Software Is Not Soft

Traditional software updating techniques usually needs to shut down the applications, which make them not applicable for applications that needs continuous service. Dynamic software updating (DSU) can update the running programs without downtime, but the existing DSU systems cannot combine flexibility, immediacy and security when they update the software. This paper presents an Immediate and Safe Live Update System (ISLUS) for C program, which aims to update the multi-threaded program securely and immediately without downtime or extra assistance of the special compiler. To solve the semantic security problem when other DSU systems update the functions being called on the stack, ISLUS makes a novel intermediate function as a transition from the old function to the new function. To guarantee the reliability of DSU, which has many dangerous memory operations, ISLUS proposes a rollback mechanism based on checkpoint that can be used to restore the crashed program, which cannot be achieved by the other DSU systems. We provide an example to explain ISLUS and do the security analysis. We have prototyped our system and deployed ISLUS to update two big data applications: Memcached and Redis. The results indicate that ISLUS is effective and with low-overhead.

Business process modelling is an important part of system design. When designing or redesigning a business process, stakeholders specify, negotiate, and agree on business requirements to be satisfied, including non-functional requirements that concern the quality of the business process. This thesis addresses the question of how to specify and compute the quality of a business process, given the model that stakeholders use. The motivation for this thesis is the increasing importance of the quality of business processes. Knowing the quality of specific business processes enables stakeholders to judge if these processes need improvement. Knowing the quality of the constructs of those processes (viz., events, inputs, activities, and outputs) and the way they are structured enables a more detailed analysis of their shortcomings and provides a basis for the design of improvements. The research challenge of this thesis is grounded in the assumption that: “Organisations need an appropriate means to effectively compute achievement of their goals and objectives by their business processes.” Given this challenge, the main research question on which this thesis focuses is: “Can the quality of a business process be computed quantitatively at different levels of granularity?” The research objective is: “To develop frameworks, factors, and metrics for computing non-functional requirements (quality) of business processes quantitatively at different levels of granularity.” The outcomes of this thesis are: 1) BPIMM, a language-independent business process integrating meta-model, based on the concepts of seven mainstream business process modelling languages: BPMN, EPC, RAD, UML AD, SADT, IDEF0, and IDEF3. 2) BPC-QC (Business Process Concept - Quality Computation), an approach to quality computation at the lowest level of granularity of a business process. The approach consists of: i. BPC-QEF (Business Process Concept - Quality Evaluation Framework), a language-independent generic framework and algorithm to compute the quality of the constructs of a business process: event, input, activity, and output. ii. A set of business process quality dimensions and factors. The following quality dimensions are distinguished: performance, efficiency, reliability, recoverability, permissibility, and availability. Each dimension categorises different quality aspects in terms of factors. A non-exhaustive set of sixteen quantitative factors is provided. iii. Quality metrics for each of the quality factors, to facilitate a quantitative computation of the quality of a specific construct of a business process. 3) BP-QC (Business Process - Quality Computation), an approach to compute the quality at the highest level of granularity of a business process. The approach consists of: i. BP-CQCF (Business Process - Compositional Quality Computation Framework), a language-independent generic framework and algorithm to compute the quality of a business process as a whole, given the quality of its constructs. ii. A set of generic business process modelling patterns to decompose a business process into more succinct parts, namely: sequential, parallel with synchronisation, exclusive, inclusive, simple loop, and complex loop. iii. A set of over one hundred computational formulae. For each combination of modelling pattern and a quality factor, there is a formula to compute the quality. 4) AAV (Approach to Application and Validation), an evaluation plan to evaluate BPIMM, BPC-QC and BP-QC in practice, together with expert stakeholders. The plan consists of the units of measure, a measurement model, and a case study procedure. To evaluate the applicability of the contributions of this thesis to real world business needs, four case studies have been conducted in different environments: a Dutch educational institution, a global financial institution, an international financial service provider, and a Dutch research project on crisis management. Each of these case studies concerns a different, single business process. This thesis shows that: 1) A quality computation approach can be adopted independent of a business process modelling language. 2) Quantitative quality factors can be introduced specifically for the constructs of a business process. 3) Quantitative metrics and computational formulae can be developed for specific quality factors, allowing the computation of different aspects of the quality of a business process quantitatively at different levels of granularity. 4) An evaluation plan can be developed to evaluate the applicability of the contributions of this thesis (viz., BPIMM, BPC-QC, and BP-QC). The contributions of this thesis are designed to be beneficial to the areas of business and management, requirements engineering, software engineering, and business process modelling. In the areas of requirements engineering and software engineering, these contributions are intended to help practitioners to consider non-functional requirements at the earliest stage. In the area of business process modelling, information systems, service computing, and cloud computing, the contributions can be used for quality-driven modelling, design, and redesign. To conclude, knowing the quality value of a business process at different levels of granularity provides a basis for its improvement.

