Automated program repair using genetic programming and model checking

Automated program repair is still a highly challenging problem mainly due to the reliance of the current techniques on test cases to validate candidate patches. This leads to the increasing unreliability of the final patches since test cases are partial specifications of the software. In the present paper, an automated program repair method is proposed by integrating genetic programming (GP) and model checking (MC). Due to its capabilities to verify the finite state systems, MC is employed as an appropriate criterion for evolving programs to calculate the fitness in GP. The application of MC for the fitness evaluation, which is novel in the context of program repair, addresses an important gap in the current heuristic approaches to the program repair. Being focused on fault detection based on the desired aspects, it enables the programmers to detect faults according to the definition of properties. Creating a general method, this characteristic can be effectively customized for different domains of application and the corresponding faults. Apart from various types of faults, the proposed method is capable of handling concurrency bugs which are not the case in many general repair methods. To evaluate the proposed method, it was implemented as a tool, named JBF, to repair Java programs. To meet the objectives of the study, some experiments were conducted in which certain programs with known bugs were automatically repaired by the JBF tool. The obtained results are encouraging and remarkably promising.     

Fatigue Crack Initiation and Propagation in Piles of Integral Abutment Bridges

Abstract: A new continuum damage modeling approach of “successive initiation” is used to determine the location of a thermomechanical fatigue crack initiation and the propagation path and rate in piles of integral abutment bridges. A global‐local modeling approach is introduced to determine the critical location in the pile where a crack is initiated using a 3‐dimensional nonlinear finite element model and to implement “successive initiation.” A simulated case study is used to showcase the multistep procedure. The results indicate that for a pile subjected to the maximum stress, the first fatigue‐induced crack initiates in the tip of the flange at the element immediately below the abutment. Several other cracks at different locations form in the flange of the pile while the initial crack continues to propagate in the flange to the web. The crack propagation rate increases as more cracks initiate in the flange. The propagation rate decreases when the crack reaches the web. Based on the case study presented, a crack could initiate in the pile in as little as 6 years, but it may take about 20 years for it to reach the web; however, final failure of the pile may not take place for several decades. The method can also be used as a guide in bridge foundation inspection and in the determination of the remaining life of an existing bridge.     

Randomized gossip algorithms under attack

Recently, gossip-based algorithms have received significant attention for data aggregation in distributed environments. The main advantage of gossip-based algorithms is their robustness in dynamic and fault-prone environments with unintentional faults such as link failure and channel noise. However, the robustness of such algorithms in hostile environments with intentional faults has remained unexplored. In this paper, we call attention to the risks which may be caused by the use of gossip algorithms in hostile environments, i.e., when some malicious nodes collude to skew aggregation results by violating the normal execution of the protocol. We first introduce a model of hostile environment and then examine the behavior of randomized gossip algorithms in this model using probabilistic analysis. Our model of hostile environment is general enough to cover a wide range of attacks. However, to achieve stronger results, we focus our analysis on fully connected networks and some powerful attacks. Our analysis shows that in the presence of malicious nodes, after some initial steps, randomized gossip algorithms reach a point at which the lengthening of gossiping is harmful, i.e., the average accuracy of the estimates of the aggregate value begins to decrease strictly.     

DDoS attack detection in IEEE 802.16 based networks

Achieving high data rate transmission, WiMAX has acquired noticeable attention by communication industry. One of the vulnerabilities of the WiMAX network which leads to DDoS attack is sending a high volume of ranging request messages to base station (BS) in the initial network entry process. In the initial network entry process, BS and subscriber station (SS) exchange management messages. Since some of these messages are not authenticated, malicious SSs can attack the network by exploiting this vulnerability which may increase the traffic load of the BS and prevent it from serving the SSs. So, detecting such attacks is one of the most important issues in such networks. In this research, an artificial neural network (ANN) based approach is proposed in order to detect DDoS attacks in IEEE 802.16 networks. Although lots of studies have been devoted to the detection of DDoS attack, some of them focus just on some statistical features of the traffic and some other focus on packets’ headers. The proposed approach exploits both qualitative and quantitative methods. It detects the attack by feeding some features of the network traffic under attack to an appropriate ANN structure. To evaluate the method, first a typical attacked network is implemented in OPNet simulator, and then by using the proposed system, the efficiency of the method is evaluated. The results show that by choosing suitable time series we can classify 93 % of normal traffic and 91 % of attack traffic.     

