| 1. |
- Abbas, Muhammad, et al.
(författare)
-
Is Requirements Similarity a Good Proxy for Software Similarity? : An Empirical Investigation in Industry
- 2021
-
Ingår i: <em>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) </em>27th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2021, 12 April 2021 - 15 April 2021. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783030731274 ; , s. 3-18, s. 3-18
-
Konferensbidrag (refereegranskat)abstract
- [Context and Motivation] Content-based recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a new requirement is proposed by a stakeholder, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn identify previously developed code. [Question/problem] Several NLP approaches for similarity computation are available, and there is little empirical evidence on the adoption of an effective technique in recommender systems specifically oriented to requirements-based code reuse. [Principal ideas/results] This study compares different state-of-the-art NLP approaches and correlates the similarity among requirements with the similarity of their source code. The evaluation is conducted on real-world requirements from two industrial projects in the railway domain. Results show that requirements similarity computed with the traditional tf-idf approach has the highest correlation with the actual software similarity in the considered context. Furthermore, results indicate a moderate positive correlation with Spearman’s rank correlation coefficient of more than 0.5. [Contribution] Our work is among the first ones to explore the relationship between requirements similarity and software similarity. In addition, we also identify a suitable approach for computing requirements similarity that reflects software similarity well in an industrial context. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and categorization.
|
|
| 2. |
- Dehghani, Razieh, et al.
(författare)
-
On Understanding the Relation of Knowledge and Confidence to Requirements Quality
- 2021
-
Ingår i: REQUIREMENTS ENGINEERING: FOUNDATION FOR SOFTWARE QUALITY (REFSQ 2021). - Cham : Springer Science and Business Media Deutschland GmbH. - 9783030731274 ; , s. 208-224
-
Konferensbidrag (refereegranskat)abstract
- [Context and Motivation] Software requirements are affected by the knowledge and confidence of software engineers. Analyzing the interrelated impact of these factors is difficult because of the challenges of assessing knowledge and confidence. [Question/Problem] This research aims to draw attention to the need for considering the interrelated effects of confidence and knowledge on requirements quality, which has not been addressed by previous publications. [Principal ideas/results] For this purpose, the following steps have been taken: 1) requirements quality was defined based on the instructions provided by the ISO29148:2011 standard, 2) we selected the symptoms of low qualified requirements based on ISO29148:2011, 3) we analyzed five Software Requirements Specification (SRS) documents to find these symptoms, 3) people who have prepared the documents were categorized in four classes to specify the more/less knowledge and confidence they have regarding the symptoms, and 4) finally, the relation of lack of enough knowledge and confidence to symptoms of low quality was investigated. The results revealed that the simultaneous deficiency of confidence and knowledge has more negative effects in comparison with a deficiency of knowledge or confidence. [Contribution] In brief, this study has achieved these results: 1) the realization that a combined lack of knowledge and confidence has a larger effect on requirements quality than only one of the two factors, 2) the relation between low qualified requirements and requirements engineers’ needs for knowledge and confidence, and 3) variety of requirements engineers’ needs for knowledge based on their abilities to make discriminative and consistent decisions. © 2021, Springer Nature Switzerland AG.
|
|
| 3. |
- Fischbach, Jannik, et al.
(författare)
-
Automatic Detection of Causality in Requirement Artifacts : The CiRA Approach
- 2021
-
Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer Science and Business Media Deutschland GmbH. - 9783030731274 ; , s. 19-36
-
Konferensbidrag (refereegranskat)abstract
- [Context & motivation:] System behavior is often expressed by causal relations in requirements (e.g., If event 1, then event 2). Automatically extracting this embedded causal knowledge supports not only reasoning about requirements dependencies, but also various automated engineering tasks such as seamless derivation of test cases. However, causality extraction from natural language (NL) is still an open research challenge as existing approaches fail to extract causality with reasonable performance. [Question/problem:] We understand causality extraction from requirements as a two-step problem: First, we need to detect if requirements have causal properties or not. Second, we need to understand and extract their causal relations. At present, though, we lack knowledge about the form and complexity of causality in requirements, which is necessary to develop a suitable approach addressing these two problems. [Principal ideas/results:] We conduct an exploratory case study with 14,983 sentences from 53 requirements documents originating from 18 different domains and shed light on the form and complexity of causality in requirements. Based on our findings, we develop a tool-supported approach for causality detection (CiRA, standing for Causality in Requirement Artifacts). This constitutes a first step towards causality extraction from NL requirements. [Contribution:] We report on a case study and the resulting tool-supported approach for causality detection in requirements. Our case study corroborates, among other things, that causality is, in fact, a widely used linguistic pattern to describe system behavior, as about a third of the analyzed sentences are causal. We further demonstrate that our tool CiRA achieves a macro-F 1 score of 82% on real word data and that it outperforms related approaches with an average gain of 11.06% in macro-Recall and 11.43% in macro-Precision. Finally, we disclose our open data sets as well as our tool to foster the discourse on the automatic detection of causality in the RE community. © 2021, Springer Nature Switzerland AG.
|
|