Dynamic software updates can be used to fix bugs or add features to a running program without downtime. Essential for some applications and convenient for others, low-level dynamic updating has been used for many years. Perhaps surprisingly, there is little high-level understanding or language support to help programmers write dynamic updates effectively.To bridge this gap, we present Proteus, a core calculus for dynamic software updating in C-like languages that is flexible, safe, and predictable. Proteus supports dynamic updates to functions (even active ones), to named types and to data, allowing on-line evolution to match source-code evolution as we have observed it in practice. We ensure updates are type-safe by checking for a property we call "con-freeness" for updated types t at the point of update. This means that non-updated code will not use t concretely beyond that point (concrete usages are via explicit coercions) and thus t's representation can safely change. We show how con-freeness can be enforced dynamically for a particular program state. We additionally define a novel and efficient static updateability analysis to establish con-freeness statically, and can thus automatically infer program points at which all future (well-formed) updates will be type-safe. We have implemented our analysis for C and tested it on several well-known programs.

Maintenance downtime and overheads for applying patches are major concerns for systems requiring round the clock availability. Hence, methods for carrying out dynamic updates are needed. However, correctness of the system during and after every dynamic update needs to be ensured. This paper defines two safety criteria, type consistency and isolation of process execution/or dynamic software update. Updates involving one or more insertions of new classes, removals of old classes and replacements of old classes are considered. The condition for producing a type safe update schedule is defined. The parts of the program whose executions have to be isolated from process update are annotated by the user. Conditions are also provided for ensuring isolation of the update process from execution of annotated parts of the program.

Patching a program during its execution without restarting is called dynamic software updating (DSU). DSU is well acknowledged in research, but rarely applied in practice as witnessed by constant need for reboots and restarts of both applications as well as operating systems. This raises the question of how well DSU related techniques are supported in education. In this paper, we review how the major software engineering and education guides acknowledge dynamic software updating techniques. Our analysis indicates that although DSU is not explicitly mentioned in the guides, the need is already well motivated and many DSU concepts are implicitly supported. Based on this, we argue that DSU could be introduced as an optional topic in software engineering studies.

In traditional formal concept analysis, the attributes in the formal context are considered fixed. However, in the real world data set, attributes always have different levels of granularity, correspondingly, the derived concept lattice may reveal different information and patterns. Therefore, the capability to change the level of granularity of an attribute in formal concept analysis to capture relevant patterns in data is a natural requirement. In this paper, a theoretical study has been undertaken in multi-scale formal contexts, where attributes with different levels of granularity possess different attribute values. Two types of formal concepts, i.e., object-oriented and property-oriented multi-scale concepts, are introduced and studied in detail. The collection of object-oriented concept lattices and property-oriented concept lattices can be obtained at different granularity levels of attributes. It has been shown that the set of extents in the derived concept lattices increases when we choose to use a finer level of granularity. Moreover, a corresponding bidirectional approach to concept construction(i.e., from coarser to finer and from finer to coarser, respectively) is exhibited, and some characterization theorems have been obtained.

In this paper we present a system for automatic Arabic text diacritization using three levels of analysis granularity in a layered back off manner. We build and exploit diacritized language models (LM) for each of three different levels of granularity: surface form, morphologically segmented into prefix/stem/suffix, and character level. For each of the passes, we use Viterbi search to pick the most probable diacritization per word in the input. We start with the surface form LM, followed by the morphological level, then finally we leverage the character level LM. Our system outperforms all of the published systems evaluated against the same training and test data. It achieves a 10.87% WER for complete full diacritization including lexical and syntactic diacritization, and 3.0% WER for lexical diacritization, ignoring syntactic diacritization.

Data warehousing is widely used in industry for reporting and analysis of huge volumes of data at different levels of detail. In general, data warehouses use standard dimensional schema designs to organize their data. However, current data warehousing schema designs fall short in their ability to model the multi-granular data found in various real-world application domains. For example, modern farm equipment in a field produces massive amounts of data at different levels of granularity that has to be stored and queried. A study of the commonly used data warehousing schemas exposes the limitation that the schema designs are intended to simply store data at the same single level of granularity. This paper on the other hand, presents several extended dimensional data warehousing schema design alternatives to store both detail and aggregated data at different levels of granularity. The paper presents three solutions to design the time dimension tables and four solutions to design the fact tables. Moreover, each of these solutions is evaluated in different combinations of the time dimension and the fact tables based on a real world farming case study.KeywordsMulti-granular datadata warehousingdata warehousing schema design

Geo‐SOMis a useful geovisualization technique for revealing patterns in spatial data, but is ineffective in supporting interactive exploration of patterns hidden in differentGeo‐SOMsizes. Based on the divide and group principle in geovisualization, the article proposes a new methodology that combinesGeo‐SOMand hierarchical clustering to tackle this problem.Geo‐SOMwas used to “divide” the dataset into several homogeneous subsets; hierarchical clustering was then used to “group” neighboring homogeneous subsets for pattern exploration in different levels of granularity, thus permitting exploration of patterns at multiple scales. An artificial dataset was used for validating the method's effectiveness. As a case study, the rush hour motorcycle flow data inTaipeiCity,Taiwan were analyzed. Compared with the best result generated solely byGeo‐SOM, the proposed method performed better in capturing the homogeneous zones in the artificial dataset. For the case study, the proposed method discovered six clusters with unique data and spatial patterns at different levels of granularity, while the originalGeo‐SOMonly identified two. Among the four hierarchical clustering methods,Ward's clustering performed the best in pattern discovery. The results demonstrated the effectiveness of the approach in visually and interactively exploring data and spatial patterns in geospatial data.

