This paper presents a novel method for testing Boolean expressions. It is based on spectral, aka Fourier analysis of Boolean functions which is exploited to generate test inputs. The approach has three important contributions: (i) It generates a relatively small test suite with a high capability of fault detection, (ii) The test suite is prioritized such that expected fault detection time is shorter, (iii) It is entirely mathematical relying on a simple and straightforward formula. The proposed method is formulated and evaluations are performed on both synthetic and real expressions. It is also compared with two common test generation criteria, MC/DC and Minimal MUMCUT. Evaluations show that the test suite generated by the spectral approach is relatively small while expressing the capability of a better and quicker fault detection. The approach presented in this paper provides a useful insight into how spectral/Fourier analysis of Boolean functions can be exploited in software testing.

Boolean expressions are highly involved in control flows of programs and software specifications. Coverage criteria for Boolean expressions aim at producing minimal test suites to detect software faults. There exist various testing criteria, efficiency of which is usually evaluated through mutation analysis. This paper proposes an integer programming-based minimal test suite generation technique relying on mutation analysis. The proposed technique also takes into account the cost of fault detection. The technique is optimal such that the resulting test suite guarantees to detect all the mutants under given fault assumptions, while maximizing the average percentage of fault detection of a test suite. Therefore, the approach presented can also be considered as a reference method to check the efficiency of any common technique. The method is evaluated using four well-known real benchmark sets of Boolean expressions and is also exemplary compared with MCDC criterion. The results show that the test suites generated by the proposed method provide better fault coverage values and faster fault detection.

Summary Test case prioritization aims at scheduling test cases in an order that improves some performance goal. One performance goal is a measure of how quickly faults are detected. Such prioritization can be performed by exploiting the fault exposing potential (FEP) parameters associated to the test cases. The FEP is usually approximated by mutation analysis under certain fault assumptions. Although this technique is effective, it could be relatively expensive compared to the other prioritization techniques. This study proposes a cost‐effective FEP approximation for prioritizing modified condition decision coverage (MCDC) test cases. A strict negative correlation between the FEP of an MCDC test case and the influence value of the associated input condition allows to order the test cases easily without the need of an extensive mutation analysis. The method is entirely based on mathematics and it provides useful insight into how spectral analysis of Boolean functions can benefit software testing.

With the significant growth in the cloud-based systems, many industries give their attention to cloud computing solutions. E-learning is a promising application area since its typical requirements such as dynamically allocation of computation and storage resources, coincide well with cloud characteristics. This paper presents some possible cloud solutions in e-learning environments by emphasizing its pros and cons. It is of paramount importance to choose the most suitable cloud model for an e-learning application or an educational organization in terms of scalability, portability and security. We distinguish various deployment alternatives of cloud computing and discuss their benefits against typical e-learning requirements.

We present a formal approach to implement fault-tolerance in real-time embedded systems. The initial fault-intolerant system consists of a set of independent periodic tasks scheduled onto a set of fail-silent processors connected by a reliable communication network. We transform the tasks such that, assuming the availability of an additional spare processor, the system tolerates one failure at a time (transient or permanent). Failure detection is implemented using heartbeating, and failure masking using checkpointing and rollback. These techniques are described and implemented by automatic program transformations on the tasks' programs. The proposed formal approach to fault-tolerance by program transformations highlights the benefits of separation of concerns. It allows us to establish correctness properties and to compute optimal values of parameters to minimize fault-tolerance overhead. We also present an implementation of our method, to demonstrate its feasibility and its efficiency.

We present a formal approach to implement and certify fault-tolerance in real-time embedded systems. The fault-intolerant initial system consists of a set of independent periodic tasks scheduled onto a set of fail-silent processors. We transform the tasks such that, assuming the availability of an additional spare processor, the system tolerates one failure at a time (transient or permanent). Failure detection is implemented using heartbeating, and failure masking using checkpointing and roll-back. These techniques are described and implemented by automatic program transformations on the tasks' programs. The proposed formal approach to fault-tolerance by program transformation highlights the benefits of separation of concerns and allows us to establish correctness properties.

This paper presents an implementation of feedback control strategy on distributed static scheduling. The static schedule is created taking into account the average execution times of the tasks. Feedback control algorithm handles the unestimated dynamic behaviors in the system and keeps the performance at a desired level. The approach of feedback control supporting static scheduling yields more flexible scheduling, low scheduling overhead and better resource utilization while preserving the realtime constraints.