Imran Sarwar Bajwa

OCL Constraints Generation from Natural Language Specification

Object Constraint Language (OCL) plays a key role in Unified Modeling Language (UML). In the UML standards, OCL is used for expressing constraints such as well-definedness criteria. In addition OCL can be used for specifying constraints on the models and pre/post conditions on operations, improving the precision of the specification. As a result, OCL has received considerable attention from the research community. However, despite its key role, there is a common consensus that OCL is the least adopted among all languages in the UML. It is often argued that, software practitioners shy away from OCL due to its unfamiliar syntax. To ensure better adoption of OCL, the usability issues related to producing OCL statement must be addressed. To address this problem, this paper aims to preset a method involving using Natural Language expressions and Model Transformation technology. The aim of the method is to produce a framework so that the user of UML tool can write constraints and pre/post conditions in English and the framework converts such natural language expressions to the equivalent OCL statements. As a result, the approach aims at simplifying the process of generation of OCL statements, allowing the user to benefit form the advantages provided by UML tools that support OCL. The suggested approach relies on Semantic Business Vocabulary and Rules (SBVR) to support formulation of natural language expressions and their transformations to OCL. The paper also presents outline of a prototype tool that implements the method.

Minimizing ambiguity in natural language software requirements specification

Software requirements are typically captured in natural languages (NL) such as English and then analyzed by software engineers to generate a formal software design/model (such as UML model). However, English is syntactically ambiguous and semantically inconsistent. Hence, the English specifications of software requirements can not only result in erroneous and absurd software designs and implementations but the informal nature of English is also a main obstacle in machine processing of English specification of the software requirements. To address this key challenge, there is need to introduce a controlled NL representation for software requirements to generate accurate and consistent software models. In this paper, we report an automated approach to generate Semantic of Business Vocabulary and Rules (SBVR) standard based controlled representation of English software requirement specification. The SBVR based controlled representation can not only result in accurate and consistent software models but also machine process able because SBVR has pure mathematical foundation. We also introduce a java based implementation of the presented approach that is a proof of concept.

Back to Origin: Transformation of Business Process Models to Business Rules

A business process model should be explained to the business stakeholders to validate that it is a correct representation of targeted information of a particular domain. A business process model is typically represented by using a graphical notation such as Business Process Modelling Notation (BPMN). A graphical representation of a business process model can be complex to understand for the business stakeholders. However, a business rule represented in a natural language can be easy to understand for a novel person. Moreover, the extracted business rules can be employed for reuse of information through mapping to other standards such as BPEL, OCL, etc. In this paper, we present a novel approach to automatically generate natural language representation of business process models explained in BPMN. The presented approach employs SBVR (Semantics of Business Vocabulary and Rules) as an intermediate representation to generate natural language expressions those are easy to understand for business stake holders.

Clinical Decision Support System Based Virtual Telemedicine

Telemedicine is a blessing for the people of remote areas because it provides high level medical facilities in an efficient way at low cost. Store-and-Forward method of telemedicine suits more to the progressive countries like Pakistan as not only because it is easy to set up but also due to its cheap operating cost. However, the high response time taken by store & forward telemedicine becomes a critical factor in emergency cases, where each minute has a price. The response time factor can be overcome by using virtual telemedicine approach. In virtual telemedicine, a Clinical Decision Support System (CDSS) is deployed at rural station. The CDSS is intelligent enough to diagnose a patients disease and prescribe proper medication. In a case, the CDSS can not answer a query, the CDSS immediately sends an e-mail to a medical expert (doctor) and when the response is received the CDSS knowledge-base is updated for the future queries. In this research paper, we not only report a NL-based CDSS that can answer NL queries but also present a complete architecture of a virtual telemedicine setup.

Resolving syntactic ambiguities in natural language specification of constraints

In the NL2OCL project, we aim to translate English specification of software constraints to formal constraints such as OCL (Object Constraint Language). In the used approach, the Stanford POS tagger and the Stanford Parser are employed for syntactic analysis of English specification and the output of syntactic analysis is given to our semantic analyzer for the detailed semantic analysis. However, in few cases, the Stanford POS tagger and parser are not able to handle particular syntactic ambiguities in English specifications of software constraints. In this paper, we highlight the identified cases of syntactic ambiguities and we also present a novel technique to automatically resolve the identified syntactic ambiguities. By addressing the identified cases of syntactic ambiguities, we can generate more accurate and complete formal (OCL) specifications.

