (PLCs). This approach uses the Uppaal model checker and is based on a combined model that contains all the mutants and the original program. We applied this approach in a tool for testing industrial PLC programs and evaluated it in terms of cost and fault detection. For realistic validation we collected industrial experimental evidence on how mutation testing compares with manual testing as well as automated decision-coverage adequate test generation. In the evaluation, we used manually seeded faults provided by four industrial engineers. The results show that even if mutation-based test generation achieves better fault detection than automated decision coverage-based test generation, these mutation-adequate test suites are not better at detecting faults than manual test suites. However, the mutation-based test suites are significantly less costly to create, in terms of testing time, than manually created test suites. Our results suggest that the fault detection scores could be improved by considering some new and improved mutation operators (e.g., Feedback Loop Insertion Operator (FIO)) for PLC programs as well as higher-order mutations.
|
|