Due to the rapid development of social media networks, as well as the recent advances on smartphone technologies, users stopped being only consumers and became data producers. It enabled a new form of sensing, engaging a variety of studies using Location-Based Social Networks (LBSN) data. For instance, in device-to-device(D2D) communication systems, the user location is required to make mobile data offloading possible. However, getting the right location is a challenging task, and the analyses of LBSN datasets provide large-scale studies at a low-cost. On the other hand, depending the the level of granularity used on the analyses, it may result in the success or failure of the prediction. Therefore, in this paper, we show the importance of combining the different levels of granularities for studying user behavior in order to obtain a robuster analysis.

This paper introduces the concept of granularity into routine dynamics studies. To establish levels of granularity we develop a phenomenological perspective on action, the central category of routine dynamics studies. By conducting an extensive literature review we show that routine dynamics scholars have at least unconsciously applied diverging levels of granularity in their empirical studies. We argue that side-stepping questions of explicitly addressing granularity significantly impedes the comparability of studies since different levels of granularity bring different aspects of performing and patterning processes into focus. Following this, we develop a methodological framework that allows scholars to establish and report on the level of granularity in their study. Finally, we sketch out some implications of taking granularity seriously for writing up research on routine dynamics.

Conformance checking provides a set of techniques for comparing observed behavior (event logs) with process models. Health care providers apply it for verifying compliance between activities realized by the patients and clinical protocols. However, health care processes are characterized by high complexity and variability, and clinical protocols can have a level of granularity different from the one in the recorded events. We proposed a new method for configuring the cost function for the alignment-based conformance checking, handling the different levels of granularity to address this problem. The costs are configured based on grouping activities and the specification of undesirable events. We applied this method using the ProM Framework in a real-world dataset containing events from patients who realized a bariatric surgery in 2016. The technique can also be applied in other conformance checking scenarios, where the granularity of the events differs from the process model. The case study result allowed us to automatically identify critical violations of the clinical protocol by analyzing the fitness metric. The proposed method could help auditors to identify crucial cases.

Software evolves to fix bugs and add features. Stopping and restarting programs to apply changes is inconvenient and often costly. Dynamic software updating (DSU) addresses this problem by updating programs while they execute, but existing DSU systems for managed languages do not support many updates that occur in practice and are inefficient. This paper presents the design and implementation of J volve , a DSU-enhanced Java VM. Updated programs may add, delete, and replace fields and methods anywhere within the class hierarchy. Jvolve implements these updates by adding to and coordinating VM classloading, just-in-time compilation, scheduling, return barriers, on-stack replacement, and garbage collection. J volve , is safe : its use of bytecode verification and VM thread synchronization ensures that an update will always produce type-correct executions. Jvolve is flexible : it can support 20 of 22 updates to three open-source programs--Jetty web server, JavaEmailServer, and CrossFTP server--based on actual releases occurring over 1 to 2 years. Jvolve is efficient : performance experiments show that incurs no overhead during steady-state execution. These results demonstrate that this work is a significant step towards practical support for dynamic updates in virtual machines for managed languages.

Dynamic software updating (DSU) systems facilitate software updates to running programs, thereby permitting developers to add features and fix bugs without downtime. This article introduces Kitsune, a DSU system for C. Kitsune’s design has three notable features. First, Kitsune updates the whole program, rather than individual functions, using a mechanism that places no restrictions on data representations or allowed compiler optimizations. Second, Kitsune makes the important aspects of updating explicit in the program text, making the program’s semantics easy to understand while minimizing programmer effort. Finally, the programmer can write simple specifications to direct Kitsune to generate code that traverses and transforms old-version state for use by new code; such state transformation is often necessary and is significantly more difficult in prior DSU systems. We have used Kitsune to update six popular, open-source, single- and multithreaded programs and find that few program changes are required to use Kitsune, that it incurs essentially no performance overhead, and that update times are fast.

In this paper we study the effect of granularity on Characteristic Scores and Scales (CSS). Unlike the traditional indicators that are mostly based on means and quantiles, CSS require the reduction of the citation distributions collaboration of the underlying reference population to four states (classes) and thus higher a different level of granularity. While the question of the choice of granularity is at higher levels of aggregation usually not critical since countries and university have rather multidisciplinary profiles, at lower aggregation levels specialisation becomes more typical. Inappropriate granularity might not warrant the depiction of the publication profiles at these levels in a correct and adequate manner and thus not add accurate citation profiles either. In order to be able to process one complete annual volume of the Web of Science, we decided to calculate CSS thresholds and classes for two levels of granularity, namely sub-fields and WoS Subject Categories. With about 5% deviation, we did not find a real significance. However, we identified journals with similar impact measures but different citation profiles, independently of the granularity. Finally, we have pointed to the limitations in the choice of granularity—in terms of both too broad and too narrow subjects.