A hash-based approach for colour image steganography

In this, paper we propose a novel hash-based approach for colour image steganography. As, the available approaches for colour image steganography are using chaos-based and symmetric-key based cryptographic algorithms are not efficient and good for bulky data. However, the hash-based algorithms based approaches are considerably better in terms of providing better speed but these approaches are vulnerable in terms of providing security due to inherent flaws caused by used checksum approach. The key reason of vulnerability is that the used algorithms in such approaches such as MD5 and SHA-2 have flaws. In our approach, we purpose the use of perfect hash-function algorithm to provide a secure and fast approach for colour image steganography. We also present a prototype tool in this paper that is implementation of the presented approach and is also a proof of concept. Another contribution of the approach is that the presented approach can be used for coding data in any type of colour images such as bmp, jpeg, gif, and tiff as other available approaches are file format specific. The results of the initial experiments are very encouraging and support not only the used approach but also uphold the potential of the presented approach in general.

BPM Meeting with SOA: A Customized Solution for Small Business Enterprises

This research paper presents a new pattern for the espousal of SOA in small enterprises for the service delivery beyond the typical role of SOA and BPM for dynamic endorsement of the processes beyond the ordinary border-lines. In comparison with large enterprises, the presented framework can expose the fact that the improvements of service orientation and the fruits of process management can be confined for small business enterprises as well. Service Oriented Architecture (SOA) and Business Process Management (BPM) in combination have been used for agility in services and dynamic process management for many years. The partnership of BPM and SOA has been fruitful by merging the benefits of both sides. These benefits are still being wallowed by the large sized enterprises, who can not only handle these large scale architectures using their vigorous work force but also have the enough budget to manage the ultimate expenses. In this paper, the key issues regarding the transformation of BPM and SOA partnership for small business enterprises has been elaborated.

From Natural Language Software Specifications to UML Class Models

Software specifications are typically captured in natural languages and then software analysts manually analyzed and produce the software models such class models. Various approaches, frameworks and tool have been presented for automatic translation of software models such as CM-Builder, Re-Builder, NL-OOML, GOOAL, etc. However, the experiments with these tools show that they do not provide with high accuracy in translation. Major reason of less accuracy reported in the literature is the ambiguous and informal nature of the natural languages. In this article, we aim to address this issue and present a better approach for processing natural languages and produce more accurate UML software models. The presented approach is based on Semantic Business Vocabulary and Rules (SBVR) recently adopted standard by OMG. Our approach works as the natural language software specifications are first mapped to SBVR rules representation. SBVR rules are easy to translate other formal representations such as OCL and UML as SBVR is based on higher order logic. A case study solved with our tool NL2UMLviaSBVR is also presented and the a comparative analysis of our tools research with other available tools show that use of SBVR in NL to UML translation helps to improve the accuracy.

SBVR2UML: A Challenging Transformation

UML is a de-facto standard used for generating the software models. UML support visualization of the software artifacts. To generate a UML diagram, a software engineer has to collect software requirements in a natural language (such as English) or a semi-formal language (such as SBVR), manually analyze the requirements and then manually generate the class diagrams in an available CASE tool. However, by automatically transforming SBVR Software requirements to UML can seriously share burden of a system analyst and can improve the quality and robustness of software modeling phase. The paper demonstrates the challenging aspect of model transformation from SBVR to UML. The presented approach takes input the software requirements specified in SBVR syntax, parses the input specification, extracts the UML ingredients such as classes, methods, attributes, associations, etc and finally generate the visual representation of the extracted information. The presented approach is fully automated. The presented approach is explained via an example.

NL-Based Automated Software Requirements Elicitation and Specification

This paper presents a novel approach to automate the process of software requirements elicitation and specification. The software requirements elicitation is perhaps the most important phase of software development as a small error at this stage can result in absurd software designs and implementations. The automation of the initial phase (such as requirement elicitation) phase can also contribute to a long standing challenge of automated software development. The presented approach is based on Semantic of Business Vocabulary and Rules (SBVR), an OMG’s recent standard. We have also developed a prototype tool SR-Elicitor (an Eclipse plugin), which can be used by software engineers to record and automatically transform the natural language software requirements to SBVR software requirements specification. The major contribution of the presented research is to demonstrate the potential of SBVR based approach, implemented in a prototype tool, proposed to improve the process of requirements elicitation and specification.