Effect of Selected Process Parameters on Durability and Defects in Surface-Mount Assemblies for Portable Electronics

This paper presents a systematic approach to study the effect of manufacturing variables on the creation of defects and the effect of those defects on the durability of lead-free (Pb-free) solder joints. An experiment was designed to systematically vary the printing and reflow process variables in order to fabricate error-seeded test assemblies. The error-seeded samples were then inspected visually and with X-ray, to identify different types of defects, especially voids, and then test for electrical performance. The specimens were subjected to an accelerated thermal cycling test to characterize the durability of these error-seeded specimens and to study the effect of each manufacturing variable on the durability of the solder joints. The response variables for the design of experiments are thermal cycling durability of the solder joints and void area percentage in ball grid array (BGA) solder joints. Pretest microstructural analysis showed that specimens produced under inadequate reflow profiles suffered from insufficient wetting and insufficient intermetallic formation. Statistical analysis of the response variables shows that waiting time, heating ramp, peak temperature, and cooling rate have nonlinear effects on thermal cycling durability. Two variables in particular [peak temperature and waiting time (the time waited after the solder paste barrel was opened and before print)] appear to have optimum values within the ranges investigated. Statistical analysis of void percentage area for all design of experiment (DOE) runs show that higher stencil thickness results in higher void percentage and that void percentage increases as time above melt and peak temperature increases.     

Grain Growth Orientation and Anisotropy in Cu6Sn5 Intermetallic: Nanoindentation and Electron Backscatter Diffraction Analysis

As the size of joints in micro/nano-electronics diminishes, the role of intermetallic (IMC) layers becomes more significant. It was shown that solder joint strength is controlled largely by IMC strength at higher strain rates. Additionally, there is a possibility that very small joints are completely composed of IMCs. Further miniaturization of joints may result in statistical grain size effects. Therefore, it is essential to characterize IMC materials and understand their anisotropic mechanical properties. One of the most common types of IMCs in microelectronic joints is Cu₆Sn₅, which is formed in a variety of bonding materials with different compositions of Sn, Cu, and Ag. This work studies through nanoindentation elastic–plastic properties of a single grain of Cu₆Sn₅ IMC in a Sn-3.5Ag/Cu system with reflow soldering. Elastic properties such as elastic modulus and hardness were determined from the nanoindentation load–depth curve. The reverse analysis model described by Dao et al. was used to extract plastic properties such as yield strength and strain hardening exponent from nanoindentation data. Care was taken to achieve indentation of single grains with sufficient accuracy and repeatability. Electron backscatter diffraction (EBSD) mapping was used to determine orientation of Cu₆Sn₅ grains and to relate the orientation with the load–depth curve results of nanoindentation and the corresponding elastic and plastic properties. The EBSD results indicated that the Cu₆Sn₅ crystal structure is hexagonal. Columnar growth of the Cu₆Sn₅ grains was observed as the grains mostly grew along the c-axis of the crystal. Indentation of different grains parallel to the basal plane showed no significant difference in mechanical properties.     

Mechanical Strength and Failure Characterization of Sn-Ag-Cu Intermetallic Compound Joints at the Microscale

Continuous miniaturization of microelectronic devices has led the industry to develop interconnects on the order of a few microns for advanced superhigh-density and three-dimensional integrated circuits (3D ICs). At this scale, interconnects that conventionally consist of solder material will completely transform to intermetallic compounds (IMCs) such as Cu₆Sn₅. IMCs are brittle, unlike conventional solder materials that are ductile in nature; therefore, IMCs do not experience large amounts of plasticity or creep before failure. IMCs have not been fully characterized, and their mechanical and thermomechanical reliability is questioned. This study presents experimental efforts to characterize such material. Sn-based microbonds are fabricated in a controlled environment to assure complete transformation of the bonds to Cu₆Sn₅ IMC. Microstructural analysis including scanning electron microscopy (SEM), energy-dispersive x-ray spectroscopy (EDS), and x-ray diffraction (XRD) is utilized to determine the IMC material composition and degree of copper diffusion into the bond area. Specimens are fabricated with different bond thicknesses and in different configurations for various tests. Normal strength of the bonds is measured utilizing double cantilever beam and peeling tests. Shear tests are conducted to quantify the shear strength of the material. Four-point bending tests are conducted to measure the fracture toughness and critical energy release rate. Bonds are fabricated in different sizes, and the size effect is investigated. The shear strength, normal strength, critical energy release rate, and effect of bond size on bond strength are reported.