Minimising conflicts among run‐time non‐functional requirements within DevOps
Systems Engineering
Significant contributions in the existing literature highlight the potential of softgoal interdep... more Significant contributions in the existing literature highlight the potential of softgoal interdependency graphs towards analyzing conflicting non‐functional requirements (NFRs). However, such analysis is often at a very abstract level and does not quite consider the run‐time performance statistics of NFR operationalizations. On the contrary, some initial empirical evaluations demonstrate the importance of the run‐time statistics. In this paper, a framework is proposed that uses these statistics and combines the same with NFR priorities for computing the impact of NFR conflicts. The proposed framework is capable of identifying the best possible set of NFR operationalizations that minimizes the impact of conflicting NFRs. A detailed space analysis of the solution framework helps proving the efficiency of the proposed pruning mechanism in terms of better space management. Furthermore, a Dynamic Bayesian Network (DBN) ‐ based system behavioral model that works on top of the proposed fra...
r RQ1: How can the end-user app reviews help the develop- ment team to precisely identify the app... more r RQ1: How can the end-user app reviews help the develop- ment team to precisely identify the app features which are of immediate concern? r RQ2: How can the user sentiments be integrated into the recommendation system to identify the more relevant reviews that are significant for the technology value stream? r RQ3: How can we integrate the entire framework within the software development pipeline to automate the continuous maintenance process? Our research methodology for addressing the above mentioned research challenges has been carried out as follows: r Literature Study: A focused study of existing works on the analysis of app reviews was done to understand the existing state-of-the-art. This is presented in detail in Section III.
In the design of autonomous systems, it is important to consider the preferences of the intereste... more In the design of autonomous systems, it is important to consider the preferences of the interested parties to improve the user experience. These preferences are often associated with the contexts in which each system is likely to operate. The operational behavior of a system must also meet various non-functional requirements (NFRs), which can present different levels of conflict depending on the operational context. This work aims to model correlations between the individual contexts and the consequent conflicts between NFRs. The proposed approach is based on analyzing the system event logs, tracing them back to the leaf elements at the specification level and providing a contextual explanation of the system’s behavior. The traced contexts and NFR conflicts are then mined to produce Context-Context and Context-NFR conflict sequential rules. The proposed Contextual Explainability (ConE) framework uses BERT-based pre-trained language models and sequential rule mining libraries for der...
Time required for Applying AES Encryption and Lempel Ziv Compression on Hospital data
We apply the AES Encryption algorithm and the Lempel Ziv(LZ) Compression algorithms on each data ... more We apply the AES Encryption algorithm and the Lempel Ziv(LZ) Compression algorithms on each data record and record the times. Then we apply combinations of AES and LZ on the data records - namely AES(LZ()) and LZ(AES()). We record the 4 times and derive scatter plots.
ZoBe: Zone-Oriented Bandwidth Estimator for Efficient IoT Networks
IoT is made up of heterogeneous networks which transport a huge volume of data packets over the I... more IoT is made up of heterogeneous networks which transport a huge volume of data packets over the Internet. Improper utilization of bandwidth or insufficient bandwidth allocation leads to faults such as packet loss, setting up routing path between source and destination, reduction of speed in data communication, etc. One of the vital causes of insufficient bandwidth is nonuniform growth in the number of Internet users in a specific region. In this paper, we propose a framework for efficient distribution of bandwidth over a region based on depth of field analysis and population statistics analysis. We propose to use existing Google Earth Pro APIs over satellite images to estimate possible number of users in a particular area and plan to allocate bandwidth accordingly. The proposed framework is aimed to reduce packet loss and distortion effects due to scattering and refraction.
ZoBe: Zone-Oriented Bandwidth Estimator for Efficient IoT Networks
IoT is made up of heterogeneous networks which transport a huge volume of data packets over the I... more IoT is made up of heterogeneous networks which transport a huge volume of data packets over the Internet. Improper utilization of bandwidth or insufficient bandwidth allocation leads to faults such as packet loss, setting up routing path between source and destination, reduction of speed in data communication, etc. One of the vital causes of insufficient bandwidth is nonuniform growth in the number of Internet users in a specific region. In this paper, we propose a framework for efficient distribution of bandwidth over a region based on depth of field analysis and population statistics analysis. We propose to use existing Google Earth Pro APIs over satellite images to estimate possible number of users in a particular area and plan to allocate bandwidth accordingly. The proposed framework is aimed to reduce packet loss and distortion effects due to scattering and refraction.
Semantic similarity detection mainly relies on the availability of laboriously curated ontologies... more Semantic similarity detection mainly relies on the availability of laboriously curated ontologies, as well as of supervised and unsupervised neural embedding models. In this paper, we present two domain-specific sentence embedding models trained on a natural language requirements dataset in order to derive sentence embeddings specific to the software requirements engineering domain. We use cosine-similarity measures in both these models. The result of the experimental evaluation confirm that the proposed models enhance the performance of textual semantic similarity measures over existing state-of-the-art neural sentence embedding models: we reach an accuracy of 88.35%-which improves by about 10% on existing benchmarks.
In the field of Natural Language Processing (NLP) the process of stemming plays a significant rol... more In the field of Natural Language Processing (NLP) the process of stemming plays a significant role. Stemmer transforms an inflected word to its root form. Stemmer significantly increases the efficiency of Information Retrieval (IR) systems. It is a very basic yet fundamental text pre-processing task widely used in many NLP tasks. Several important works on stemming have been carried out by researchers in English and other major languages. In this paper, we study and review existing works on stemming in Bengali and other Indian languages. Finally we propose a rule based approach that explores Bengali morphology and leverages WordNet to achieve better accuracy. Our algorithm produced stemming accuracy of 98.86% for Nouns and 99.75% for Verbs.
Dynamic Contextual Goal Management in IoT-Based Systems
One of the crucial research issues in the Internet of Things (IoT) is to capture the exact intent... more One of the crucial research issues in the Internet of Things (IoT) is to capture the exact intent of the user during the specification of system goals. It is often the case that there is a mismatch between what the user asks for and what the user actually needs. Existing works have tried to filter data based on user-specified goals. In this article, we present our framework that tries to align the user’s intent with system goal specifications based on the data being used. Dynamic contextual goal management in IoT-based systems becomes necessary when users start to use more (or less) data than that extracted to fulfill their earlier specified goals. This would require an augmentation of the goals vis-a-vis the used data and the context in which the data was used. To that end, we present the concept of a contextual goal lattice, where goals and their associated contexts are managed appropriately. This would make it easy for future users to specify their goals more accurately and extra...
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Papers by Souvick Das